Edited Books
V. N. Gudivada, V. V. Raghavan, V. Govindaraju, C. R. Rao (Editors), Cognitive Computing- Theory and Applications: Handbook of Statistics (Volume 35), September 2016,ISBN 978-0-444-63744-4, Elsevier, Amsterdam, Netherlands.
V. Govindaraju, V. V. Raghavan, C. R. Rao (Editors), Big Data Analytics: Handbook of Statistics (Volume 33), July 2015,ISBN: 978-0-444-63492-4, Elsevier, Amsterdam, Netherlands.
Edited Conference Proceedings
Victor S. Sheng, Chindo Hicks, Charles Ling, Vijay Raghavan and Xindong Wu, (Editors), Proceedings of the 2023 IEEE International Conference on Knowledge Graph, 1-2 December 2023, Shanghai, PRC, IEEE Computer Society, Los Alamitos, CA.
Shusaku Tsumoto, Yukio Ohsawa, Lei Chen, Dirk Van den Poel, Xiaohua Hu, Yoichi Motomura, Takuya Takagi, Lingfei Wu, Ying Xie, Akihiro Abe, Vijay Raghavan (Editors), Proceedings of the IEEE International Conference on Big Data, Big Data 2022, Osaka, Japan, December 17-20, 2022. IEEE 2022, ISBN 978-1-6654-8045-1
Vijay Raghavan, Srinivas Aluru, George Karypis, Lucio Miele and Xindong Wu, (Editors), Proceedings of the 2017 IEEE International Conference on Data Mining, 18-21 November 2017, New Orleans, LA, USA, IEEE Computer Society, Los Alamitos, CA.
Raju Gottumukkala, Xia Ning, Guozhu Dong, Vijay Raghavan, Srinivas Aluru, George Karypis, Lucio Miele and Xindong Wu, (Editors), Proceedings of the 2017 IEEE International Conference on Data Mining (Workshops), 18-21 November 2017, New Orleans, LA, USA, IEEE Computer Society, Los Alamitos, CA.
Xiaohua Hu, Tsau Young Lin, Vijay Raghavan, Benjamin W Wah, Ricardo A Baeza-Yates, Geoffrey Fox, Cyrus Shahabi, Matthew Smith, Qiang Yang, Rayid Ghani, Wei Fan, Ronny Lempel, Raghunath Nambiar (Editors), Proceedings of the 2013 IEEE International Conference on Big Data, 6-9 October 2013, Santa Clara, CA, USA, IEEE Computer Society, Los Alamitos, CA.
V. V. Raghavan, S. Ruegar, T. Yamaguchi and Y. Zhang (Editors), Proc. of the 2013 IEEE/WIC/ACM International Conference on Web Intelligence (WI-IAT 2013), Atlanta, GA, Nov. 17 – Nov. 20, 2013, IEEE Computer Society, Los Alamitos, CA.
V. V. Raghavan, Xiaolin Hu, C-J. Liau and J. Treur (Editors), Proc. of the 2013 IEEE/WIC/ACM International Conference on Intelligent Agent Technologies (WI-IAT 2013), Atlanta, GA, Nov. 17 – Nov. 20, 2013, IEEE Computer Society, Los Alamitos, CA.
Xiaohua Hu, T. Y. Lin, V. V. Raghavan, J. Grzymala-Busse, Q. Liu and A. Broder (Editors), Proc. of the 2010 IEEE International Conference on Granular Computing, San Jose, Ca, August 14 -16, 2010, IEEE Computer Society, Los Alamitos, CA.
X. J. Huang, I. King, V. V. Raghavan and S. Ruegar (Editors), Proc. of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence (WI-IAT 2010), Toronto, Canada, Aug. 31 – Sept. 3, 2010, IEEE Computer Society, Los Alamitos, CA
Y.-F. Li, V. V. Raghavan A. Broder and H. Ho (Eds.), Proceedings of the Web Intelligence and Intelligent Agent Technology (ACM/IEEE WI-IAT 2007) Workshops, Silicon Valley, CA, Nov. 2 -5, 2007.
J. Han, B. W. Wah, V. V. Raghavan, X. Wu and R. Rastogi (Eds.), "Proc. of the Fifth International Conference on Data Mining," IEEE Press, November 2005.
A. Bookstein, Y. Chiaramella, G. Salton and V. V. Raghavan (Eds.), ‘‘Proc. of the 14th International ACM- SIGIR Conference on Research and Development in Information Retrieval,’ ACM Press, 1991.
J. S. Deogun and V. V. Raghavan (Eds.), Proc. of the 1987 South Central Regional ACM Conference,’’ USL Press, 1987.
V. V. Raghavan (Ed.), Proc. of the 8th International ACM-SIGIR Conference on Research and Development in Information Retrieval,’ ACM Press, 1985.
Edited Journal Special Issues
V. N. Gudivada, V. V. Raghavan and L. Berti-Equille (Guest Editors), Special Issue on “Data Quality in Big Data: Problems and Solutions,” IEEE Trans. on Big Data, Volume nn, Issue n, 2019, IEEE Computer Society, Los Alamitos, CA.
M.D. Lytras, V. V. Raghavan and E. Damiani (Guest Editors), Special Issue on Big Data and Data Analytics Research: Challenging Data and Web Science for Next Generation High Performance Information Systems, Int’l J. on Semantic Web and Information Systems, Volume 13, No.1, January – March 2017, IGI Global, Hershey, PA.
V. N. Gudivada, R. Baeza-Yates and V. V. Raghavan, (Guest Editors), Special Issue on “Big Data Management,” IEEE Computer, Volume 48, Issue 3, March 2015, IEEE Computer Society, Los Alamitos, CA.
S. Ruegar, V. V. Raghavan, I. King, and X. J. Huang (Guest Editors), Neurocomputing- Special Issue on Advances in Web Intelligence, Vol. 76, No. 1, pp. 48 – 146, 2012.
V. V. Raghavan, Editor-in-Chief, The IEEE Intelligent Informatics Bulletin, Vol. 11 - 17, No. 1, Dec. 2010 - Dec. 2016.
J.-T. Yao, V. V. Raghavan and Z. Wu (Guest Eds.), Special Issue on ‘‘Web Information Fusion," An International J. on Information Fusion, Vol. 9, No. 4, Elsevier, October 2008.
V. V. Raghavan and J. S. Deogun and H. Sever (Guest Eds.), Special Issue on ‘‘Knowledge Discovery and Data Mining," J. Amer. Soc. for Information Sci., Vol. 49, No. 4, April 1998.
V. V. Raghavan and V. N. Gudivada (Guest Eds.), Special Issue on ‘‘Content- Based Picture Retrieval Systems,’ IEEE Computer, Vol. 28, No. 9, IEEE Press, September 1995, pp. 18-62.
Book Chapters
Ying Xie, Linh Le, Yiyun Zhou and V. V. Raghavan, "Deep Learning for Natural Language Processing," in Computational Analysis and Understanding of Natural Languages: Principles, Methods and Applications (Volume 38), (V. N. Gudivada, C. R. Rao, Eds.), Elsevier, Amsterdam, pp. 317 - 328, 2018.
Y. Xie, Jing He, and V. Raghavan, "Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs: A Big Data Perspective," in Data Science and Big Data Computing: Frameworks and Methodologies, (Mahmoud Zaigham, ed.), Springer-Verlag, Berlin-Heidelberg, pp. 79-92, 2016 (ISBN 978-3-319-31861-5).
M. K. Pusala, M. A. Salehi, J. R. Katukuri, Y. Xie, and V. V. Raghavan, "Massive Data Analysis: Tasks, Tools, Applications and Challenges," in Big Data Analytics- Methods and Applications, (S. Pyne, B. L. S. Prakasa Rao and S. B. Rao eds.), Chapter 2, Springer-Verlag, New Delhi, pp. 33-46, 2016 (ISBN 978-8-132-23626-9).
S. R. Venna, R. N. Gottumukkala and V. V. Raghavan, "Visual Analytic Decision-Making Environments for Large-scale Time-evolving Graphs," in Cognitive Computing- Theory and Applications: Handbook of Statistics (Volume 35), (V. N. Gudivada, V. V. Raghavan, V. Govindaraju, C. R. Rao, Eds.), Elsevier, Amsterdam, pp. 81 - 116, 2016.
V. N. Gudivada, Dhana Rao and V. V. Raghavan, "Big Data Driven Natural Language Processing Research and Applications," in Big Data Analytics: Handbook of Statistics (Volume 33), (V. Govindaraju, V. V. Raghavan, C. R. Rao, Eds.), Elsevier, Amsterdam, pp. 203 - 238, 2015.
Y. Xie, T. Johnsten, V. Raghavan, R. Benton and W. Bush, "A Comprehensive Granular Model for Decision Making with Complex Data," in Granular Computing and Decision Making: Interactive and Iterative Approaches, (W. Pedrycz and S-M. Chen, eds.), Springer-Verlag, Berlin-Heidelberg, pp. 33-46, 2015 (ISBN 978-3-319-16828-9).
Y. Xie, J. Katukuri, Vijay. V. Raghavan, and T Presti, "Conceptual Biology Research Supporting Platform: Current Design and Future Directions," in Applications of Computational Intelligence in Biology: Current Trends and Open Problems, (Tomasz G. Smolinski, Mariofanna G. Milanova, and Aboul-Ella Hassanien, Eds.), Springer-Verlag Berlin Heidelberg, pp. 307-324, 2008.
B. Shah, R. Benton, Z. Wu, V. Raghavan, "Automatic and Semi-automatic Annotation Techniques for Images," in Semantic-Based Visual Information Retrieval, (Yu-Jin Zhang, ed.), IRM Press, Hershey, PA, pp. 112-134, 2007 (ISBN 1-59904-370-X).
Y. Xie, V. Raghavan, "A Probabilistic Logic-based Framework for Characterizing Knowledge Discovery in Databases," in Foundations of Data Mining and Knowledge Discovery, (T. Y. Lin, S. Ohsuga, C. J. Lian, S. Tsumoto, eds.), Springer-Verlag, Berlin-Heidelberg, pp. 87-100, 2005 (ISBN 3-540-26257-1).
V. Raghavan, N. Gudivada, Z. Wu, W. Grosky, ‘‘Information Retrieval,’’ in The PracticalHandbook of Internet Computing, (Munindar P. Singh, ed.), Chapman and Hall/CRC Press, Part-2, Ch. 12, 2004.
K.Efe, V. Raghavan, A. Lakhotia, ‘‘Content and Link Structure Analysis for Searching the Web,’’ Computational Web Intelligence: Intelligent Technology for Web Applications, (Y.-Q. Zhang, A. Kandel, T. Y. Lin and Y. Y. Yao, eds.), World Scientific Press, pp. 431-448, Aug 2004.
S. Noel, V. Raghavan, C. Chu, “Document Clustering, Visualization, and Retrieval via Link Mining,” in Clustering and Information Retrieval, (W. Wu, H. Xiong, S. Shekhar, eds.), Kluwer, Boston, MA, pp. 161-194, 2003.
T. D. Johnsten and V. V. Raghavan, “Impact of Decision-Region based classification Mining Algorithms on Database Security," in J. Hale and V. Atluri (eds.), Research Advances in Database and Information Systems Security, Kluwer Academic, Norwell, MA, pp. 171-191, 2000.
