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Philip K. Chan: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Philip K. Chan, Salvatore J. Stolfo
    Experiments on Multi-Strategy Learning by Meta-Learning. [Citation Graph (3, 0)][DBLP]
    CIKM, 1993, pp:314-323 [Conf]
  2. Christopher J. Matheus, Philip K. Chan, Gregory Piatetsky-Shapiro
    Systems for Knowledge Discovery in Databases. [Citation Graph (3, 13)][DBLP]
    IEEE Trans. Knowl. Data Eng., 1993, v:5, n:6, pp:903-913 [Journal]
  3. Philip K. Chan, Salvatore J. Stolfo
    On the Accuracy of Meta-Learning for Scalable Data Mining. [Citation Graph (2, 0)][DBLP]
    J. Intell. Inf. Syst., 1997, v:8, n:1, pp:5-28 [Journal]
  4. Philip K. Chan, Salvatore J. Stolfo
    Learning Arbiter and Combiner Trees from Partitioned Data for Scaling Machine Learning. [Citation Graph (1, 0)][DBLP]
    KDD, 1995, pp:39-44 [Conf]
  5. Philip K. Chan, Salvatore J. Stolfo
    Sharing Learned Models among Remote Database Partitions by Local Meta-Learning. [Citation Graph (1, 0)][DBLP]
    KDD, 1996, pp:2-7 [Conf]
  6. Philip K. Chan, Salvatore J. Stolfo
    Toward Scalable Learning with Non-Uniform Class and Cost Distributions: A Case Study in Credit Card Fraud Detection. [Citation Graph (1, 0)][DBLP]
    KDD, 1998, pp:164-168 [Conf]
  7. Salvatore J. Stolfo, Andreas L. Prodromidis, Shelley Tselepis, Wenke Lee, Dave W. Fan, Philip K. Chan
    JAM: Java Agents for Meta-Learning over Distributed Databases. [Citation Graph (1, 0)][DBLP]
    KDD, 1997, pp:74-81 [Conf]
  8. Gaurav Tandon, Philip K. Chan
    Learning Useful System Call Attributes for Anomaly Detection. [Citation Graph (0, 0)][DBLP]
    FLAIRS Conference, 2005, pp:405-411 [Conf]
  9. Philip K. Chan, Matthew V. Mahoney
    Modeling Multiple Time Series for Anomaly Detection. [Citation Graph (0, 0)][DBLP]
    ICDM, 2005, pp:90-97 [Conf]
  10. Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan
    Using Artificial Anomalies to Detect Unknown and Known Network Intrusions. [Citation Graph (0, 0)][DBLP]
    ICDM, 2001, pp:123-130 [Conf]
  11. Matthew V. Mahoney, Philip K. Chan
    Learning Rules for Anomaly Detection of Hostile Network Traffic. [Citation Graph (0, 0)][DBLP]
    ICDM, 2003, pp:601-604 [Conf]
  12. Philip K. Chan
    Inductive Learning with BCT. [Citation Graph (0, 0)][DBLP]
    ML, 1989, pp:104-108 [Conf]
  13. Philip K. Chan, Salvatore J. Stolfo
    A Comparative Evaluation of Voting and Meta-learning on Partitioned Data. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:90-98 [Conf]
  14. Wei Fan, Salvatore J. Stolfo, Junxin Zhang, Philip K. Chan
    AdaCost: Misclassification Cost-Sensitive Boosting. [Citation Graph (0, 0)][DBLP]
    ICML, 1999, pp:97-105 [Conf]
  15. Hyoung-rae Kim, Philip K. Chan
    Identifying Variable-Length Meaningful Phrases with Correlation Functions. [Citation Graph (0, 0)][DBLP]
    ICTAI, 2004, pp:30-38 [Conf]
  16. Gaurav Tandon, Debasis Mitra, Philip K. Chan
    Motif-Oriented Representation of Sequences for a Host-Based Intrusion Detection System. [Citation Graph (0, 0)][DBLP]
    IEA/AIE, 2004, pp:605-615 [Conf]
  17. Philip K. Chan, Salvatore J. Stolfo
    Toward Multi-Strategy Parallel & Distributed Learning in Sequence Analysis. [Citation Graph (0, 0)][DBLP]
    ISMB, 1993, pp:65-73 [Conf]
  18. Hyoung R. Kim, Philip K. Chan
