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Andrew McCallum: [Publications] [Author Rank by year] [Co-authors] [Prefers] [Cites] [Cited by]

Publications of Author

  1. Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery
    Learning to Extract Symbolic Knowledge from the World Wide Web. [Citation Graph (1, 0)][DBLP]
    AAAI/IAAI, 1998, pp:509-516 [Conf]
  2. L. Douglas Baker, Andrew McCallum
    Distributional Clustering of Words for Text Classification. [Citation Graph (1, 0)][DBLP]
    SIGIR, 1998, pp:96-103 [Conf]
  3. Wei Li, Andrew McCallum
    Semi-Supervised Sequence Modeling with Syntactic Topic Models. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:813-818 [Conf]
  4. Aron Culotta, Andrew McCallum
    Reducing Labeling Effort for Structured Prediction Tasks. [Citation Graph (0, 0)][DBLP]
    AAAI, 2005, pp:746-751 [Conf]
  5. Dayne Freitag, Andrew McCallum
    Information Extraction with HMM Structures Learned by Stochastic Optimization. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 2000, pp:584-589 [Conf]
  6. Trausti T. Kristjansson, Aron Culotta, Paul A. Viola, Andrew McCallum
    Interactive Information Extraction with Constrained Conditional Random Fields. [Citation Graph (0, 0)][DBLP]
    AAAI, 2004, pp:412-418 [Conf]
  7. Andrew McCallum, Chris Pal, Gregory Druck, Xuerui Wang
    Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification. [Citation Graph (0, 0)][DBLP]
    AAAI, 2006, pp:- [Conf]
  8. Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell
    Learning to Classify Text from Labeled and Unlabeled Documents. [Citation Graph (0, 0)][DBLP]
    AAAI/IAAI, 1998, pp:792-799 [Conf]
  9. Aron Culotta, Ron Bekkerman, Andrew McCallum
    Extracting social networks and contact information from email and the Web. [Citation Graph (0, 0)][DBLP]
    CEAS, 2004, pp:- [Conf]
  10. Aron Culotta, Andrew McCallum
    Joint deduplication of multiple record types in relational data. [Citation Graph (0, 0)][DBLP]
    CIKM, 2005, pp:257-258 [Conf]
  11. Nadia Ghamrawi, Andrew McCallum
    Collective multi-label classification. [Citation Graph (0, 0)][DBLP]
    CIKM, 2005, pp:195-200 [Conf]
  12. David Pinto, Andrew McCallum, Xing Wei, W. Bruce Croft
    Table Extraction Using Conditional Random Fields. [Citation Graph (0, 0)][DBLP]
    DG.O, 2003, pp:- [Conf]
  13. Shaolei Feng, R. Manmatha, Andrew McCallum
    Exploring the Use of Conditional Random Field Models and HMMs for Historical Handwritten Document Recognition. [Citation Graph (0, 0)][DBLP]
    DIAL, 2006, pp:30-37 [Conf]
  14. Ron Bekkerman, Ran El-Yaniv, Andrew McCallum
    Multi-way distributional clustering via pairwise interactions. [Citation Graph (0, 0)][DBLP]
    ICML, 2005, pp:41-48 [Conf]
  15. Huan Chang, David Cohn, Andrew McCallum
    Learning to Create Customized Authority Lists. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:127-134 [Conf]
  16. John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira
    Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:282-289 [Conf]
  17. Wei Li, Andrew McCallum
    Pachinko allocation: DAG-structured mixture models of topic correlations. [Citation Graph (0, 0)][DBLP]
    ICML, 2006, pp:577-584 [Conf]
  18. Andrew McCallum
    Using Transitional Proximity for Faster Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    ML, 1992, pp:316-321 [Conf]
  19. Andrew McCallum
    Overcoming Incomplete Perception with Util Distinction Memory. [Citation Graph (0, 0)][DBLP]
    ICML, 1993, pp:190-196 [Conf]
  20. Andrew McCallum
