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Andrew Mccallum
(ALIAS: Andrew R. McCallum) [FOAF]  [Follow]

Position: Associate Professor
Affiliation: Department of Computer Science University of Massachusetts Amherst
Address: Department of Computer Science University of Massachusetts Amherst 140 Governors Drive Amherst, MA 01003
Phone: (413) 545-1323
Fax: (413) 545-1789
Email:
Homepage: http://www.cs.umass.edu/~mccallum/
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Statistics: H-index: 37 (See all experts' h-index.)
total citation number: 11033
highest-cited paper: Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data (2001) at ICML (Cited By 2905)

bio:

Associate Professor, Department of Computer Science, University of Massachusetts Amherst, (2003-pres ... More

Research Interest:

information extraction, Conditional Random Fields, conditional random field, Reinforcement Learning, Conditional Models

Show Temporal Interests (Do you want to see the change of his/her research interests?)


National Science Foundation - US

[4] RI-Medium: Collaborative Research: Dynamically-Structured Conditional Random Fields for Complex, Natural Domains (0803847), 2008-08-01 － 2009-07-31
[3] CRI: Collaborative Research: Improving Experimental Computer Science with a Searchable Web Portal for Data Sets (0551597), 2006-03-15 － 2010-02-28
[2] ITR: Collaborative Research: (ACS+NHS)-(dmc+soc): Machine Learning for Sequences and Structured Data: Tools for Non-Experts (0427594), 2004-09-01 － 2008-08-31
[1] ITR: Unified Graphical Models of Information Extraction and Data Mining with Application to Social Network Analysis (0326249), 2003-09-15 － 2010-08-31

Publications: [Edit disambiguation Result]