J. S. Deogun, V. V. Raghavan, A. Sarkar and H. Sever, “Data Mining: Trends in Research and
Development,” in T. Y. Lin and Nick Cercone (eds.), Rough Sets and Data Mining: Analysis of Imprecise Data, Kluwer Academic, pp. 9-46, 1997.
V. N. Gudivada, V. V. Raghavan and K. Vanapipat, ‘‘Unified Approach to Data Modeling and Retrieval for a Class of Image Database Applications,’’ in S. Jajodia and V. S. Subrahmanian (eds.), Multimedia Database Systems: Issues and Research Directions, Springer-Verlag, pp. 37-78, 1995.
V. V. Raghavan, S. K. M. Wong and W. Ziarko, “Vector Space Model in Information Retrieval,” in A. Kent and J. G. Williams (Eds.), Encyclopedia of Computer Science and Technology, Marcel Dekker, Inc., Vol. 22, Supplement 7, pp. 423-446, 1990.
Special Report to the National Science Foundation
V. V. Raghavan, Y. Xie, T. Johnsten, R. G. Benton, B. Lemoine and D. Difallah, "Concept Map-based Organizer for REsearch Portfolios (C-MORE)," in CISE and SBE AC Subcomittee on Discovery in a Research Portfolio: Tools for Structuring, Analyzing, Visualizing and Interacting with Proposal and Award Portfolios, Nov. 2011.
Referred Journal Papers
Tarikul I. Milon, Krishna Rauniyar, Sara Furman, Khairum H. Orthi, Yingchun Wang, Vijay Raghavan and Wu Xu. “Representing and Quantifying Conformational Changes of Kinases and Phosphatases Using the TSR-Based Algorithm,” Kinases Phosphatases, 2(4):315-339, 2024.
Tarikul I. Milon, Yuhong Wang, Ryan L. Fontenot, Poorya Khajouie, Francois Villinger, Vijay Raghavan, Wu Xu. “Development of a novel representation of drug 3D structures and enhancement of the TSR-based method for probing drug and target interactions,” Computational Biology and Chemistry, 112(108117), 2024.
T. Sarkar, Y-W. Chen, Y. Wang, Y-X. Chen, F. Chen, C. R. Reaux, L. E. Moore, V.V. Raghavan,W. Xu, “Introducing mirror-image discrimination capability to the TSR-based method for capturing stereo geometry and understanding hierarchical structure relationships of protein receptor family,” Computational Biology and Chemistry, Vol. 103, pp.107824, 2023. https://doi.org/10.1016/j.compbiolchem.2023.107824
S. Katragadda, R.T. Bhupatiraju, V. V. Raghavan, Z. Ashkar, and R. Gottumukkala,” Examining the COVID‑19 case growth rate due to visitor vs. local mobility in the United States using machine learning,” Sci Rep 12, pp. 12337, 2022. https://doi.org/10.1038/s41598-022-16561-0 [IF 4.9]
T. Sarkar, C. R. Reaux, J.-X. Li, V. V. Raghavan, and W. Xu, “The specific applications of the TSR-based method in identifying Zn2+ binding sites of proteases and ACE/ACE2,” Data in Brief, Vol 45, pp. 108629, 2022. https://doi.org/10.1016/j.dib.2022.108629
M. Hassan, Md. E, Haque, M. E. Tozal, V. V. Raghavan and R. Agrawal, “Intrusion detection using payload embeddings,” IEEE Access, Vol. 10, pp. 4015-4030, 2022. https://doi:.org/10.1109/ACCESS.2021.3139835
R. Gottumukkala, S. Katragadda, R. T. Bhupatiraju, V. V. Raghavan, et al. “Exploring the relationship between mobility and COVID− 19 infection rates for the second peak in the United States using phase-wise association,” BMC Public Health 21, 1669, 2021. https://doi.org/10.1186/s12889-021-11657-0
S. Katragadda, R. Gottumukkala, R. T. Bhupatiraju, V. V. Raghavan, et al. “Association mining based approach to analyze COVID-19 response and case growth in the United States,” Sci Rep 11, 18635, 2021. https://doi.org/10.1038/s41598-021-96912-5
S. R. Venna, S. Katragadda, V. V. Raghavan, et al. “River Stage Forecasting using Enhanced Partial Correlation Graph,” Water Resour Manage 35, 4111–4126, 2021. https://doi.org/10.1007/s11269-021-02933-0
T. Sarkar, V.V. Raghavan, F. Chen, A. Riley, S. Zhou and W. Xu. “Exploring the effectiveness of the TSR-based protein 3-D structural comparison method for protein clustering, and structural motif identification and discovery of protein kinases, hydrolases, and SARS-CoV-2's protein via the application of amino acid grouping,” Computational Biology and Chemistry Jun;92, 107479, 2021 (Impact factor: 2.877). https://pubmed.ncbi.nlm.nih.gov/33951604/
V. S. Kondra, T. Sarkar, V. V. Raghavan, and W. Xu. “Development of a TSR-based method for protein 3-D structural comparison with its applications to protein classification and motif discovery,” Frontiers in Chemistry-Theoretical and Computational Chemistry8, 602291, 2021 (Impact factor: 3.782). https://www.frontiersin.org/articles/10.3389/fchem.2020.602291/full
T. Sarkar, V. S. Kondra , W. Xu and V. V. Raghavan. “Identification of Common Structural Motifs from Proteases, Kinases, and Phosphatases Using a New Structure Comparison Method,” Biomed J Sci & Tech Res 26(5)-2020. BJSTR, short communications. https://biomedres.us/pdfs/BJSTR.MS.ID.004411.pdf
Linh Le, Ying Xie, and V. V. Raghavan, “KNN Loss and Deep KNN,” Fundamenta Informaticae, vol. 182, no. 2, pp. 95-110, 2021.
G. Cao, A. Iosifidis, M. Gabbouj, V. V. Raghavan and R. N. Gottumukkala, "Deep Multi-view Learning to Rank", IEEE Trans. on Knowledge and Data Engineering, Sept. 2019 (Early Access). https://doi.org/10.1109/TKDE.2019.2942590
S. R. Venna, A. Tavanaei, R. N. Gottumukkala, V. V. Raghavan, A, S. Maida and S. Nichols, “A Novel Data-Driven Model for Real-Time Influenza Forecasting,” IEEE Access, Vol. 7, No. 1, pp. 7691 - 7701, Dec. 2019 (Impact factor: 5.56). DOI: 10.1109/ACCESS.2018.2888585
M. B. Duggimpudi, Shaaban Abbady, Jian Chen and V. V. Raghavan, “Spatio-Temporal Outlier Detection Algorithms Based on Computing Behavioral Outlierness Factor,” Data & Knowledge Engineering(DKE), An Elsevier Journal, Vol. 122, pp. 1 – 24, July 2019. https://doi.org/10.1016/j.datak.2017.12.001
M. D. Lytras, V. V. Raghavan and E. Damiani, “Big Data and Data Analytics Research: From Metaphors to Value Space for Collective Wisdom in Human Decision Making and Smart Machines,” International J. on Semantic Web and Information Systems, Vol. 13, No. 1, pp. 1 - 10, January – March 2017.
V.N. Gudivada, Dhana Rao and V. V. Raghavan, “Renaissance in Database Management: Navigating the Landscape of Candidate Systems,” IEEE Computer, Vol. 49, No. 4, pp. 31 - 42, April. 2016.
R. N. Gottumukkala, S. R. Venna and V. V. Raghavan, “Visual Analytics of Time-Evolving Large Graphs,” Feature Article, IEEE Intelligent Informatics Bulletin, Vol. 16, No.1, pp. 10 – 16, Dec. 2015.
V.N. Gudivada, R. Baeza-Yates and V. V. Raghavan, “Big Data: Promises and Problems,” IEEE Computer, Vol. 48, No. 3, pp. 20 -23, March. 2015.
M. S. Ayhan, R.G. Benton, V. V. Raghavan, S.K. Choubey, “Exploitation of 3D Stereotactic Surface Projection for predictive modelling of Alzheimer's Disease,” International J. Data Mining and Bioinformatics, Vol. 7, No. 2, pp. 146 - 165, 2013.
J. Katukuri, Y. Xie, V. V. Raghavan, and A. Gupta, “Hypotheses generation as supervised link discovery with automated class labeling on large-scale biomedical concept networks,” BMC Genomics 2012, 13(Suppl 3):S5 (11 June 2012), (Impact factor: 4.397).
S. Ruegar, V. V. Raghavan, I. King, and X. J. Huang, “Special issue on Advances in Web Intelligence- Guest Editors’ Introduction,” Neurocomputing, Vol. 76, No. 1, pp. 48 – 49, 2012.
R. Singh, T. Johnsten, V.V. Raghavan, Y. Xie, “Efficient Algorithm for Discovering Potentially Interesting Patterns,” International Journal of Granular Computing, Rough Sets and Intelligent Systems, Vol. 2, No. 2, pp. 107-122, 2011.
N. M. Hk. AlSudairy, V. V. Raghavan, A. M. Hafez and H. I. Mathkour, “Connection Subgraphs: A survey,” International Journal of Applied Sciences, 11(17): 3221-3232, 2011. http://docsdrive.com/pdfs/ansinet/jas/2011/3221-3232.pdf
J. Katukuri, Y. Xie, V. V. Raghavan, “Biomedical Relationship Extraction from literature based on bio-semantic token subsequences,” International Journal of Functional Informatics and Personalised Medicine, Vol. 3, No. 1, pp.16–28, 2010.
Y. Xie, V. V. Raghavan, A. Young, “Hyper-Textual Language Model for Web Information Retrieval,” International Journal of Granular Computing, Rough Sets and Intelligent Systems, Vol. 1, No. 2, pp. 190-202, 2009.
J. T. Yao, V. V. Raghavan, Z. Wu, “Web Information Fusion: A Review of the State of the Art,” An International J. on Information Fusion- Multi-Sensor, Multi-Source Information Fusion, 9(4): 446-449, Oct. 2008, Elsevier.
Y. Xie and V. V. Raghavan, "Language-Modeling Kernel Based Approach for Information Retrieval," Journal of the American Society for Information Science and Technology, 58(14), 2007, pp. 2353-2365.
Y. Chang, M. Kim and V. Raghavan, "Construction of Query Concepts Based on Feature Clustering of Documents," Information Retrieval, Vol. 9, 2006, pp. 231-248.
B. Shah, V. Raghavan, P. Dhatric and X. Zhao, "A Cluster-Based Approach for Efficient Content-Based Image Retrieval using a Similarity-preserving Space Transformation Method," Journal of the American Society for Information Science and Technology, 57(12), 2006, pp. 1694-1707.
J. Choi, M. Kim and V. Raghavan, "Adaptive Relevance Feedback Method of Extended Boolean Model using Hierarchical Clustering Techniques," Information Processing & Management, 42(2), March 2006, pp. 331-349.
B. Shah, K. Ramachandran and V. Raghavan, "A Hybrid Approach for Data Warehouse View Selection," Inter- national J. of Data Warehousing & Mining, 2(2), April-June 2006, pp. 1-37.