    Instance-Based Utile Distinctions for Reinforcement Learning with Hidden State. [Citation Graph (0, 0)][DBLP]
    ICML, 1995, pp:387-395 [Conf]
  21. Andrew McCallum, Dayne Freitag, Fernando C. N. Pereira
    Maximum Entropy Markov Models for Information Extraction and Segmentation. [Citation Graph (0, 0)][DBLP]
    ICML, 2000, pp:591-598 [Conf]
  22. Andrew McCallum, Kamal Nigam
    Employing EM and Pool-Based Active Learning for Text Classification. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:350-358 [Conf]
  23. Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng
    Improving Text Classification by Shrinkage in a Hierarchy of Classes. [Citation Graph (0, 0)][DBLP]
    ICML, 1998, pp:359-367 [Conf]
  24. Andrew McCallum, Kent A. Spackman
    Using Genetic Algorithms to Learn Disjunctive Rules from Examples. [Citation Graph (0, 0)][DBLP]
    ML, 1990, pp:149-152 [Conf]
  25. Nicholas Roy, Andrew McCallum
    Toward Optimal Active Learning through Sampling Estimation of Error Reduction. [Citation Graph (0, 0)][DBLP]
    ICML, 2001, pp:441-448 [Conf]
  26. Jason Rennie, Andrew McCallum
    Using Reinforcement Learning to Spider the Web Efficiently. [Citation Graph (0, 0)][DBLP]
    ICML, 1999, pp:335-343 [Conf]
  27. Charles A. Sutton, Khashayar Rohanimanesh, Andrew McCallum
    Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data. [Citation Graph (0, 0)][DBLP]
    ICML, 2004, pp:- [Conf]
  28. B. Michael Kelm, Chris Pal, Andrew McCallum
    Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning. [Citation Graph (0, 0)][DBLP]
    ICPR (2), 2006, pp:828-832 [Conf]
  29. Andrew McCallum, Andrés Corrada-Emmanuel, Xuerui Wang
    Topic and Role Discovery in Social Networks. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2005, pp:786-791 [Conf]
  30. Andrew McCallum, Kamal Nigam, Jason Rennie, Kristie Seymore
    A Machine Learning Approach to Building Domain-Specific Search Engines. [Citation Graph (0, 0)][DBLP]
    IJCAI, 1999, pp:662-667 [Conf]
  31. Andrew McCallum, Ben Wellner
    Toward Conditional Models of Identity Uncertainty with Application to Proper Noun Coreference. [Citation Graph (0, 0)][DBLP]
    IIWeb, 2003, pp:79-84 [Conf]
  32. Pallika Kanani, Andrew McCallum, Chris Pal
    Improving Author Coreference by Resource-Bounded Information Gathering from the Web. [Citation Graph (0, 0)][DBLP]
    IJCAI, 2007, pp:429-434 [Conf]
  33. Yu Gu, Andrew McCallum, Donald F. Towsley
    Detecting Anomalies in Network Traffic Using Maximum Entropy Estimation. [Citation Graph (0, 0)][DBLP]
    Internet Measurment Conference, 2005, pp:345-350 [Conf]
  34. Gideon S. Mann, David M. Mimno, Andrew McCallum
    Bibliometric impact measures leveraging topic analysis. [Citation Graph (0, 0)][DBLP]
    JCDL, 2006, pp:65-74 [Conf]
  35. Andrew McCallum
    Information extraction, data mining and joint inference. [Citation Graph (0, 0)][DBLP]
    KDD, 2006, pp:835- [Conf]
  36. Andrew McCallum, Kamal Nigam, Lyle H. Ungar
    Efficient clustering of high-dimensional data sets with application to reference matching. [Citation Graph (0, 0)][DBLP]
    KDD, 2000, pp:169-178 [Conf]
  37. Xuerui Wang, Andrew McCallum
    Topics over time: a non-Markov continuous-time model of topical trends. [Citation Graph (0, 0)][DBLP]
    KDD, 2006, pp:424-433 [Conf]
  38. Fuchun Peng, Andrew McCallum
    Accurate Information Extraction from Research Papers using Conditional Random Fields. [Citation Graph (0, 0)][DBLP]
    HLT-NAACL, 2004, pp:329-336 [Conf]
  39. Charles A. Sutton, Michael Sindelar, Andrew McCallum
