David D. Lewis

发表

RCV1: A New Benchmark Collection for Text Categorization Research

Yiming Yang, Fan Li, David D. Lewis, 2004, J. Mach. Learn. Res..

New demands on information retrieval provide opportunities for natural language processing to work together with proven statistical retrieval approaches.

Karen Sparck Jones, David D. Lewis, D. Lewis, 1996 .

Automatic classification of Web queries using very large unlabeled query logs

Ophir Frieder, Abdur Chowdhury, Eric C. Jensen, 2007, TOIS.

Minutes of the 1996 ACM SIGIR Business Meeting

David D. Lewis, 1996, SIGF.

Natural language processing for information retrieval

Karen Spärck Jones, David D. Lewis, D. Lewis, 1996, CACM.

Large-Scale Bayesian Logistic Regression for Text Categorization

David Madigan, David D. Lewis, Alexander Genkin, 2007, Technometrics.

A complex document information processing prototype

Ellen M. Voorhees, Shlomo Argamon, Ophir Frieder, 2006, SIGIR '06.

Text categorization of low quality images

David D. Lewis, David J. Ittner, David D. Ahn, 1995 .

Representation and Learning in Information Retrieval

David D. Lewis, D. Lewis, 1991 .

The use of phrases and structured queries in information retrieval

W. Bruce Croft, Howard R. Turtle, David D. Lewis, 1991, SIGIR '91.

Designing XML Internet applications

Matthew Fuchs, Michael Leventhal, David D. Lewis, 1998 .

Training algorithms for linear text classifiers

James P. Callan, Robert E. Schapire, David D. Lewis, 1996, SIGIR '96.

Constructing informative prior distributions from domain knowledge in text classification

David Madigan, David D. Lewis, Aynur A. Dayanik, 2006, SIGIR.

Feature Selection and Feature Extraction for Text Categorization

David D. Lewis, D. Lewis, 1992, HLT.

Guest Editorial - Special Issue on Text Categorization

Philip J. Hayes, David D. Lewis, D. Lewis, 1994, ACM Trans. Inf. Syst..

Fax: An Alternative to SGML

Kenneth Ward Church, William A. Gale, David D. Lewis, 1994, COLING.

A comparison of two learning algorithms for text categorization

David D. Lewis, Marc Ringuette, D. Lewis, 1994 .

Complex document information processing: prototype, test collection, and evaluation

Shlomo Argamon, Ophir Frieder, Gady Agam, 2006, Electronic Imaging.

The TREC-5 Filtering Track

David D. Lewis, D. Lewis, 1996, TREC.

Naive (Bayes) at Forty: The Independence Assumption in Information Retrieval

David D. Lewis, D. Lewis, 1998, ECML.

Approximating matrix multiplication for pattern recognition tasks

Edith Cohen, David D. Lewis, D. Lewis, 1997, SODA '97.

TREC-3 Ad-Hoc, Routing Retrieval and Thresholding Experiments using PIRCS

Kui-Lam Kwok, Laszlo Grunfeld, David D. Lewis, 1994, TREC.

Text Retrieval Priors for Bayesian Logistic Regression

Ophir Frieder, Eugene Yang, David D. Lewis, 2019, SIGIR.

Boosting for document routing

Yoram Singer, Robert E. Schapire, Amit Singhal, 2000, CIKM '00.

A Regularization Approach to Combining Keywords and Training Data in Technology-Assisted Review

Ophir Frieder, Eugene Yang, David D. Lewis, 2019, ICAIL.

A sequential algorithm for training text classifiers: corrigendum and additional data

David D. Lewis, D. Lewis, 1995, SIGF.

Prospective Data Fusion for Batch Filtering

Dmitriy Fradkin, David D. Lewis, Vladimir Menkov, 2003 .

Challenges in machine learning for text classification

David D. Lewis, D. Lewis, 1996, COLT '96.

An evaluation of phrasal and clustered representations on a text categorization task

David D. Lewis, D. Lewis, 1992, SIGIR '92.