Y. Xie, V. Raghavan, P. Dhatric and X. Zhao, “A New Fuzzy Clustering Algorithm for Optimally Finding Granular Prototypes,” in International Journal of Approximate Reasoning, Special Issue on Data Mining and Granular Computing, 40 (1-2), July 2005, pp. 109-124. (Ranked #11 in Fall 2005 for frequency of papers accessed on-line from the journal).
S. Noel, C. Chu and V. Raghavan, “Co-citation Count vs. Correlation for Influence Network Visualization,” Information Visualization, Vol. 3, No. 2, 2003, pp. 160-170.
M. Kubat, A. Hafez, V. V. Raghavan, J. Lekkala, and W. K. Chen, “Itemset Trees for Targeted Association Mining,” IEEE Trans. on Knowledge and Data Engineering, Vol. 15, No. 6, 2003, pp. 1522-1534.
M. Kim, V. V. Raghavan, and J. S. Deogun, “Concept Based Retrieval using Generalized Retrieval Functions,” Fundamenta Informaticae, 47(1-2):119-135, 2001.
J. Yoon, V. V. Raghavan, V. Chakilam and L. Kerschberg, ‘‘Bitcube: A Three-Dimensional Bitmap Indexing for XML Documents,’’ J. of Intelligent Information Systems, 17(2/3):241-254, Nov. 2001.
A. H. Alsaffar, J. S. Deogun, V. V. Raghavan and H. Sever, ‘‘Enhancing Concept-based Retrieval based on Minimal Term Sets", In Z. Ras and A. Skowron (eds.), Special Issue on Methodologies for Intelligent Systems, J. of Intelligent Information Systems, Vol. 14, No. 2-3: 155-173, 2000.
N. Tadayon and V. V. Raghavan, ‘‘Improving perceptron convergence algorithm for retrieval systems," PatternRecognition Letters, Vol. 20, No. 11-13, 1999, pp. 1331-1336.
P. Bollmann-Sdorra and V. V. Raghavan, ‘‘On the Necessity of Term Dependence in a Query Space for Weighted Retrieval," J. Amer. Soc. for Information Sci., Vol. 49, No. 13, 1998, pp. 1161-1168.
V. V. Raghavan, J. S. Deogun and H. Sever, “Data Mining: Trends and Issues- Guest Editors’ Introduction,” J. Amer. Soc. for Information Sci., Vol. 49, No. 4, 1998, pp. 397-402.
S. K. Choubey, J. S. Deogun, V. V. Raghavan and H. Sever, “On Feature Selection and Effective Classifiers,” J. Amer. Soc. for Information Sci., Vol. 49, No. 4, 1998, pp. 423-434.
V. N. Gudivada, V. V. Raghavan, W. I. Grosky and R. Kasanagottu, “Information Retrieval on the World-Wide Web,” IEEE Internet Computing, Vol. 1, No. 5, 1997, pp. 58-68.
S. K. Choubey and V. V. Raghavan, “Generic and Fully Automatic Content-based Image Retrieval Using Color,” Pattern Recognition Letters, Vol. 18, No. 11-13, 1997, pp. 1233-1240.
V. N. Gudivada and V. V. Raghavan, ‘‘Modeling and Retrieving Images by Content," Information Processing & Management, Vol. 33, No. 4, 1997, pp. 427-452.
J. N. Bhuyan, J. S. Deogun, and V. V. Raghavan, ‘‘Algorithms for the Boundary Selection Problem in Information Retrieval,’’ Algorithmica, Vol. 17, 1997, pp. 133-161.
V. N. Gudivada and V. V. Raghavan, ‘‘Content-based Image Retrieval Systems,’’ IEEE Computer, Vol. 8, No. 9, Sept. 1995, pp. 18-22.
S. K. Bhatia, J. S. Deogun and V. V. Raghavan, ‘‘Conceptual Query Formulation and Retrieval,’’ Journal of Intelligent Information Systems, Vol. 5, No. 3, 1995, pp. 183-209.
N. Pissinou, V. V. Raghavan and K. Vanapipat, ‘‘RIMM: A Reactive Multidatabase Integration Model,’’ Informatica- An International J. of Computing and Informatics, Vol. 19, No. 2, 1995, pp. 177-194.
V. N. Gudivada and V. V. Raghavan, ‘‘Design and Evaluation of Algorithms for Image Retrieval by Spatial Similarity,’’ ACM Trans. on Information Systems, Vol. 13, No. 2, April 1995, pp. 115-144.
P. Bollmann, V. V. Raghavan, ‘‘On the Delusiveness of Adopting a Common Space for Modeling IR Objects: Are Queries Documents?’’ J. Amer. Soc. for Information Sci., Vol. 44, December 1993, pp. 579-587.
P. Bollmann, V. V. Raghavan, G. S. Jung and L. -C. Shu, ‘‘On Probabilistic Notions of Precision as a Function of Recall,’’ Information Processing and Management, Vol. 28, May-June 1992, pp. 291-315.
S. K. Mishra, V. V. Raghavan and N. -F. Tzeng, ‘‘Efficient Algorithms for Selection of Recovery Points in Tree Task Models,’’ IEEE Trans. on Software Engineering, Vol. SE-17, July 1991, pp. 731-734, (Concise Paper).
L. V. Saxton and V. V. Raghavan, ‘‘Design of an Integrated Information Retrieval/Database Management System,’’ IEEE Trans. on Data and Knowledge Engineering, June 1990, Vol. 2, pp. 210-219.
V. V. Raghavan, P. Bollmann and G. S. Jung, ‘‘A Critical Investigation of Recall and Precision as Measures of Retrieval System Performance,’’ ACM Trans. on Information Systems, July 1989, Vol. 7, pp. 205-229. (One of 6 papers selected from about 110 papers submitted to ACM-SIGIR Conference to be published in a special issue of this journal.)
S. K. M. Wong, W. Ziarko, V. V. Raghavan and P. C. N. Wong, ‘‘Extended Boolean Query Processing in the Generalized Vector Space Model,’’ Information Systems, 1989, Vol. 14, pp. 47-63.
J. S. Deogun and V. V. Raghavan, ‘‘Integration of Information Retrieval and Database Management Systems,’’ Information Processing and Management - Special Issue: The Potential for Improvements in Commercial Retrieval Systems, 1988, Vol. 24, pp. 303-313.
S. K. M. Wong, W. Ziarko, V. V. Raghavan and P. C. N. Wong, ‘‘On Modeling Information Retrieval Concepts in Vector Spaces,’’ ACM Trans. on Database Systems, June 1987, Vol. 12, pp. 299-321.
V. V. Raghavan and R. S. Sharma, ‘‘A Framework and a Prototype for Intelligent Organization of Information,’’ The Canadian J. of Information Science, 1986, Vol. 11, pp. 88-101.
V. V. Raghavan and S. K. M. Wong, ‘‘A Critical Analysis of Vector Space Model for Information Retrieval,’’ J.Amer. Soc. for Information Sci., 1986, Vol. 37, pp. 279-287.
P. Prusinkiewicz and V. V. Raghavan, ‘‘A Simple, Space-optimal Contour Algorithm for a Set of Iso-rectangles," Congress Numerantium, May 1985, Vol. 46, pp. 249-270.
J. S. Deogun, V. V. Raghavan and T. K. W. Tsou, ‘‘Organization of Clustered Files for Consecutive Retrieval,’’ ACM Trans. on Database Systems, Dec. 1984, Vol. 9, pp. 646-671.
M. Y. L. Ip, L. V. Saxton and V. V. Raghavan, ‘‘On the Selection of an Optimal Set of Indexes,’’ IEEE Trans. on Software Engineering, March 1983, Vol. SE-9, pp. 135-143. (One of 4 papers selected from about 60 papers presented at IEEE 5th International COMPSAC Conference to be included in a special issue of this journal).
V. V. Raghavan and J. S. Deogun, ‘‘Information Retrieval Research: Strategies and User Implications,’’ Information Technology: Research and Development, April 1982, Vol. 1, pp. 157-171.
V. V. Raghavan and C. T. Yu, ‘‘A Comparison of the Stability Characteristics of Some Graph Theoretic Clustering Methods,’’ IEEE Transactions on Pattern Analysis and Machine Intelligence, 1981, Vol. PAMI-3, pp. 393-402.
V. V. Raghavan and C. T. Yu, ‘‘Experiments on the Determination of the Relationships between Terms,’’ ACM Transactions on Database Systems, 1979, Vol. 4, pp. 240-260. (Only paper selected from about 15 papers presented at First Annual International ACM-SIGIR Conference to be included for publication in this journal)
C. T. Yu and V. V. Raghavan, ‘‘A Single Pass Method for Determining the Relationships between Terms,’’ J. Amer. Soc. for Information Sci., 1977, Vol. 28, pp. 345-354.
V. V. Raghavan and C. T. Yu, ‘‘A Note on a Multidimensional Searching Problem,’’ Information Processing Letters, 1977, Vol. 6, pp. 133-135.
Referred Papers in Conference Proceedings
M. Hassan, M. E. Tozal, V. Swarup, S. Noel, R. Gottumukkala, V. Raghavan, “Anomalous Link Detection in Dynamically Evolving Scale-Free-Like Networked Systems,” 2024 IEEE International Systems Conference (SysCon), 1-8.
J. Chen, Y. He and V. Raghavan, "Learning with Partial Multi-Outlooks," 2020 International Joint Conference on Neural Networks (IJCNN), Glasgow, UK, 2020, pp. 1-8. https://ieeexplore.ieee.org/document/9207633
Katragadda, Satya, Raju Gottumukkala, Siva Venna, Nicholas Lipari, Shailendra Gaikwad, Murali Pusala, Jian Chen, Christoph W. Borst, Vijay Raghavan, and Magdy Bayoumi, "VAStream: A Visual Analytics System for Fast Data Streams," In Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning), pp. 76 - 83. ACM, July 28 - Aug. 1, 2019. https://doi.org/10.1145/3332186.3332256
Md. E. Haque, S. M. Zobaed, M. E. Tozal and V. V. Raghavan, “Divergence Based Non-Negative Matrix Factorization for top-N Recommendations,” Proc. of the 52nd Annual Hawaii International Conference on System Sciences (HICSS 2019), Waikoloa, HI, Jan. 2019. http://hdl.handle.net/10125/59485
S. Katragadda, R. N. Gottumukkala, M. K. Pusala, V. V. Raghavan and J. Wojtkiewicz, “Distributed Real Time Link Prediction on Graph Streams,” Third Workshop on Real-time and Stream Analytics in Big Data & Stream Data Management, in 2018 IEEE International Conference on Big Data, Seattle, WA, Dec. 2018.
Linh Le, Ying Xie, and V. V. Raghavan, “Deep Similarity-Enhanced K Nearest Neighbors,” Special session on Information Granulation in Data Science and Scalable Computing, in 2018 IEEE Data, Seattle, WA, Dec. 2018.
M. S. Ayhan and V. V. Raghavan, “Efficient and Automatic Subspace Relevance Determination viaMultiple Kernel Learning for High-dimensional Neuroimaging Data,” In Springer Lecture Notes in Computer Science, Vol. nn, xxx (Eds.), 11thInternational Conference on Brain Informatics, Arlington, Dec. 2018.