    Reducing Weight Undertraining in Structured Discriminative Learning. [Citation Graph (0, 0)][DBLP]
    HLT-NAACL, 2006, pp:- [Conf]
  40. Aron Culotta, Andrew McCallum, Jonathan Betz
    Integrating Probabilistic Extraction Models and Data Mining to Discover Relations and Patterns in Text. [Citation Graph (0, 0)][DBLP]
    HLT-NAACL, 2006, pp:- [Conf]
  41. Charles A. Sutton, Andrew McCallum
    Composition of Conditional Random Fields for Transfer Learning. [Citation Graph (0, 0)][DBLP]
    HLT/EMNLP, 2005, pp:- [Conf]
  42. Andrew McCallum
    Instance-Based State Identification for Reinforcement Learning. [Citation Graph (0, 0)][DBLP]
    NIPS, 1994, pp:377-384 [Conf]
  43. Andrew McCallum, Ben Wellner
    Conditional Models of Identity Uncertainty with Application to Noun Coreference. [Citation Graph (0, 0)][DBLP]
    NIPS, 2004, pp:- [Conf]
  44. Rajat Raina, Yirong Shen, Andrew Y. Ng, Andrew McCallum
    Classification with Hybrid Generative/Discriminative Models. [Citation Graph (0, 0)][DBLP]
    NIPS, 2003, pp:- [Conf]
  45. Xuerui Wang, Natasha Mohanty, Andrew McCallum
    Group and Topic Discovery from Relations and Their Attributes. [Citation Graph (0, 0)][DBLP]
    NIPS, 2005, pp:- [Conf]
  46. David Pinto, Andrew McCallum, Xing Wei, W. Bruce Croft
    Table extraction using conditional random fields. [Citation Graph (0, 0)][DBLP]
    SIGIR, 2003, pp:235-242 [Conf]
  47. David M. Blei, J. Andrew Bagnell, Andrew McCallum
    Learning with Scope, with Application to Information Extraction and Classification. [Citation Graph (0, 0)][DBLP]
    UAI, 2002, pp:53-60 [Conf]
  48. Andrew McCallum
    Efficiently Inducing Features of Conditional Random Fields. [Citation Graph (0, 0)][DBLP]
    UAI, 2003, pp:403-410 [Conf]
  49. Ron Bekkerman, Andrew McCallum
    Disambiguating Web appearances of people in a social network. [Citation Graph (0, 0)][DBLP]
    WWW, 2005, pp:463-470 [Conf]
  50. Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Seán Slattery
    Learning to construct knowledge bases from the World Wide Web. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2000, v:118, n:1-2, pp:69-113 [Journal]
  51. Aron Culotta, Trausti T. Kristjansson, Andrew McCallum, Paul A. Viola
    Corrective feedback and persistent learning for information extraction. [Citation Graph (0, 0)][DBLP]
    Artif. Intell., 2006, v:170, n:14-15, pp:1101-1122 [Journal]
  52. William W. Cohen, Andrew McCallum, Dallan Quass
    Learning to Understand the Web. [Citation Graph (0, 0)][DBLP]
    IEEE Data Eng. Bull., 2000, v:23, n:3, pp:17-24 [Journal]
  53. Fuchun Peng, Andrew McCallum
    Information extraction from research papers using conditional random fields. [Citation Graph (0, 0)][DBLP]
    Inf. Process. Manage., 2006, v:42, n:4, pp:963-979 [Journal]
  54. Andrew McCallum, Kamal Nigam, Jason Rennie, Kristie Seymore
    Automating the Construction of Internet Portals with Machine Learning. [Citation Graph (0, 0)][DBLP]
    Inf. Retr., 2000, v:3, n:2, pp:127-163 [Journal]
  55. Xing Wei, W. Bruce Croft, Andrew McCallum
    Table extraction for answer retrieval. [Citation Graph (0, 0)][DBLP]
    Inf. Retr., 2006, v:9, n:5, pp:589-611 [Journal]
  56. Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell
    Text Classification from Labeled and Unlabeled Documents using EM. [Citation Graph (0, 0)][DBLP]
    Machine Learning, 2000, v:39, n:2/3, pp:103-134 [Journal]
  57. Andrew McCallum
    Information extraction: distilling structured data from unstructured text. [Citation Graph (0, 0)][DBLP]