A history of AI and Law in 50 papers: 25 years of the international conference on AI and Law

Trevor J. M. Bench-Capon, Henry Prakken, Floris Bex, 2012, Artificial Intelligence and Law.

Automatic web query classification using labeled and unlabeled training data

Ophir Frieder, Abdur Chowdhury, Eric C. Jensen, 2005, SIGIR '05.

Towards minimizing the annotation cost of certified text classification

Douglas W. Oard, William Webber, Mossaab Bagdouri, 2013, CIKM.

Minutes - 1995 ACM SIGIR Annual Meeting

David D. Lewis, David D. Lewis, 1995, SIGIR Forum.

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

Djoerd Hiemstra, Alan F. Smeaton, Nicholas J. Belkin, 2003, SIGF.

ATTICS (poster abstract): a software platform for online text classification

Amit Singhal, David D. Lewis, Daniel L. Stern, 1999, SIGIR '99.

Applying Support Vector Machines to the TREC-2001 Batch Filtering and Routing Tasks

David D. Lewis, D. Lewis, 2001, TREC.

Learning in Intelligent Information Retrieval

David D. Lewis, D. Lewis, 1991, ML.

A sequential algorithm for training text classifiers

William A. Gale, David D. Lewis, D. Lewis, 1994, SIGIR '94.

Improving automatic query classification via semi-supervised learning

Ophir Frieder, Abdur Chowdhury, Eric C. Jensen, 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

Evaluating Message Understanding Systems: An Analysis of the Third Message Understanding Conference (MUC-3)

Lynette Hirschman, Nancy Chinchor, David D. Lewis, 1993, CL.

Term clustering of syntactic phrases

W. Bruce Croft, David D. Lewis, D. Lewis, 1989, SIGIR '90.

Text filtering in MUC-3 and MUC-4

David D. Lewis, Richard M. Tong, 1992, MUC.

Content-based document image retrieval in complex document collections

Shlomo Argamon, Ophir Frieder, David A. Grossman, 2007, Electronic Imaging.

AT&T at TREC-7

Amit Singhal, Fernando Pereira, Donald Hindle, 1998, TREC.

Language‐oriented information retrieval

W. Bruce Croft, Nehru Bhandaru, David D. Lewis, 1989, Int. J. Intell. Syst..

Information retrieval for e-discovery

David D. Lewis, D. Lewis, 2010, SIGIR.

Data extraction as text categorization: an experiment with the MUC-3 corpus

David D. Lewis, D. Lewis, 1991, MUC.

Use of Natural Language Processing at TREC

Alan F. Smeaton, David D. Lewis, D. Lewis, 1992, Text Retrieval Conference.

Evaluating and optimizing autonomous text classification systems

David D. Lewis, D. Lewis, 1995, SIGIR '95.

Evaluation of information retrieval for E-discovery

Douglas W. Oard, David D. Lewis, Stephen Tomlinson, 2010, Artificial Intelligence and Law.

Text representation for intelligent text retrieval: a classification-oriented view

David D. Lewis, 1992 .

DIMACS at the TREC 2004 Genomics Track

Paul B. Kantor, Dmitriy Fradkin, David Madigan, 2004, TREC.

Retrieval and Richness when Querying by Document

Ophir Frieder, David A. Grossman, Eugene Yang, 2018, DESIRES.

Building a test collection for complex document information processing

Shlomo Argamon, Ophir Frieder, Gady Agam, 2006, SIGIR.

Threading Electronic Mail - A Preliminary Study

David D. Lewis, K. A. Knowles, D. Lewis, 1997, Inf. Process. Manag..

An approach to natural language for document retrieval

W. Bruce Croft, David D. Lewis, 1987, SIGIR '87.

TREC 2006 Legal Track Overview

Douglas W. Oard, David D. Lewis, Jason R. Baron, 2006, TREC.

Reuters-21578 Text Categorization Test Collection, