| Fuzzy association rule mining algorithm for fast and efficient performance on very large datasets A Mangalampalli, V Pudi 2009 IEEE International Conference on Fuzzy Systems, 1163-1168, 2009 | 92 | 2009 |
| Advances in knowledge discovery and data mining JPVS Tseng, LCH Motoda, G Xu Lecture Notes in Artificial Intelligence), vol. LNAI 8444, 2003 | 77* | 2003 |
| Frequent itemset based hierarchical document clustering using wikipedia as external knowledge GVR Kiran, R Shankar, V Pudi International Conference on Knowledge-based and Intelligent Information and …, 2010 | 39 | 2010 |
| Paper2vec: Combining graph and text information for scientific paper representation S Ganguly, V Pudi European Conference on Information Retrieval, 383-395, 2017 | 34 | 2017 |
| Class based weighted k-nearest neighbor over imbalance dataset H Dubey, V Pudi Pacific-Asia Conference on Knowledge Discovery and Data Mining, 305-316, 2013 | 34 | 2013 |
| Quantifying the utility of the past in mining large databases V Pudi, JR Haritsa Information Systems 25 (5), 323-343, 2000 | 33 | 2000 |
| Disc: Data-intensive similarity measure for categorical data A Desai, H Singh, V Pudi Pacific-Asia Conference on Knowledge Discovery and Data Mining, 469-481, 2011 | 32 | 2011 |
| Advances in knowledge discovery and data mining G Xu Berlin: Springer-Verlag, 2004 | 31* | 2004 |
| ARMOR: Association Rule Mining based on ORacle. V Pudi, JR Haritsa FIMI, 2003 | 31 | 2003 |
| An efficient algorithm for ranking research papers based on citation network AP Singh, K Shubhankar, V Pudi 2011 3rd Conference on data mining and optimization (DMO), 88-95, 2011 | 29 | 2011 |
| FPrep: Fuzzy clustering driven efficient automated pre-processing for fuzzy association rule mining A Mangalampalli, V Pudi International Conference on Fuzzy Systems, 1-8, 2010 | 26 | 2010 |
| Autolearn—Automated feature generation and selection A Kaul, S Maheshwary, V Pudi 2017 IEEE International Conference on data mining (ICDM), 217-226, 2017 | 24 | 2017 |
| An efficient algorithm for topic ranking and modeling topic evolution K Shubhankar, AP Singh, V Pudi International Conference on Database and Expert Systems Applications, 320-330, 2011 | 24 | 2011 |
| ACME: An associative classifier based on maximum entropy principle R Thonangi, V Pudi International Conference on Algorithmic Learning Theory, 122-134, 2005 | 24 | 2005 |
| Author2vec: Learning author representations by combining content and link information S Ganguly, M Gupta, V Varma, V Pudi Proceedings of the 25th International Conference Companion on World Wide Web …, 2016 | 23 | 2016 |
| Generalized closed itemsets for association rule mining V Pudi, JR Haritsa Proceedings 19th International Conference on Data Engineering (Cat. No …, 2003 | 22 | 2003 |
| Using prefix-trees for efficiently computing set joins R Jampani, V Pudi International Conference on Database Systems for Advanced Applications, 761-772, 2005 | 21 | 2005 |
| Predicting the Outcome of ODI Cricket Matches: A Team Composition Based Approach. MG Jhanwar, V Pudi MLSA@ PKDD/ECML, 2016 | 19 | 2016 |
| A frequent keyword-set based algorithm for topic modeling and clustering of research papers K Shubankar, AP Singh, V Pudi 2011 3rd Conference on Data Mining and Optimization (DMO), 96-102, 2011 | 19 | 2011 |
| A feature-pair-based associative classification approach to look-alike modeling for conversion-oriented user-targeting in tail campaigns A Mangalampalli, A Ratnaparkhi, AO Hatch, A Bagherjeiran, R Parekh, ... Proceedings of the 20th international conference companion on World wide web …, 2011 | 19 | 2011 |
Ashish MangalampalliMicrosoftVerified email at microsoft.com