2009(4)
[88]Limin Yao, David M. Mimno, Andrew McCallum. Efficient methods for topic model inference on streaming document collections.  KDD'2009. pp.937~946    Cited By 8[Bibtex]
[87]Sameer Singh, Karl Schultz, Andrew McCallum. Bi-directional Joint Inference for Entity Resolution and Segmentation Using Imperatively-Defined Factor Graphs.  ECML/PKDD (2)'2009. pp.414~429    Cited By 4[Bibtex]
[86]Michael L. Wick, Aron Culotta, Khashayar Rohanimanesh, Andrew McCallum. An Entity Based Model for Coreference Resolution.  SDM'2009. pp.365~376    Cited By 2[Bibtex]
[85]Charles A. Sutton, Andrew McCallum. Piecewise training for structured prediction. Machine Learning, 2009: 165~194    Cited By 4[Bibtex]
2008(5)
[84]Robert Hall, Charles A. Sutton, Andrew McCallum. Unsupervised deduplication using cross-field dependencies.  KDD'2008. pp.310~317    Cited By 8[Bibtex]
[83]Michael L. Wick, Khashayar Rohanimanesh, Karl Schultz, Andrew McCallum. A unified approach for schema matching, coreference and canonicalization.  KDD'2008. pp.722~730    Cited By 9[Bibtex]
[82]Gregory Druck, Gideon S. Mann, Andrew McCallum. Learning from labeled features using generalized expectation criteria.  SIGIR'2008. pp.595~602    Cited By 41[Bibtex]
[81]David M. Mimno, Andrew McCallum. Topic Models Conditioned on Arbitrary Features with Dirichlet-multinomial Regression.  UAI'2008. pp.411~418    Cited By 18[Bibtex]
[80]Michael L. Wick, Khashayar Rohanimanesh, Andrew McCallum, AnHai Doan. A Discriminative Approach to Ontology Mapping.  NTII'2008. pp.16~19   [Bibtex]
2007(18)
[79]Pallika Kanani, Andrew McCallum. Resource-Bounded Information Gathering for Correlation Clustering.  COLT'2007. pp.625~627    Cited By 4[Bibtex]
[78]Vidit Jain, Erik G. Learned-Miller, Andrew McCallum. People-LDA: Anchoring Topics to People using Face Recognition.  ICCV'2007. pp.1~8    Cited By 15[Bibtex]
[77]Gary B. Huang, Erik G. Learned-Miller, Andrew McCallum. Cryptogram Decoding for OCR Using Numerization Strings.  ICDAR'2007. pp.208~212   [Bibtex]
[76]Xuerui Wang, Andrew McCallum, Xing Wei. Topical N-Grams: Phrase and Topic Discovery, with an Application to Information Retrieval.  ICDM'2007. pp.697~702    Cited By 35[Bibtex]
[75]David M. Mimno, Wei Li, Andrew McCallum. Mixtures of hierarchical topics with Pachinko allocation.  ICML'2007. pp.633~640    Cited By 26[Bibtex]
[74]Charles A. Sutton, Andrew McCallum. Piecewise pseudolikelihood for efficient training of conditional random fields.  ICML'2007. pp.863~870    Cited By 22[Bibtex]
[73]Gideon S. Mann, Andrew McCallum. Simple, robust, scalable semi-supervised learning via expectation regularization.  ICML'2007. pp.593~600    Cited By 44[Bibtex]
[72]Pallika Kanani, Andrew McCallum, Chris Pal. Improving Author Coreference by Resource-Bounded Information Gathering from the Web.  IJCAI'2007. pp.429~434    Cited By 25[Bibtex] [PDF]
[71]David M. Mimno, Andrew McCallum. Organizing the OCA: learning faceted subjects from a library of digital books.  JCDL'2007. pp.376~385    Cited By 20[Bibtex]
[70]David M. Mimno, Andrew McCallum. Mining a digital library for influential authors.  JCDL'2007. pp.105~106    Cited By 5[Bibtex]
[69]Xuerui Wang, Chris Pal, Andrew McCallum. Generalized component analysis for text with heterogeneous attributes.  KDD'2007. pp.794~803    Cited By 2[Bibtex]
[68]David M. Mimno, Andrew McCallum. Expertise modeling for matching papers with reviewers.  KDD'2007. pp.500~509    Cited By 36[Bibtex]
[67]Aron Culotta, Michael L. Wick, Robert Hall, Matthew Marzilli, Andrew McCallum. Canonicalization of database records using adaptive similarity measures.  KDD'2007. pp.201~209    Cited By 8[Bibtex]