    Learning implicit user interest hierarchy for context in personalization. [Citation Graph (0, 0)][DBLP]
    Intelligent User Interfaces, 2003, pp:101-108 [Conf]
  19. Philip K. Chan
    Constructing Web User Profiles: A non-invasive Learning Approach. [Citation Graph (0, 0)][DBLP]
    WEBKDD, 1999, pp:39-55 [Conf]
  20. Matthew V. Mahoney, Philip K. Chan
    Learning nonstationary models of normal network traffic for detecting novel attacks. [Citation Graph (0, 0)][DBLP]
    KDD, 2002, pp:376-385 [Conf]
  21. Hyoung-rae Kim, Philip K. Chan
    Personalized Search Results with User Interest Hierarchies Learnt from Bookmarks. [Citation Graph (0, 0)][DBLP]
    WEBKDD, 2005, pp:158-176 [Conf]
  22. Matthew V. Mahoney, Philip K. Chan
    An Analysis of the 1999 DARPA/Lincoln Laboratory Evaluation Data for Network Anomaly Detection. [Citation Graph (0, 0)][DBLP]
    RAID, 2003, pp:220-237 [Conf]
  23. Gaurav Tandon, Philip Chan, Debasis Mitra
    MORPHEUS: motif oriented representations to purge hostile events from unlabeled sequences. [Citation Graph (0, 0)][DBLP]
    VizSEC, 2004, pp:16-25 [Conf]
  24. Hyoung-rae Kim, Philip K. Chan
    Implicit Indicators for Interesting Web Pages. [Citation Graph (0, 0)][DBLP]
    WEBIST, 2005, pp:270-277 [Conf]
  25. Douglas H. Fisher, Philip K. Chan
    Statistical guidance in symbolic learning. [Citation Graph (0, 0)][DBLP]
    Ann. Math. Artif. Intell., 1990, v:2, n:, pp:135-147 [Journal]
  26. Gaurav Tandon, Philip K. Chan
    On the Learning of System Call Attributes for Host-based Anomaly Detection. [Citation Graph (0, 0)][DBLP]
    International Journal on Artificial Intelligence Tools, 2006, v:15, n:6, pp:875-892 [Journal]
  27. Philip K. Chan, Richard Lippmann
    Machine Learning for Computer Security. [Citation Graph (0, 0)][DBLP]
    Journal of Machine Learning Research, 2006, v:6, n:, pp:2669-2672 [Journal]
  28. Salvatore J. Stolfo, Ouri Wolfson, Philip K. Chan, Hasanat M. Dewan, Leland Woodbury, Jason S. Glazier, David Ohsie
    PARULE: Parallel Rule Processing Using Meta-rules for Redaction. [Citation Graph (0, 0)][DBLP]
    J. Parallel Distrib. Comput., 1991, v:13, n:4, pp:366-382 [Journal]
  29. Wei Fan, Matthew Miller, Salvatore J. Stolfo, Wenke Lee, Philip K. Chan
    Using artificial anomalies to detect unknown and known network intrusions. [Citation Graph (0, 0)][DBLP]
    Knowl. Inf. Syst., 2004, v:6, n:5, pp:507-527 [Journal]
  30. Philip K. Chan, Salvatore J. Stolfo, David Wolpert
    Guest Editors' Introduction. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 1999, v:36, n:1-2, pp:5-7 [Journal]
  31. Salvatore J. Stolfo, Wenke Lee, Philip K. Chan, Wei Fan, Eleazar Eskin
    Data Mining-based Intrusion Detectors: An Overview of the Columbia IDS Project. [Citation Graph (0, 0)][DBLP]
    SIGMOD Record, 2001, v:30, n:4, pp:5-14 [Journal]
  32. Gaurav Tandon, Philip K. Chan
    Weighting versus pruning in rule validation for detecting network and host anomalies. [Citation Graph (0, 0)][DBLP]
    KDD, 2007, pp:697-706 [Conf]

  33. Incrementally Learning Rules for Anomaly Detection. [Citation Graph (, )][DBLP]


  34. Tracking User Mobility to Detect Suspicious Behavior. [Citation Graph (, )][DBLP]


  35. Learning implicit user interest hierarchy for context in personalization. [Citation Graph (, )][DBLP]


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