    ACM Queue, 2005, v:3, n:9, pp:48-57 [Journal]
  58. James Allan, Jay Aslam, Nicholas J. Belkin, Chris Buckley, James P. Callan, W. Bruce Croft, Susan T. Dumais, Norbert Fuhr, Donna Harman, David J. Harper, Djoerd Hiemstra, Thomas Hofmann, Eduard H. Hovy, Wessel Kraaij, John D. Lafferty, Victor Lavrenko, David D. Lewis, Liz Liddy, R. Manmatha, Andrew McCallum, Jay M. Ponte, John M. Prager, Dragomir R. Radev, Philip Resnik, Stephen E. Robertson, Ronald Rosenfeld, Salim Roukos, Mark Sanderson, Rich Schwartz, Amit Singhal, Alan F. Smeaton, Howard R. Turtle, Ellen M. Voorhees, Ralph M. Weischedel, Jinxi Xu, ChengXiang Zhai
    Challenges in information retrieval and language modeling: report of a workshop held at the center for intelligent information retrieval, University of Massachusetts Amherst, September 2002. [Citation Graph (0, 0)][DBLP]
    SIGIR Forum, 2003, v:37, n:1, pp:31-47 [Journal]
  59. Wei Li, Andrew McCallum
    Rapid development of Hindi named entity recognition using conditional random fields and feature induction. [Citation Graph (0, 0)][DBLP]
    ACM Trans. Asian Lang. Inf. Process., 2003, v:2, n:3, pp:290-294 [Journal]
  60. Pallika Kanani, Andrew McCallum
    Resource-Bounded Information Gathering for Correlation Clustering. [Citation Graph (0, 0)][DBLP]
    COLT, 2007, pp:625-627 [Conf]
  61. Gideon S. Mann, Andrew McCallum
    Simple, robust, scalable semi-supervised learning via expectation regularization. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:593-600 [Conf]
  62. David M. Mimno, Wei Li, Andrew McCallum
    Mixtures of hierarchical topics with Pachinko allocation. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:633-640 [Conf]
  63. Charles A. Sutton, Andrew McCallum
    Piecewise pseudolikelihood for efficient training of conditional random fields. [Citation Graph (0, 0)][DBLP]
    ICML, 2007, pp:863-870 [Conf]
  64. David M. Mimno, Andrew McCallum
    Mining a digital library for influential authors. [Citation Graph (0, 0)][DBLP]
    JCDL, 2007, pp:105-106 [Conf]
  65. David M. Mimno, Andrew McCallum
    Organizing the OCA: learning faceted subjects from a library of digital books. [Citation Graph (0, 0)][DBLP]
    JCDL, 2007, pp:376-385 [Conf]
  66. Xuerui Wang, Chris Pal, Andrew McCallum
    Generalized component analysis for text with heterogeneous attributes. [Citation Graph (0, 0)][DBLP]
    KDD, 2007, pp:794-803 [Conf]
  67. Aron Culotta, Michael Wick, Robert Hall, Matthew Marzilli, Andrew McCallum
    Canonicalization of database records using adaptive similarity measures. [Citation Graph (0, 0)][DBLP]
    KDD, 2007, pp:201-209 [Conf]
  68. Gregory Druck, Chris Pal, Andrew McCallum, Xiaojin Zhu
    Semi-supervised classification with hybrid generative/discriminative methods. [Citation Graph (0, 0)][DBLP]
    KDD, 2007, pp:280-289 [Conf]
  69. David M. Mimno, Andrew McCallum
    Expertise modeling for matching papers with reviewers. [Citation Graph (0, 0)][DBLP]
    KDD, 2007, pp:500-509 [Conf]
  70. Ben Wellner, Andrew McCallum, Fuchun Peng, Michael Hay
    An Integrated, Conditional Model of Information Extraction and Coreference with Appli. [Citation Graph (0, 0)][DBLP]
    UAI, 2004, pp:593-601 [Conf]
  71. Andrew McCallum, Kedar Bellare, Fernando C. N. Pereira
    A Conditional Random Field for Discriminatively-trained Finite-state String Edit Distance. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:388-395 [Conf]
  72. Charles A. Sutton, Andrew McCallum
    Piecewise Training for Undirected Models. [Citation Graph (0, 0)][DBLP]
    UAI, 2005, pp:568-575 [Conf]

  73. Generalized Expectation Criteria for Semi-Supervised Learning of Conditional Random Fields. [Citation Graph (, )][DBLP]

  74. People-LDA: Anchoring Topics to People using Face Recognition. [Citation Graph (, )][DBLP]

  75. Cryptogram Decoding for OCR Using Numerization Strings. [Citation Graph (, )][DBLP]

  76. Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval. [Citation Graph (, )][DBLP]

  77. High-Performance Semi-Supervised Learning using Discriminatively Constrained Generative Models. [Citation Graph (, )][DBLP]

  78. A unified approach for schema matching, coreference and canonicalization. [Citation Graph (, )][DBLP]

  79. Unsupervised deduplication using cross-field dependencies. [Citation Graph (, )][DBLP]

  80. Efficient methods for topic model inference on streaming document collections. [Citation Graph (, )][DBLP]

  81. First-Order Probabilistic Models for Coreference Resolution. [Citation Graph (, )][DBLP]

  82. Efficient Computation of Entropy Gradient for Semi-Supervised Conditional Random Fields. [Citation Graph (, )][DBLP]

  83. Resource-Bounded Information Extraction: Acquiring Missing Feature Values on Demand. [Citation Graph (, )][DBLP]

  84. Bi-directional Joint Inference for Entity Resolution and Segmentation Using Imperatively-Defined Factor Graphs. [Citation Graph (, )][DBLP]

  85. Modeling Relations and Their Mentions without Labeled Text. [Citation Graph (, )][DBLP]

  86. An Entity Based Model for Coreference Resolution. [Citation Graph (, )][DBLP]

  87. Learning from labeled features using generalized expectation criteria. [Citation Graph (, )][DBLP]

  88. Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression. [Citation Graph (, )][DBLP]

  89. A Discriminative Approach to Ontology Mapping. [Citation Graph (, )][DBLP]

  90. Active Learning by Labeling Features. [Citation Graph (, )][DBLP]

  91. Polylingual Topic Models. [Citation Graph (, )][DBLP]

  92. Generalized Expectation Criteria for Bootstrapping Extractors using Record-Text Alignment. [Citation Graph (, )][DBLP]

  93. Learning Field Compatibilities to Extract Database Records from Unstructured Text. [Citation Graph (, )][DBLP]

  94. Scalable Probabilistic Databases with Factor Graphs and MCMC [Citation Graph (, )][DBLP]

  95. Distantly Labeling Data for Large Scale Cross-Document Coreference [Citation Graph (, )][DBLP]

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