[66]Gregory Druck, Chris Pal, Andrew McCallum, Xiaojin Zhu. Semi-supervised classification with hybrid generative/discriminative methods.  KDD'2007. pp.280~289    Cited By 26[Bibtex]
[65]Aron Culotta, Michael L. Wick, Andrew McCallum. First-Order Probabilistic Models for Coreference Resolution.  HLT-NAACL'2007. pp.81~88   [Bibtex]
[64]Gideon S. Mann, Andrew McCallum. Efficient Computation of Entropy Gradient for Semi-Supervised Conditional Random Fields.  HLT-NAACL (Short Papers)'2007. pp.109~112    Cited By 10[Bibtex]
[63]Andrew McCallum, Xuerui Wang, Andres Corrada-Emmanuel. Topic and Role Discovery in Social Networks with Experiments on Enron and Academic Email. J. Artif. Intell. Res. (JAIR), 2007: 249~272    Cited By 179[Bibtex]
[62]Haizheng Zhang, John Yen, C. Lee Giles, Bamshad Mobasher, Myra Spiliopoulou, Jaideep Srivastava, Olfa Nasraoui, Andrew McCallum. WebKDD/SNAKDD 2007: web mining and social network analysis post-workshop report. SIGKDD Explorations, 2007: 87~92   [Bibtex]
2006(12)
[61]Andrew McCallum, Chris Pal, Gregory Druck, Xuerui Wang. Multi-Conditional Learning: Generative/Discriminative Training for Clustering and Classification.  AAAI'2006.    [Bibtex] [PDF]
[60]Shaolei Feng, R. Manmatha, Andrew McCallum. Exploring the Use of Conditional Random Field Models and HMMs for Historical Handwritten Document Recognition.  DIAL'2006. pp.30~37    Cited By 13[Bibtex]
[59]Wei Li, Andrew McCallum. Pachinko allocation: DAG-structured mixture models of topic correlations.  ICML'2006. pp.577~584    Cited By 109[Bibtex] [PDF]
[58]B. Michael Kelm, Chris Pal, Andrew McCallum. Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning.  ICPR (2)'2006. pp.828~832    Cited By 11[Bibtex] [PDF]
[57]Gideon S. Mann, David M. Mimno, Andrew McCallum. Bibliometric impact measures leveraging topic analysis.  JCDL'2006. pp.65~74    Cited By 31[Bibtex] [PDF]
[56]Andrew McCallum. Information extraction, data mining and joint inference.  KDD'2006. pp.835~835    Cited By 2[Bibtex] [PDF]
[55]Xuerui Wang, Andrew McCallum. Topics over time: a non-Markov continuous-time model of topical trends.  KDD'2006. pp.424~433    Cited By 148[Bibtex] [PDF]
[54]Charles A. Sutton, Michael Sindelar, Andrew McCallum. Reducing Weight Undertraining in Structured Discriminative Learning.  HLT-NAACL'2006.     Cited By 13[Bibtex] [PDF]
[53]Aron Culotta, Andrew McCallum, Jonathan Betz. Integrating Probabilistic Extraction Models and Data Mining to Discover Relations and Patterns in Text.  HLT-NAACL'2006.     Cited By 47[Bibtex] [PDF]
[52]Aron Culotta, Trausti T. Kristjansson, Andrew McCallum, Paul A. Viola. Corrective feedback and persistent learning for information extraction. Artif. Intell., 2006: 1101~1122    Cited By 28[Bibtex]
[51]Fuchun Peng, Andrew McCallum. Information extraction from research papers using conditional random fields. Inf. Process. Manage., 2006: 963~979    Cited By 183[Bibtex]
[50]Xing Wei, W. Bruce Croft, Andrew McCallum. Table extraction for answer retrieval. Inf. Retr., 2006: 589~611   [Bibtex]
2005(13)
[49]Aron Culotta, Andrew McCallum. Reducing Labeling Effort for Structured Prediction Tasks.  AAAI'2005. pp.746~751    Cited By 29[Bibtex]
[48]Wei Li, Andrew McCallum. Semi-Supervised Sequence Modeling with Syntactic Topic Models.  AAAI'2005. pp.813~818    Cited By 36[Bibtex] [PDF]
[47]Nadia Ghamrawi, Andrew McCallum. Collective multi-label classification.  CIKM'2005. pp.195~200    Cited By 66[Bibtex] [PDF]
[46]Aron Culotta, Andrew McCallum. Joint deduplication of multiple record types in relational data.  CIKM'2005. pp.257~258    Cited By 28[Bibtex] [PDF]
[45]Ron Bekkerman, Ran El-Yaniv, Andrew McCallum. Multi-way distributional clustering via pairwise interactions.  ICML'2005. pp.41~48    Cited By 70[Bibtex]