A. Tavanaei, R. N. Gottumukkala, A. S. Maida and V. V. Raghavan, “Unsupervised Learning to RankAggregation using Parameterized Function Optimization,” Special Session on Data Mining and Knowledge Discovery (IJCNN-S8n-1), 2018 Int’l Joint Conference on Neural Networks (IJCNN 2018), Rio De Janeiro, Brazil, July 2018.
S. Abbady, C. Ke, J. Lavergne, J. Chen, V. V. Raghavan and R. G. Benton, “Online Mining for Association Rules and Collective Anomalies in Data Streams,” Second Workshop on Real-time and Stream Processing in Big Data, in 2017 IEEE International Conference on Big Data, Boston, MA, 2017, pp. 1 – 10.
M. K. Pusala, R. G. Benton, V. V. Raghavan and R. N. Gottumukkala, "Supervised approach to rank predicted links using interestingness measures," 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, 2017, pp. 1085-1092. doi: 10.1109/BIBM.2017.8217807 url: http://ieeexplore.ieee.org/document/8217807/
S. Singh, W. Xu and V. V. Raghavan, "Descriptor based protein structure representation using triangular spatial relationships in 3-D," 2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Kansas City, MO, USA, 2017, pp. 1114-1118. doi:10.1109/BIBM.2017.8217812 url: http://ieeexplore.ieee.org/document/8217812/
M. S. Cinar, B. Genc, H. Sever and V. V. Raghavan, “Analyzing Structure of Terrorists Networks by Using Graph Metrics,” The 8th IEEE International Conference on Big Knowledge (IEEE ICBK 2017), Hefei, PRC, pp. 9 – 16, Aug. 2017.
Nasser, H. Sever and V. V. Raghavan, “Utilization Rough Sets for Intrusion Detection,” Position Paper, Joint 17th World Congress of International Fuzzy Systems Association and 9th International Conference on Soft Computing and Intelligent Systems (IFSA-SCIS 2017), Otsu, Japan, June 2017.
S. Katragadda, R. G. Benton and V. V. Raghavan, “Sub-Event Detection from Tweets,” Special Session on Datastream Mining (IJCNN-S12+29), 2017 Int’l Joint Conference on Neural Networks (IJCNN 2017), Anchorage, AK, May 2017.
A. Sharif and V. V. Raghavan, “Link Prediction Based Hybrid Recommendation System using User-Page Preference Graphs,” 2017 Int’l Joint Conference on Neural Networks (IJCNN 2017), Anchorage, AK, May 2017.
S. Katragadda, R. G. Benton and V. V. Raghavan, “Framework for Real-Time Event Detection using Multiple Social Media Sources,” Proc. of the 50th Annual Hawaii International Conference on System Sciences (HICSS 2017), Waikoloa, HI, Jan. 2017.
J. Woodworth, M. A. Salehi, V. V. Raghavan, “S3C: An Architecture for Space-Efficient Semantic Search over Encrypted Data in the Cloud,” in Workshop on Privacy and Security of Big Data(PSBD) as part of the IEEE Big Data Conference, Washington DC, USA, Dec. 2016.
M. B. Duggimpudi, A. Moursy, E. Ali and V. V. Raghavan, “An Ontology-based Architecture for Providing Insights in Wireless Networks Domain,” Proc. of the IEEE/WIC/ACM International Conference on Web Intelligence (WI 2016), Omaha, NE, Oct. 2016.
S. Katragadda, R. G. Benton, S. Virani and V. V. Raghavan, “Detection of Event Onset Using Twitter,” Special Session on Online Real-Time Learning Strategies for Large Data Streams (IJCNN-36), 2016 Int’l Joint Conference on Neural Networks (IJCNN 2016), Vancouver, Canada., July 2016.
S. Katragadda, H. Karnati, M. K. Pusala, V. V. Raghavan and R. G. Benton, “Detecting Adverse Drug Effects Using Link Classification on Twitter Data,” 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), Washington, D.C., Nov. 2015.
Elshaimaa Ali and V. V. Raghavan, “Extending SKOS: A Wikipedia-based Unified Annotation Model for Creating Interoperable Domain Ontologies,” Proc. of the ISMIS 2015, Warsaw, Poland, pp. 243 – 250, Oct. 2015.
N. M. Hk. AlSudairy, A. M. Hafez, V. V. Raghavan and H. I. Mathkour, “Candidate Graph Generation Algorithm,” Proc. of the 9th International Conf. on Computer Engineering and Applications (CEA 2015)- in conjunction with WSEAS, Feb. 2015. http://www.wseas.org/main/conferences/2015/Dubai/Program.pdf
V. N. Gudivada, D. Rao and V. V. Raghavan, “NoSQL Systems for Big Data Management,” Proc. of the 2014 IEEE World Congress on Services, Anchorage, Alaska, pp. 190–197, 2014.
Mohammad Amir Sharif, Vijay V. Raghavan, “A Clustering Based Scalable Hybrid Approach for Web Page Recommendation.” Proc. of the 2014 IEEE International Conference on Big Data: 2nd Workshop on Scalable Machine Learning: Theory and Applications, Oct. 2014, Washington, D.C.
Satya Katragadda, Miao Jin, Vijay V. Raghavan, “An Unsupervised Approach to Identify Location Based on the Content of User's Tweet History.” AMT 2014: 311-323.
Mohammad Amir Sharif, Vijay V. Raghavan, “A Large-Scale, Hybrid Approach for Recommending Pages Based on Previous User Click Pattern and Content.” ISMIS 2014: 103-112.
Ying Xie, Jing (Selena) He, Vijay V. Raghavan, “MapReduce-Accelerated Framework for Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs,” Proc. of the 2014 International Conference on Advances in Big Data Analytics (ABDA'14), July 21-24, 2014, Las Vegas, Nevada, USA. http://www.world-academy-of-science.org/worldcomp14/ws/program/abdicmgca24
J. Lavergne, R. G. Benton, V. V. Raghavan, A. Hafez, “DynTARM: An In-Memory Data Structure for Targeted Strong and Rare Association Rule Mining Over Time-Varying Domains,” Proc. of the IEEE/WIC/ACM International Conference on Web Intelligence, Atlanta, GA, pp. 298 – 306, Nov. 2013.
M. S. Ayhan, R. G. Benton, V. V. Raghavan, S. K. Choubey, “Composite Kernels for Automatic Relevance Determination in Computerized Diagnosis of Alzheimer's Disease,” In Springer Lecture Notes in Computer Science, Vol. 8211, Imamura, K., Usui, S., Shirao, T., Kasamatsu, T., Schwabe, L., Zhong, N. (Eds.), International Conference on Brain and Health Informatics, Maebashi, Japan, pp. 126 - 137, Oct. 2013.
R. G. Benton, S. K. Choubey, D. G. Clark, T. D. Johnsten, V. V. Raghavan, “Diagnosis and Grading of Alzheimer's Disease via Automatic Classification of FDG-PET Scans,” In Springer Lecture Notes in Computer Science, Vol. 8211, Imamura, K., Usui, S., Shirao, T., Kasamatsu, T., Schwabe, L., Zhong, N. (Eds.), International Conference on Brain and Health Informatics, Maebashi, Japan, pp. 266 - 276, Oct. 2013.
V. V. Raghavan and Elshaimaa Ali, “Modeling the Wikipedia for Web Annotation: Towards Building a Semantic Annotation Framework,” Proc. of the IADIS International Conference WWW/INTERNET 2013, Fort Worth, TX, pp. 243 – 250, Oct. 2013.
V. V. Raghavan, R. G. Benton, T. D. Johnsten, Y. Xie, “Representations for Large-Scale Sequence Data Mining: A Tale of Two Vector Space Models,” Proc. of the Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing: 14th International Conference, RSFDGrc 2013, Halifax, NS, Canada, pp. 15 – 25, Oct. 2013, (Invited Paper).
J. Lavergne, R. G. Benton, V. V. Raghavan, “Min-Max Itemset Trees for Dense and Categorical Datasets,” Proc. of the 20th International Symposium on Methodologies for Intelligent Systems (ISMIS 2012), Macau, China, pp. 51 – 60, Dec. 2012.
J. Lavergne, R. G. Benton, V. V. Raghavan, “TRARM-RelSup: Targeted Rare Association Rule Mining Using Itemset Trees and the Relative Support Measure,” Proc. of the 20th International Symposium on Methodologies for Intelligent Systems (ISMIS 2012), Macau, China, pp. 61 – 70, Dec. 2012.
M. S. Ayhan, R.G. Benton, V. V. Raghavan, S.K. Choubey, “Utilization of Domain-Knowledge for Simplicity and Comprehensibility in Predictive Modeling of Alzheimer's Disease,”IEEE workshop on Multiscale Biomedical Imaging Analysis (MBIA'12) at BIBM 2012, Philadelphia, PA, Dec. 2012.
Y. Xie, J. Fisher, V. V. Raghavan, T. Johnsten and C. Akkoc, “Granular approach for protein sequence analysis,” Proc. of the 8th International Conference on Rough Sets and Current Trends in Computing, Chengdu, China, pp. 414-421, Aug. 2012.
Y. Xie and V. V. Raghavan, “A random walk model based approach for quantifying technology emergence and impact for research articles,” Proc. of 2012 IEEE International Conference on Granular Computing, Hangzhou, China, pp. 656 – 658, Aug. 2012.
A. De, E. Diaz, V. V. Raghavan, “Weighted Fuzzy Aggregation for Metasearch: An Application of Choquet Integral,” in Advances on Computational Intelligence (Eds. Salvatore Greco, Bernadette Bouchon-Meunier, Giulianella Coletti, Mario Fedrizzi, Benedetto Matarazzo, and Ronald R. Yager) Proc. of the 14th Int’l Conf. on Information Processing and Management of Uncertainty in Knowledge-based Systems, Catania, Italy, pp. 501-510, July 2012.
J. Katukuri, Y. Xie, V. V. Raghavan and A. Gupta, “Supervised Link Discovery on Large-Scale Biomedical Networks,” Proc. of the 2011 IEEE International Conf. on Bioinformatics & Biomedicine, Atlanta, GA, pp. 562-568, Nov. 2011.
D.E. Diffalah, R. G. Benton, T. Johnsten and V. V. Raghavan, “FAARM: Frequent Association Action Rules Mining using FP-Tree,” Proc. of the 2011 Workshop on Domain-Driven Data Mining, held in conjunction with IEEE International Conference on Data Mining 2011 (ICDM-2011), Dec. 2011, Vancouver, Canada.
R. Singh, T. Johnsten, V. V. Raghavan and Y. Xie, “An Efficient Algorithm for Discovering Positive and Negative Patterns with closed itemsets,” Proc. of the 2010 IEEE International Conf. on Granular Computing, San Jose, CA, pp. 414-419, August 2010.
D. Mundluru, V. V. Raghavan, and Z. Wu, “Automatically Extracting Web Data Records,” Proc. of the 6th International Conf. on Active Media Technology and Brain Informatics (AMT-BI 2010), Toronto, Canada, pp. 510-521, August 2010.