[44]Andrew McCallum, Andres Corrada-Emmanuel, Xuerui Wang. Topic and Role Discovery in Social Networks.  IJCAI'2005. pp.786~791   [Bibtex] [PDF]
[43]Yu Gu, Andrew McCallum, Donald F. Towsley. Detecting Anomalies in Network Traffic Using Maximum Entropy Estimation.  Internet Measurment Conference'2005. pp.345~350    Cited By 101[Bibtex] [PDF]
[42]Charles A. Sutton, Andrew McCallum. Composition of Conditional Random Fields for Transfer Learning.  HLT/EMNLP'2005.     Cited By 28[Bibtex] [PDF]
[41]Xuerui Wang, Natasha Mohanty, Andrew McCallum. Group and Topic Discovery from Relations and Their Attributes.  NIPS'2005.     Cited By 21[Bibtex] [PDF]
[40]Charles A. Sutton, Andrew McCallum. Piecewise Training for Undirected Models.  UAI'2005. pp.568~575   [Bibtex]
[39]Andrew McCallum, Kedar Bellare, Fernando C. N. Pereira. A Conditional Random Field for Discriminatively-trained Finite-state String Edit Distance.  UAI'2005. pp.388~395    Cited By 64[Bibtex]
[38]Ron Bekkerman, Andrew McCallum. Disambiguating Web appearances of people in a social network.  WWW'2005. pp.463~470    Cited By 159[Bibtex]
[37]Andrew McCallum. Information extraction: distilling structured data from unstructured text. ACM Queue, 2005: 48~57    Cited By 69[Bibtex]
2004(6)
[36]Trausti T. Kristjansson, Aron Culotta, Paul A. Viola, Andrew McCallum. Interactive Information Extraction with Constrained Conditional Random Fields.  AAAI'2004. pp.412~418    Cited By 77[Bibtex] [PDF]
[35]Aron Culotta, Ron Bekkerman, Andrew McCallum. Extracting social networks and contact information from email and the Web.  CEAS'2004.    [Bibtex] [PDF]
[34]Charles A. Sutton, Khashayar Rohanimanesh, Andrew McCallum. Dynamic conditional random fields: factorized probabilistic models for labeling and segmenting sequence data.  ICML'2004.    [Bibtex] [PDF]
[33]Fuchun Peng, Andrew McCallum. Accurate Information Extraction from Research Papers using Conditional Random Fields.  HLT-NAACL'2004. pp.329~336    Cited By 183[Bibtex] [PDF]
[32]Andrew McCallum, Ben Wellner. Conditional Models of Identity Uncertainty with Application to Noun Coreference.  NIPS'2004.     Cited By 125[Bibtex] [PDF]
[31]Ben Wellner, Andrew McCallum, Fuchun Peng, Michael Hay. An Integrated, Conditional Model of Information Extraction and Coreference with Appli.  UAI'2004. pp.593~601   [Bibtex]
2003(7)
[30]David Pinto, Andrew McCallum, Xing Wei, W. Bruce Croft. Table Extraction Using Conditional Random Fields.  DG.O'2003.     Cited By 206[Bibtex] [PDF]
[29]Andrew McCallum, Ben Wellner. Toward Conditional Models of Identity Uncertainty with Application to Proper Noun Coreference.  IIWeb'2003. pp.79~84    Cited By 88[Bibtex] [PDF]
[28]Rajat Raina, Yirong Shen, Andrew Y. Ng, Andrew McCallum. Classification with Hybrid Generative/Discriminative Models.  NIPS'2003.     Cited By 92[Bibtex] [PDF]
[27]David Pinto, Andrew McCallum, Xing Wei, W. Bruce Croft. Table extraction using conditional random fields.  SIGIR'2003. pp.235~242    Cited By 206[Bibtex] [PDF]
[26]Andrew McCallum. Efficiently Inducing Features of Conditional Random Fields.  UAI'2003. pp.403~410    Cited By 252[Bibtex]
[25]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, Richard M. 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. SIGIR Forum, 2003: 31~47    Cited By 86[Bibtex]
[24]Wei Li, Andrew McCallum. Rapid development of Hindi named entity recognition using conditional random fields and feature induction. ACM Trans. Asian Lang. Inf. Process., 2003: 290~294    Cited By 49[Bibtex]
2002(1)
[23]David M. Blei, J. Andrew Bagnell, Andrew McCallum. Learning with Scope, with Application to Information Extraction and Classification.  UAI'2002. pp.53~60    Cited By 23[Bibtex]
2001(2)
[22]Nicholas Roy, Andrew McCallum. Toward Optimal Active Learning through Sampling Estimation of Error Reduction.  ICML'2001. pp.441~448    Cited By 314[Bibtex] [PDF]
[21]John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data.  ICML'2001. pp.282~289    Cited By 2905[Bibtex] [PDF]
2000(8)
[20]Dayne Freitag, Andrew McCallum. Information Extraction with HMM Structures Learned by Stochastic Optimization.  AAAI/IAAI'2000. pp.584~589    Cited By 207[Bibtex] [PDF]
[19]Andrew McCallum, Dayne Freitag, Fernando C. N. Pereira. Maximum Entropy Markov Models for Information Extraction and Segmentation.  ICML'2000. pp.591~598    Cited By 652[Bibtex] [PDF]
[18]Huan Chang, David Cohn, Andrew McCallum. Learning to Create Customized Authority Lists.  ICML'2000. pp.127~134    Cited By 40[Bibtex] [PDF]
[17]Andrew McCallum, Kamal Nigam, Lyle H. Ungar. Efficient clustering of high-dimensional data sets with application to reference matching.  KDD'2000. pp.169~178    Cited By 364[Bibtex] [PDF]
[16]Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Sean Slattery. Learning to construct knowledge bases from the World Wide Web. Artif. Intell., 2000: 69~113   [Bibtex] [PDF]
[15]William W. Cohen, Andrew McCallum, Dallan Quass. Learning to Understand the Web. IEEE Data Eng. Bull., 2000: 17~24    Cited By 22[Bibtex]
[14]Andrew McCallum, Kamal Nigam, Jason Rennie, Kristie Seymore. Automating the Construction of Internet Portals with Machine Learning. Inf. Retr., 2000: 127~163    Cited By 303[Bibtex] [PDF]
[13]Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell. Text Classification from Labeled and Unlabeled Documents using EM. Machine Learning, 2000: 103~134    Cited By 1431[Bibtex] [PDF]
1999(2)
[12]Jason Rennie, Andrew McCallum. Using Reinforcement Learning to Spider the Web Efficiently.  ICML'1999. pp.335~343    Cited By 236[Bibtex] [PDF]
[11]Andrew McCallum, Kamal Nigam, Jason Rennie, Kristie Seymore. A Machine Learning Approach to Building Domain-Specific Search Engines.  IJCAI'1999. pp.662~667    Cited By 126[Bibtex] [PDF]
1998(5)
[10]Mark Craven, Dan DiPasquo, Dayne Freitag, Andrew McCallum, Tom M. Mitchell, Kamal Nigam, Sean Slattery. Learning to Extract Symbolic Knowledge from the World Wide Web.  AAAI/IAAI'1998. pp.509~516    Cited By 537[Bibtex] [PDF]
[9]Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom M. Mitchell. Learning to Classify Text from Labeled and Unlabeled Documents.  AAAI/IAAI'1998. pp.792~799    Cited By 284[Bibtex]
[8]Andrew McCallum, Ronald Rosenfeld, Tom M. Mitchell, Andrew Y. Ng. Improving Text Classification by Shrinkage in a Hierarchy of Classes.  ICML'1998. pp.359~367    Cited By 417[Bibtex] [PDF]
[7]Andrew McCallum, Kamal Nigam. Employing EM and Pool-Based Active Learning for Text Classification.  ICML'1998. pp.350~358    Cited By 4[Bibtex] [PDF]
[6]L. Douglas Baker, Andrew McCallum. Distributional Clustering of Words for Text Classification.  SIGIR'1998. pp.96~103    Cited By 452[Bibtex] [PDF]
1995(1)
[5]Andrew McCallum. Instance-Based Utile Distinctions for Reinforcement Learning with Hidden State.  ICML'1995. pp.387~395    Cited By 165[Bibtex] [PDF]
1994(1)
[4]Andrew McCallum. Instance-Based State Identification for Reinforcement Learning.  NIPS'1994. pp.377~384   [Bibtex] [PDF]
1993(1)
[3]Andrew McCallum. Overcoming Incomplete Perception with Util Distinction Memory.  ICML'1993. pp.190~196   [Bibtex] [PDF]
1992(1)
[2]Andrew McCallum. Using Transitional Proximity for Faster Reinforcement Learning.  ML'1992. pp.316~321    Cited By 19[Bibtex] [PDF]
1990(1)
[1]Andrew McCallum, Kent A. Spackman. Using Genetic Algorithms to Learn Disjunctive Rules from Examples.  ML'1990. pp.149~152    Cited By 26[Bibtex] [PDF]