O. Aslanturk, E. A. Sezer, H. Sever and V. V. Raghavan, “Application of Cascading Rough Set-Based Classifiers on Authorship Attribution,” Proc. of the 2010 IEEE International Conf. on Granular Computing, San Jose, CA, pp. 656-660, August 2010.
M. S. Ayhan, R. G. Benton, V. V. Raghavan and S. K. Choubey, “Exploitation of 3D Stereotactic Surface Projection for Automated Classification of Alzheimer’s Disease according to Dementia Levels,” IEEE Int’l Conf. on Bioinformatics and Biomedicine (BIBM 2010), Hong Kong, China, pp. 516-519, Dec. 2010.
A. De, E. Diaz and V. V. Raghavan, “Search Engine Result Aggregation using Analytical Hierarchy Process,” In Proc. of the Web-based Information Retrieval Support Systems Workshop, held in conjunction with IEEE International Conference on WI-IAT 2010, Sept. 2010, Toronto, Canada.
F. M. Gulec, T. Bicakci, E. A. Sezer, H. Sever, and V. V. Raghavan, “Analyzing the Effectiveness of Pruning and Grouping Methods Used in Literature-Based Discovery Tools,” In Proc. of the Web-based Information Retrieval Support Systems, held in conjunction with IEEE International Conf. on WI-IAT 2010, Sept. 2010, Toronto, Canada.
K. Efe, V. V. Raghavan and S. K. Choubey, “Simulation Modeling Movable Hospital AssetsManaged with RFID Sensors”, Proc. of the 2009 Winter Simulation Conf., Austin, TX, December 2009.
J. R. Katukuri, Y. Xie and V. V. Raghavan, “Biomedical Relationship Extraction from Literature Based on Bio- semantic Token Sequences,” Proc. of the 2009 IEEE International Conf. on Bioinformatics & Biomedicine, Washington, D.C., November 2009.
R. Singh, T. Johnsten, V. V. Raghavan and Y. Xie, “An Efficient Algorithm for Discovering Positive and Negative Patterns,” Proc. of the 2009 IEEE International Conf. on Granular Computing, Lushan Mountain/ Nanchang, China, August 2009.
Y. Xie, V. V. Raghavan and A. Young, “Hyper-Textual Language Model for Web Information Retrieval,” Proc. of the 2008 IEEE International Conf. on Granular Computing, Hongzhou, China, 68-73, 2008.
Y. Xie, J. Katukuri, V. V. Raghavan and T. Johnsten, “Examining Granular Computing from a Modeling Perspective,” Proc. of the NAFIPS 2008, New York, 1-5, May 2008.
S. Chu, J. Chen, Z. Wu, V. V. Raghavan and H. Chu. “A Treemap-based Result Interface for Search Engine Users,” 12th International Conf. on Human-Computer Interaction (HCI 2007), Beijing, China, July 2007.
A. De., D. Diaz and V. V. Raghavan, "On Fuzzy Result Merging for Metasearch," Proceedings of the IEEE International Conference on Fuzzy Systems- FUZZ-IEEE 2007, Imperial College, London, U.K., pp. 1-6, July 2007.
A. De, E. D. Diaz and V. V. Raghavan, "A Fuzzy Search Engine Weighted Approach to Result Merging for Metasearch," in (Eds. A. An, J. Stefanowski, S. Ramanna, C. J. Butz, W. Pedrycz and G. Wang), Proceedings of the 11th International Conf., RSFDGrC 2007, Toronto, Canada, May 2007, pp. 95-102.
A. Doloc-Mihu and V. V. Raghavan, "Fusion and Kernel Type Selection in Adaptive Image Retrieval," in (ed. B. V. Dasarathy), Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications (DS22), SPIE Defense and Security, DSS2007, Volume 6571, Orlando, FL, April 9-13, 2007.
A. Doloc-Mihu and V. V. Raghavan, "Three-Way Aspect Model (TWAPM) and Co-Training for Mining Image Collections," in (ed. B. V. Dasarathy), Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security (DS21), SPIE Defense and Security, DSS2007, Volume 6570, Orlando, FL, April 9-13, 2007.
A. Doloc-Mihu and V. V. Raghavan, "Score Distribution Approach to Automatic Kernel Selection for Image Retrieval Systems," Proceedings of the 16th International Symposium on Methodologies for Intelligent Systems (ISMIS 2006), Springer, LNAI/LNCS, vol. 4203, Bari, Italy, September 27-29, 2006, pp. 443-452.
A. Doloc-Mihu and V. V. Raghavan, "Selecting the Kernel Type for a Web-based Adaptive Image Retrieval System (AIRS)," Internet Imaging VII, SPIE-IS&T Electronic Imaging, San Jose, CA, January 19, 2006.
M. K. Elteir, K.M. Ahmed, V. V. Raghavan and A.M. Hafez, Scalabale, Adaptive Distributed Association Rule Mining Algorithms for Skewed Datasets, in (Eds. G. Di Fatta, M. R. Berthold and S. Parthasarathy), Proceedings of the Workshop on Parallel Data Mining, in conjunction with ECML/PKDD 2006 conference, Berlin, Germany, Sept. 2006.
P. Kuntala and V. V. Raghavan, "Fusion Based Methodology for Spatial Clustering," in (Eds. C. Claramunt, S. Saltenis, and K.-J. Li), Proceedings of the Third Workshop on Spatio-Temporal Database Management, STDBM 2006, in conjunction with VLDB 2006, Seoul, Korea, Sept. 2006.
A. Dolco-Mihu and V. V. Raghavan, "Using Score Distribution Models to Select the Kernel Type for a Web- based Adaptive Image Retrieval System," in (Eds. H. Sundaram, M. Naphade, J. R. Smith, Y. Rui), Proceedings of the Image and Video Retrieval: 5th International Conf., CIVR 2006, Tempe, AZ, USA, July 13-15, 2006, pp. 443-442.
Y. Xie, M. Nagarajan, V. V. Raghavan, and H. Haddad, "On Novelty Evaluation of Potentially Useful Patterns," in (Eds. S. F. Crone, S. Lessmann & R. Stahlbock), Proceedings of the 2006 International Conf. on Data Mining, Las Vegas, NV, June 2006, pp. 211-217.
Y. Xie, T. Johnsten, V. V. Raghavan and K. Ramachandran, “On Discovering Potentially Useful Patters from Databases,” (Eds. Y.-Q. Zhang, T. Y. Lin), Proceedings of the 2006 IEEE International Conf. on Granular Computing, Atlanta, May 2006, pp. 494-497.
D. Mundluru, Z. Wu, V. Raghavan, W. Meng and H. Zhao, "Automatically Extracting Subsequent Response Pages from Web Search Sources," in (Eds. D. Caragea, V. Honavar, I. Muslea, R. Ramakrishna), Proc. 5th IEEE Workshop on Knowledge Acquisition from Distributed Autonomous, Semantically Heterogeneous Data and Knowledge Sources, Houston, TX, Nov. 2005, pp. 25-34.
E. Diaz, A. De and V. Raghavan, "A Comprehensive OWA-based Framework for Result Merging in Metasearch," in (Eds. D. Slezak, J.-T. Yao, J. F. Peters, W. Ziarko, X. Hu), Proc. 10th International Conf. on Rough Sets, Fuzzy Sets and Granular Computing (RSFDGRC 2005, Part II, Regina, Canada, Sept. 2005, pp. 193-201.
K. Ramachandran, B. Shah and V. Raghavan, "Access Pattern-Based Dynamic Pre-fetching of Views in an OLAP System," in International Conf. on Enterprise Information Systems, May 2005.
J. R. Alsabbagh and V. Raghavan: A Model for Multiple Query Processing Based upon Strong Factoring, Proceedings of the International Conf. on Information Technology: Coding and Computing (ITCC’04), Vol. 1, 2004, pp. 528-533.
H. Zhao, W. Meng, Z. Zu, V. Raghavan and C. Yu, "Fully Automatic Wrapper Generation for Search Engines," in (Eds. A. Ellis, T. Hagino, F. Douglis, P. Raghavan), Proc. 14th International World Wide Web Conf., Chiba, Japan, May 2005, pp. 66-75.
Y. Xie, D. Mundluru and V. Raghavan, "Incorporating Agent-based Neural Network Model for Adaptive Meta Search," in (Eds. V. A. Clincy, B. Harbort), Proc. 43rd ACM Southeast Conf. (ACMSE 2005), Kennesay, GA, March 2005, pp. 53-58.
A. Doloc-Mihu, V. Raghavan, S. Karnatapu and C. H. Chu, "Interface for Visualization of Image Database in Adaptive Image Retrieval Systems," in (Eds. R. Erbacher, J. Roberts, M. Groehn, K. Boerner), Proceedings of IS&T/SPIE 17th Annual Symposium on Electronic Imaging Science and Technology, Vol. 5669, Visualization and Data Analysis 2005, San Jose, CA, Jan. 2005, pp. 106.
S. Karnatapu, K. Ramachandran, Z. Wu, B. Shah, V. Raghavan and R. Benton, "Estimating Size of Search Engines in Uncooperative Environment," in International Workshop on Web-based Support Systems (WI- WSS’04), Beijing, China, Sep. 2004.
Z. Wu, D. Mundluru and V. Raghavan, "Automatically Detecting Boolean Operations Supported by Search Engines," in International Workshop on Web-based Support Systems (WI-WSS’04), Beijing, China, 2004.
R. Mehra, S. K. Gandham, Z. Wu and V. Raghavan, "Configuring Java-based Web Application Development Environment for an Academic Setting," in International Workshop on Web-based Support Systems (WI- WSS’04), Beijing, China, Sep. 2004.
E. Diaz, A. De and V. Raghavan, "On Selective Result Merging in a Metasearch," in International Workshop on Web-based Support Systems (WI-WSS’04), Beijing, China, Sep. 2004.
A. Doloc-Mihu, V. Raghavan and P. Bollmann-Sdorra, "Integration of Multiple Feature Types with Adaptive Retrieval in Vector Space Model," in ACM SIGIR Workshop on Mathematical/Formal Methods in Information Retrieval, U.K., July 2004.
B. Shah, K. Ramachandran and V. Raghavan, "Storage Estimation of Multidimensional Aggregates in a Data Warehouse Environment,” in World Multi-Conference on Systemics, Cybneretics and Informatics, Orlando, FL, July 2004.
H. Sever and V. Raghavan, "Meta Patterns: Discovering Rough Classifiers," in North American Fuzzy Information Processing Society Conf. (NAFIPS 2004), Banff, Canada, June 2004.
H. Sever, Z. Bolat and V. Raghavan, "Use of Preference Relation for Text Categorization," in (Eds. S. Tsumoto, R. Slowinski, J. Komorowski and J. W. Grzymala-Busse), Proc. of 4th International Conf. on Rough Sets and Current Trends in Computing (RSCTC 2004), Uppsala, Sweden, June 2004, pp. 708-713.
Y. Xie and V. Raghavan, "GAMInG - A Framework for Generalization of Association Mining via Information Granulation," in (Eds. S. Tsumoto, R. Slowinski, J. Komorowski and J. W. Grzymala-Busse), Proc. of 4th International Conf. on Rough Sets and Current Trends in Computing (RSCTS 2004), Uppsala, Sweden, June 2004, pp. 119-203.
J. Deogun, L. Jiang and V. Raghavan, "Discovering Maximal Potentially Useful Association Rules Based on Probability Logic," in (Eds. S. Tsumoto, R. Slowinski, J. Komorowski and J. W. Grzymala-Busse), Proc. of 4th International Conf. on Rough Sets and Current Trends in Computing (RSCTC 2004), Uppsala, Sweden, June 2004, pp. 274-284.
B. Shah, A. Gummadi, J. Yoon and V. Raghavan, "Efficient Dynamic Indexing and Retrieval of XML High Performance XML Computing, New York, NY, May 2004.
B. Shah, P. Dhatric and V. Raghavan, "Using Inverse Image Frequency for Perception-Based Color Image Quantization," in Southwest Symposium on Image Analysis and Interpretation, Lake Tahoe, NV, USA, Mar. 2004, pp. 71-75.
B. Shah, V. Raghavan and P. Dhatric, "Efficient and Effective Content-Based Image Retrieval using Space Transformation Methods," in International Conf. on Multimedia Modeling, Brisbane, Australia, Jan. 2004.
Y. Xie, T. Johnsten and V. V. Raghavan, "Knowledge Hiding in Databases for Concept-based Data Mining Algorithms,’’ in Proceedings of WISICT04 Workshop on Security Procedures’ Effects on Network Communication (SPENC), Cancun, Mexico, Jan. 2004.
T. Johnsten, R. Sweeney and V. Raghavan, A Methodology for Hiding Knowledge in XML Document Collections,’ in Proceedings of COMPSAC-2003 Workshop on Web & Security Informatics, Dallas, TX, Nov. 2003.
Z. Wu, W. Meng, V. Raghavan, C. Yu, H. He, H. Qian and R. Vuyyuru, “Towards Automatic Incorporation of Search Engines into a Large-Scale Meta-Search Engine,’ in Proc. of IEEE/WIC Web Intelligence 2003 Conference, Halifax, Canada, Oct. 2003.
B. Shah and V. Raghavan, ‘‘Space Transformation Based Approach for Effective Content-Based Image Retrieval,’’ in International Symposium on Methodologies for Intelligent Systems (ISMIS 2003), Maebashi City, Japan, Oct. 2003.
A. Gummadi, J. P. Yoon, B. Shah and V. Raghavan, ‘‘A Bitmap-Based Access Control for Restricted Views of XML Document,’’ in ACM Workshop on XML Security, Fairfax, VA, Oct. 2003.
J. Deogun, L. Jiang, Y. Xie and V. Raghavan, ‘‘Probability Logic Modeling of Knowledge Discovery in Databases,’’ in 14th International Symposium on Methodologies for Intelligent System (ISMIS 2003), Maebashi City, Japan, Oct. 2003.
R. Fanguy and V. Raghavan, "Generating Rule-based Trees from Decision Trees for Concept Based Informa- tion Retrieval," in Proc. of the First Int’l Workshop on Web-based Support Systems, held with Web Intelligence conference, 2003, Halifax, Canada, Oct. 2003.
Y. Xie and V. Raghavan, ‘‘A Theoretical Framework for Knowledge Discovery in Databases Based on Probabilistic Logic,’’ in Proceedings of RSFDGrC’2003 (9th International Conf. on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing), Chongqing, China, Oct. 2003.
A. Doloc-Mihu, V. Raghavan and P. Bollmann-Sdorra, ‘‘Color Retrieval in Vector Space Model,’’ in ACM SIGIR Workshop on Mathematical/Formal Methods in Information Retrieval, Toronto, Canada, Aug. 2003.
Y. Chang, I. Choi, J. Choi, M. Kim, and V. V. Raghavan, ‘‘Conceptual Retrieval Based on Feature Clustering of Documents,’’ in Proceedings of ACM SIGIR Workshop on Mathematical/Formal Methods in Information Retrieval, Tampere, Finland, Aug. 2002.
T. D. Johnsten and V. V. Raghavan, ‘‘Knowledge Hiding in Databases and its Relationship to KDD,’’ in Proc. of 6th World Multiconference on Systemics, Cybernetics, and Informatics (SCI 2002), Orlando, FL, July 2002.
T. D. Johnsten, V. V. Raghavan, and K. Hill, ‘‘The Security Assessment of Association Mining Algorithms,’’ in Proc. of Sixteenth IFIP WG 11.3 Working Conf. on Data and Applications Security, Cambridge, England, July 2002.
T. Johnsten and V. V. Raghavan, ‘‘A Methodology for Hiding Knowledge in Databases," in Proc. of the ICDM02 Workshop on Privacy, Security and Data Mining, Maebashi, Japan, Dec. 2002, pp. 9-18.
S. Noel, C. H. Chu, and V. V. Raghavan, ‘‘Visualization of Document Cocitation Counts,’’ in Proceedings of 6th International Conf. on Information Visualization, London, England, July 2002, pp. 691-696.
B. N. Shah and V. V. Raghavan, ‘‘An Approach to Content-based Image Retrieval using Clustering and Space Information,’’ in Proceedings of Workshop on Multimedia InformationRetrieval-MIR02, Juan les Pins, France, Dec. 2002.
Y. Xie and V. V. Raghavan, ‘‘Probabilistic Logic-based Characterization of Knowledge Discovery in Databases,’’ in Proceedings of ICDM’02 Workshop on Foundation of Data Mining and Knowledge Dis- covery, Maebashi, Japan, Dec. 2002, pp. 107-112.
Y. Xie, V. V. Raghavan, and X. Zhao, ‘‘3M Algorithm: Finding an Optimal Fuzzy Cluster Scheme for Proximity Data,’’ in Proceedings of the FUZZ-IEEE Conf.-2002 IEEE World Congress on Computational Intelligence, Honolulu, HI, May 2002.
W. Badawy and V. V. Raghavan, Interfacing the “Abridged Bayou State Periodical Index with a Search Engine: A Dublin Core Approach”, in Proceedings of 7th International Conf. on Object-Oriented Information Systems (OOIS’01), Calgary, Alberta, Canada, Aug. 2001.
P. Bollmann-Sdorra, A. Hafez, and V. V. Raghavan, ‘‘A Theoretical Framework for Association Mining Based on the Boolean Retrieval Model,’’ in Y. Kambayashi, W. Winiwarter, and M. Arikawa, editors, Data Warehousing and Knowledge Discovery: Third International Conf., DaWAK’01), Munich, Germany, Sept. 2001, pp. 21-30.
J. Choi, M. Kim, and V. V. Raghavan, ‘‘Adaptive Feedback Methods in an Extended Boolean Model,’’ in Proceedings of ACM SIGIR Workshop on Mathematical/Formal Methods in Information Retrieval, New Orleans, LA, Sept. 2001.
A. Hafez and V. V. Raghavan, ‘‘A Matrix Approach for Association Mining,’’ in Proceedings of the ISCA 10th International Conf., Arlington VA, June 2001, pp. 104-108.
T. D. Johnsten and V. V. Raghavan, ‘‘Security Procedures for Classification Mining Algorithms,’’ Proc. of Fifteenth IFIP WG 11.3 Working Conf. on Database Security, Niagra on the Lake, Ontario, Canada, July 2001, pp. 293-309.
S. Noel, V. V. Raghavan, and C. H. Chu, ‘‘Visualizing Association Mining Results through Hierarchical Clusters,’’ in Proceedings of the 2001 International Conf. on Data Mining (ICDM-01), San Jose, CA, Nov. - Dec. 2001, pp. 425-432.
J. Yoon, V. V. Raghavan, and V. Chakilam, ‘‘Bitcube: A Three-Dimensional Bitmap Indexing for XML Documents,’’ in Proc. of 13th International Conf. on Scientific and Statistical Database Management, Fairfax, VA, July 2001, pp. 158-167.
J. Yoon, V. V. Raghavan, and V. Chakilam, ‘‘BitmapIndexing Based Clustering and Retrieval of XML Documents,’’ in Proceedings of ACM SIGIR Workshop on Mathematical/Formal Methods in Information Retrieval, New Orleans, LA, Sept. 2001.
M. Kim, A. H. Alsaffar, J. S. Deogun, and V. V. Raghavan, "On Modeling of Concept Based Retrieval in Gen- eralized Vector Spaces," in Proceedings of ISMIS 2000, Charlotte, NC, Oct. 2000, pp. 453-462.
J. P. Yoon, A. Hafez, and V. V. Raghavan, "Query Rewriting for Multimedia XML Data," in Proceedings of the 6th International Workshop on Multimedia Information Systems (MIS’00), Chicago, IL, Oct. 2000, pp. 62-71.
M. Kim, F. Lu, and V. V. Raghavan, "Automatic Construction of Rule-based Trees for Conceptual Retrieval," in Proceedings of the 7th International Symposium on String Processing and Information Retrieval (SPIRE-2000), A Coruna, Spain, Sept. 2000, pp.151-161.
M. Kim and V. V. Raghavan, "Adaptive Concept-based Retrieval using Neural Model," in Proceedings of ACM SIGIR Workshop on Mathematical/Formal Methods in Information Retrieval, Athens, Greece, July 2000. Published in a special issue of Technology Letters: Vol. 4, No. 1, pp. 33-40.
P. Bollmann-Sdorra, T. H. Graepel, R. Herbrich, and V. V. Raghavan, "Why the Vector Space Model Works?", in Proceedings of ACM SIGIR Workshop on Mathematical/Formal Methods in Information Retrieval, Athens, Greece, July 2000. Abstract published in a special issue of Technology Letters: Vol. 4, No. 1, pp. 7.
K. Efe, V. V. Raghavan, C. H. Chu, A. L. Broadwater, L. Bolelli, and S. Ertekin, "The Shape of the Web and its Applications for Searching the Web," in International Conf. on Advances in Infrastructure for Electronic Business, Science, and Education on the Internet, on the Internet, Rome, Italy, Jul.-Aug. 2000.
V. V. Raghavan and A. Hafez, ‘‘Dynamic Data Mining," Proc. of IEA/AIE ‘00 Thirteenth International Conf. on Industrial Engineering Applications of AI & Expert Systems, June 2000, New Orleans, LA, pp. 220-229 (Best Paper Award).
J. P. Yoon and V. V. Raghavan, "Multi-level Scheme Extraction for Heterogeneous Semi-structured Data," in First International Conf. on Web-Age Information Management, Shanghai, PRC, June 2000, pp. 411-422.
P. Bollmann-Sdorra, V. V. Raghavan and H. Sever, ‘‘Term preference weight," Proc. of ISCIS ‘99- Fourteenth International Symposium on Computer and Information Sciences, Oct. 1999, Izmir, Turkey, pp. 360--369.
T. D. Johnsten and V. V. Raghavan, ‘‘Impact of decision-region based classification mining algorithms on database security," Proc. of Thirteenth IFIP WG 11.3 Working Conf. on Database Security, Jul. 1999, Seattle, WA.
A. Hafez, J. S. Deogun and V. V. Raghavan, ‘‘The item-set tree: A data structure for data mining," In Mukesh Mohania and A Min Tjoa (eds.), Data Warehousing and Knowledge Discovery: First International Conf. (DaWaK’99), Aug. 1999, Springer, Florence, Italy, pp. 183--192.
F. Lu, T. D. Johnsten, V. V. Raghavan and D. Traylor, ‘‘Enhancing internet search engines to achieve concept- based retrieval," InForum’99- Improving the Visibility of R & D Information, May 1999, Oak Ridge, TN.
A. H. Alsaffar, J. S. Deogun, V. V. Raghavan and H. Sever. "Concept-based retrieval with minimal term sets," In Z. W. Ras and A. Skowron (eds.), Foundations of Intelligent Systems: Eleventh Int’l Symposium, ISMIS’99 proceedings, June 99, Springer, Warsaw, Poland, pp. 114-122.
J. S. Deogun and V. V. Raghavan and H. Sever, ‘‘Association Mining and Formal Concept Analysis,’’ JCIS Proceedings 98: RSDMGrC98- Sixth International Workshop on Rough Sets, Data Mining and Granular Computing, Vol. II, Oct. 1998, Research Triangle Park, NC, pp. 335-338.
J. S. Deogun and H. Sever and V. V. Raghavan, ‘‘Structural Abstractions of Hypertext Documents for Web- based Retrieval,’’ Proc. of DEXA 98 - 9th International Workshop on Database and Expert Systems Applications, Aug. 1998, Vienna, AT, pp. 385-390.
M. C. Erie and S. M. LeBlanc and V. V. Raghavan, ‘‘Enhancing Search Capabilities of Legacy Internet Resources,’’ InForum 98- Science at the Desktop: Synergy through Sharing, May 1998, Oak Ridge, TN.
H. Sever and V. V. Raghavan and T. D. Johnsten, ‘‘The Status of Research on Rough Sets for Knowledge Discovery in Databases,’’ Proc. of ICNPAA98- Second Int’l Conf. On Nonlinear Problems in Aviation and Aerospace, Apr. - May 1998, Daytona Beach, FL, Volume 2, pp. 673-680.
S. K. Choubey and V. V. Raghavan, ‘‘Generic and Fully Automatic Content Based Image Retrieval Architecture,’’ Proc. of the 10th International Symposium on Methodologies for Intelligent Systems, Oct. 1997, Charlotte, NC, pp. 360-369.
S. K. Choubey and V. V. Raghavan, ‘‘Generic and Fully Automatic Content Based Image Retrieval using Color,'' International Conf. on Imaging Science, Systems, and Technology, June- July, 1997, Las Vegas, NV, pp. 228-237.
S. K. Choubey and V. V. Raghavan, ‘‘Generic and Fully Automatic Content-based Image Retrieval Using Color,’’ Pattern Recognition in Practice- V, June. 1997, Vlieland, The Netherlands.
H. Sever,V. V. Raghavan, J. S. Deogun and S. K. Choubey ‘‘A Comparison of Classification Methods,’’ International Conf. of Information Sciences- Rough Set & Computer Science, Mar. 1997, Raleigh, NC, Vol. 3, pp. 371-374.
S. K. Choubey, J. S. Deogun, V. V. Raghavan and H. Sever, ‘‘A comparison of feature selection algorithms in the context of rough classifiers,’’ Fuzz- IEEE ’96 International Conf. on Fuzzy Systems, Sept. 1996, New Orleans, LA, Vol. 2, pp. 1122-1128.
J. S. Deogun, V. V. Raghavan and H. Sever, ‘‘Exploiting upper approximations in the rough set methodology,’’Proc. of the the First International Conf. on Knowledge Discovery and Data Mining, Aug. 1995, Montreal, CDN, pp. 69-74.
V. V. Raghavan and H. Sever, ‘‘On the reuse of past optimal queries,’’Proc. of the ACM SIGIR’95, Jul. 1995, Seattle, WA, pp. 344-350.
V. V. Raghavan and H. Sever, ‘‘The state of rough sets for database mining applications,’’Proc. of the 23rd Computer Science Conf. Workshop on Rough Sets and Database Mining, Mar. 1995, Nashville, TN, pp. 1-11.
K. Vanapipat, N. Pissinou and V. V. Raghavan, ‘‘A Dynamic Framework to Actively Support Interoperability in Multidatabase Systems,’’Proc. of the Fifth International Workshop on Research Issues on Data Engineer- ing: Distributed Object Management (RIDE- DOM), March 1995, Taipei, Taiwan, pp. 148-153.
J. S. Deogun, V. V. Raghavan and H. Sever, ‘‘Rough Set Based Classification Methods and Extended Decision Tables,’’Proc. of the Third International Workshop on Rough Sets and Soft Computing, Nov. 1994, San Jose, CA, pp. 302-309.
V. N. Gudivada and V. V. Raghavan, ‘‘A System for Retrieving Images by Content,’’ Proc. of RIAO-94: Conf. on Intelligent Multimedia, Information Retrieval, Systems and Management, Vol. 1, Oct. 1994, New York, NY, pp. 418-436.
S. K. Mishra and V. V. Raghavan, ‘‘Design Issues in Randomized Branch and Bound Algorithms: A Study of Graph Partitioning,’’ Proc. of the IFIP World Congress ’94, Sept. 1994, Hamburg, FRG, pp. 276-281.
S. K. Mishra and V. V. Raghavan, ‘‘An Empirical Study of the Performance of Heuristic Methods for Cluster- ing,’’ in E.S. Gelsema and L.N. Kanal (Eds.), Proc. of Pattern Recognition in Practice IV: Multiple Paradigms, Comparative Studies and Hybrid Systems, Elsevier Science B.V., June 1994, Vlieland, NL, pp. 425-436.
V. N. Gudivada, V. V. Raghavan and G. S. Seetharaman, ‘‘An Approach to Interactive Retrieval in Face Image Databases based on Semantic Attributes,’’ Proc. of the Third Annual Symposium on Document Analysis and Information Retrieval, April 1994, Las Vegas, NV, pp. 319-335.
J. R. Alsabbagh and V. V. Raghavan, ‘‘Analysis of Common Subexpression Exploitation Models in Multiple Query Processing,’’ Proc. of the 10th International Conf. on Data Engineering, Feb. 1994, Houston, TX, pp. 488-497.
V. V. Raghavan, H. Sever and J.S. Deogun, ‘‘A System Architecture for Database Mining Applications,’’ International Workshop on Rough Sets and Knowledge Discovery (RSKD ’93), October 1993, Banff, Canada, pp. 73-77. An extended version published in W. Ziarko (Ed.), Rough Sets, Fuzzy Sets and Knowledge Discovery, Workshops in Computing Series, Springer Verlag,1994, pp.82-89.
V. N. Gudivada and V. V. Raghavan, “Spatial Similarity Based Retrieval in Image Databases,” Proc. of the Second Annual Symposium on Document Analysis and Information Retrieval, April 1993, Las Vegas, NV, pp. 255-270.
J. N. Bhuyan, J. S. Deogun and V. V. Raghavan, ‘‘A Retrieval Scheme for Cluster-based Adaptive Information Retrieval Based on Term Refinement,’’ Proc. of the SPIE- Applications of Artificial Intelligence 1993: Knowledge-Based Systems in Aerospace and Industry, Vol. 1963, April 1993, Orlando, FL, pp. 303-315.
J. R. Alsabbagh and V. V. Raghavan, ‘‘A Framework for Multiple-Query Optimization,’’ Proc. of the Second International Workshop on Research Issues on Data Engineering: Transaction and Query Processing (RIDE-TQP), Feb. 1992, Phoenix, AZ, pp. 157-162.
S. K. Bhatia, J. S. Deogun and V. V. Raghavan, ‘‘User Profiles for Information Retrieval,’’ Proc. of the Sixth International Symposium on Methodologies for Intelligent Systems, Lecture Notes in A.I., #152, Springer- Verlag, October 1991, Charlotte, NC, pp. 102-111.
Y. Zhang, V. V. Raghavan and J. S. Deogun, ‘‘An Object-Oriented Modeling of the History of Optimal Retrievals,’’ Proc. of the Fourteenth International ACM-SIGIR Conf. on Research and Development in Information Retrieval, October 1991, Chicago, IL, pp. 241-250.
P. Bollmann and V. V. Raghavan, ‘‘The Axiomatic Approach for Theory Development in IR,‘‘ Working Notes of NSF Workshop on Future Directions in Text Analysis, Retrieval and Understanding, October 1991, Chicago IL, pp. 16-22 (INVITED PAPER).
J. N. Bhuyan, V. V. Raghavan and V. K. Elayavalli, ‘‘Genetic Algorithm for Clustering with an Ordered Representation,’’ Proc. of the Fourth International Conf. on Genetic Algorithms, Morgan Kaufmann Publishers, July 1991, San Diego, CA, pp. 408-415.
S. K. Bhatia, J. S. Deogun and V. V. Raghavan, ‘‘Query Formulation through Knowledge Acquisition,’’ Proc. of ML 91--The Eighth International Workshop on Machine Learning: Intelligent Information Retrieval track, Morgan Kaufmann Publishers, June 1991, Evanston, IL, pp. 250-254.
J. N. Bhuyan and V. V. Raghavan, ‘‘A Probabilistic Retrieval Scheme for Cluster-based Adaptive Information Retrieval,’’ Proc. of ML 91--The Eighth International Workshop on Machine Learning: Intelligent Information Retrieval Track, Morgan Kaufmann Publishers, June 1991, Evanston, IL, pp. 240-244.
J. S. Deogun and V. V. Raghavan, ‘‘Description of the UNL/USL System used for MUC-3,’’ Proc. of DARPA’s Third Message Understanding Conf. (MUC-3), Morgan Kaufmann Publishers, May 1991, San Diego, CA, pp. 234-242.
J. S. Deogun and V. V. Raghavan, ‘‘UNL/USL: MUC-3 Test Results and Analysis,’’ Proc. of DARPA’s Third Message Understanding Conf. (MUC-3), Morgan Kaufmann Publishers, May 1991, San Diego, CA, pp. 120-125.
J. S. Deogun, S. K. Bhatia and V. V. Raghavan, ‘‘Automatic Identification of Message Destinations,’’ FloridaAI Research Symposium, April 1991, Cocoa Beach, FL, pp. 140-144.
J. S. Deogun, S. K. Bhatia and V. V. Raghavan, ‘‘Document Classification Using ID-3,’’ Proc. of the 24th Simulation MultiConference on AI and Simulation: Simulation Series, Vol. 23, No. 4, April 1991, New Orleans, LA, pp. 133-138.
V. V. Raghavan, V. N. Gudivada and A. S. Katiyar, ‘‘Discovery of Conceptual Categories in an Image Database,’’ Proc. of RIAO-91: Conf. on Intelligent Text and Image Handling, April 1991, Barcelona, Spain, pp. 902-915.
J. S. Deogun, S. K. Bhatia and V. V. Raghavan, ‘‘Automatic Cluster Assignment for Documents,’’ Proc. of the 7th IEEE Conf. on Artificial Intelligence Applications, February 1991, Miami Beach, FL, pp. 25-28.
J. N. Bhuyan, V. V. Raghavan and J. S. Deogun, ‘‘Cluster-Based Adaptive Information Retrieval,’’ Proc. of the Twenty-fourth Hawaii Int’l Conf. on Systems Sciences- Architecture and emerging Technologies Tracks, Vol. I, January 1991, Kailua-Kona, Hawaii, pp. 307-316.
V. V. Raghavan and V. N. Gudivada, ‘‘A Domain Independent Similarity Measure for Symbolic Images,’’ Proc. of the 1990 Indian Computing Conf., November 1990, Hyderabad, India, pp. 195-203.
S. K. Bhatia, J. S. Deogun and V. V. Raghavan, ‘‘Automatic Rule-Base Generation for User-oriented Information Retrieval,’’ Proc. of the Fifth International Symposium on Methodologies for Intelligent Systems, Oct. 1990, Knoxville, TN, pp. 119-125.
S. K. Bhatia, J. S. Deogun and V. V. Raghavan, ‘‘Assignment of Term Descriptors to Clusters,’’ Proc. of the 1990 Symposium on Applied Computing, April 1990, Fayetteville, AR, pp. 181-185.
G. S. Jung and V. V. Raghavan, ‘‘Connectionist Learning in Constructing Thesauruslike Knowledge Structure,’’ Working Notes of AAAI Symposium on Text-Based Intelligent Systems, March 1990, Palo Alto, CA, pp. 123-127.
V. V. Raghavan and G. S. Jung, ‘‘A Machine Learning Approach to Automatic Pseudothesaurus Construction,’’ Proc. of the Fourth International Symposium on Methodologies for Intelligent Systems: Poster Session Program, Oak Ridge National Lab., October 1989, Charlotte, NC, pp. 111-121.
J. S. Deogun, V. V. Raghavan, and S. K. Bhatia, ‘‘A Theoretical Basis for the Automatic Extraction of Relation- ships from Expert-provided Data,’’ Proc. of the Fourth International Symposium on Methodologies for Intelligent Systems: Poster Session Program, Oak Ridge National Lab., October 1989, Charlotte, NC, pp. 123-131.
J. N. Bhuyan, J. S. Deogun, and V. V. Raghavan, ‘‘Near-optimal Algorithms for the Boundary Selection Problem in User-oriented Information Retrieval’’, Proc. of the Eleventh World Computer Congress, North- Holland, August 1989, San Francisco, CA, pp. 275-280.
V. V. Raghavan, P. Bollmann and G. S. Jung, ‘‘Retrieval System Evaluation Using Recall and Precision: Problems and Answers,’’ Proc. of the Twelfth International ACM-SIGIR Conf. on Research and Development in Information Retrieval, Association for Computing Machinery Press, June 1989, Cambridge, MA, pp. 59-68.
J. S. Deogun, V. V. Raghavan and P. Rhee, ‘‘Formulation of the Term Refinement Problem for User-oriented Information Retrieval,’’ Proc. of the Fourth AI Systems in Government Conf., March 1989, Washington, DC, pp. 72-78.
P. Bollmann and V. V. Raghavan, ‘‘A Utility-theoretic Analysis of Expected Search Length,’’ Proc. of the 11th International ACM-SIGIR Conf., June 13-15, 1988, Grenoble, France, pp. 245-256.
R. Kosireddy, M. A. Bayoumi and V. V. Raghavan, ‘‘A VLSI Parallel Architecture for Pattern Classification," ACM South Central Regional Conf., Nov. 1987, Lafayette, LA, pp. 189-199.
V. V. Raghavan, ‘‘Deterministic Strategies for Query (Re)formulation in Information Retrieval," First International Conf. on Bibliometrics and Theoretical Aspects of Information Retrieval,” Aug. 1987, Diepenbeek, Belgium, published in L. Egghe and R. Rousseau (Eds.) Informetrics 87/88, Elsevier Science Publishers B.V., Amsterdam, 1988, pp. 219-229.
V. V. Raghavan and B. Agarwal, ‘‘Optimal Determination of User-oriented clusters: An Application for the Reproductive Plan," Proc. of the Second International Conf. on Genetic Algorithms, July 1987, Cambridge, MA., pp. 241-246.
V. V. Raghavan and J. S. Deogun, ‘‘Optimal Determination of User-oriented Clusters," Proc. of the Tenth ACM- SIGIR International Conf., June 3-5, 1987, New Orleans, LA, pp. 140-146.
V. V. Raghavan and L. V. Saxton, ‘‘Conceptual Design for an Integrated Information Retrieval/Database Man- agement System," G.I. Conf. on Database Systems for Offi ce Automation, Engineering and Scientifi c Applications, March-April 87, Darmstadt, FRG., published in H. -J. Schek and G. Schlageter (Eds.) Datenbanksysteme in Buro, Technik und Wissenschaft, Springer-Verlag, Berlin, FRG, 1987, pp. 443-447.
V. V. Raghavan, L. V. Saxton, S. K. M. Wong and S. S. Ting, ‘‘A Unified Architecture for the Integration of Data Base Management and Information Retrieval Systems,’’ Proc. of the IFIP 10th World Computer Congress, North-Holland, Sept. 1986, Dublin, Ireland, pp. 1049-1054.
J. S. Deogun and V. V. Raghavan, ‘‘User-oriented Document Clustering - A Framework for Learning in IR, ’’ Proc. of Ninth International ACM-SIGIR Conf., Sept. 1986, Pisa, Italy, pp. 157-163.
S. K. M. Wong, W. Ziarko, V. V. Raghavan and P. C. N. Wong, ‘‘On Extending the Vector Space Model for Boolean Query Processing,’’ Proc. of Ninth Annual International ACM-SIGIR Conf., Sept. 1986, Pisa, Italy, pp. 175-185.
V. V. Raghavan, ‘‘Clustering Algorithms for Information Retrieval - An AI Perspective,’’ Proc. of the 19th Hawaii International Conf. on System Sciences, Jan. 1986, Honolulu, HI, pp. 142-151.
K. Vidyasankar and V. V. Raghavan, ‘‘Highly Flexible Integration of the Locking and the Optimistic Approaches of Concurrency Control,’’ Proc. of the IEEE 9th International Compsac Conf., Oct. 1985, Chicago, IL, pp. 489-494.
J. S. Deogun and V. V. Raghavan, ‘‘Integration of Information Retrieval and Data Base Management Systems,’’ Proc. of the RIAO-85 (Recherche d’Informations Assistee par Ordinateur) Conf., March 1985, Grenoble, France, pp. 627-644.
J. S. Deogun and V. V. Raghavan, ‘‘A Generalized Retrieval System: Formulation and its Implications for the Sciences, Symposium on Automatic Information Retrieval in the Sciences (organizer: Dr. M. J. McGill, Symposium II, Ninth International CODATA Conf., June 1984, Jerusalem, Israel, published in The Role of Data in Scientific Progress, P. S. Glaser (ed.) Elsevier Science Publishers B. V. (North Holland), 1985, pp. 513-516 (INVITED PAPER).
S. K. M. Wong and V. V. Raghavan, ‘‘Vector Space Model of Information Retrieval- A Reevaluation,’’ in (ed.) C. J. van Rijsbergen: Research and Development in Information Retrieval, Proc. of the 3rd Joint BCS and ACM Symposium, July 1984, King’s College, Cambridge, England, pp. 167-186.
V. V. Raghavan, K. Vidyasankar and Jing Xinhai,‘‘Distributed Calendar System with High Availability,’’ Proc. of the 17th Hawaii International Conf. on System Sciences, Jan. 1984, Honolulu, HI, pp. 639-645.
K. W. Tsou, L. V. Saxton, V. V. Raghavan and J. S. Deogun, ‘‘Consecutive Retrieval with Redundancy Organization of Clustered Files,’’ in R. E. A. Mason (ed.) Information Processing 83, North-Holland, Amsterdam. Proc. of the IFIP 9th World Co mputer Congress, Sept. 1983, Paris, France, pp. 533-537.
V. V. Raghavan, H. Shi and C. T. Yu, ‘‘Evaluation of the 2-Poisson Model as a Basis for Using Term Frequency Data in Searching,’ Proc. of Sixth International ACM-SIGIR Conf., June 1983, Washington, DC, pp. 88-100.
V. V. Raghavan and M. Y. L. Ip, ‘‘Techniques for Measuring the Stability of Clustering: A Comparative Study,’’ in G. Salton and H.-J. Schneider (ed.) Research and Development in Information Retrieval Proc., Berlin, May 1982. Published as Lecture Notes in Computer Science Series, Springer-Verlag, Berlin, FRG, 1983, pp. 209-237.
J. S. Deogun and V. V. Raghavan, ‘‘Query Directed Partitioning Scheme for Securing Statistical Databases,” Proc. of the Workshop on Statistical Database Management, Dec. 1981, Menlo Park, CA, pp. 285-293.
M. Y. L. Ip, V. V. Raghavan and L. V. Saxton, ‘‘An Approximation Algorithm for the Index Selection Problem,’’ Proc. of the IEEE 5th International COMPSAC Conf., Nov. 1981, Chicago, IL, pp. 43-49.
V. V. Raghavan and J. S. Deogun, ‘‘Information Retrieval: Research Strategies and their Implications,’’ Proc. of the Canadian Information Processing Society Conf., June 1981, Waterloo, CDN, pp.9.4.1-9.4.9.
V. V. Raghavan and K. Birchard, ‘‘A Clustering Strategy Based on a Formalism of the Reproductive Process in Natural Systems,’’ Proc. of the Second International ACM-SIGIR Conf., Sept. 1979, Dallas, TX, pp. 10-22.
Demo and Industrial Track Papers
Ying Xie, Jing (Selena) He, Vijay V. Raghavan: “MapReduce Algorithms for Identifying Minimum-Sized Influential Vertices on Large-Scale Weighted Graphs.” 2nd International IBM Cloud Academy Conference program (ICA CON 2014), Poster Session, Atlanta, GA, USA, May 2014, pp. 57.
Y. Lu, Z. Wu, H. Zhao, W. Meng, K.-L. Liu, V. V. Raghavan and C. Yu. "MySearchView: A Customized Meta-search Engine Generator," 26th ACM SIGMOD International Conf. on Management of Data (ACM SIGMOD 2007), Demo paper, Beijing, China, June 2007, pp. 1113-1115.
K.-L. Liu, W. Meng, J. Qiu, C. Yu, V. V. Raghavan, Z. Wu, Y. Lu, H. He and H. Zhao. "AllInOneNews: Devel- opment and Evaluation of a Large-Scale News Meta-search Engine," 26th ACM SIGMOD International Conf. on Management of Data (ACM SIGMOD 2007), Industrial track, Beijing, China, June 2007, pp. 1017-1028.
Z. Wu, V. V. Raghavan, W. Meng, C. Yu, D. Chun, H. He and K. Sai, ‘‘SE-LEGO: A System to Create Meta- Search Engines on Demand,’’ in Proc. of 26th ACM SIGIR Conf., Demo paper, Toronto, CDN, Jul. 2003, pp. 464.
Z. Wu, V. V. Raghavan, C. Du, W. Meng, H. He and C. Yu, ‘‘Creating Customized Meta-Search Engines on Demand Using SE-LEGO,’’ in Proc. of Fourth International Conf. on Web-Age Information Management (WAIM’03), Demo Paper, Chengdu, China, Aug. 2003, pp. 503-505.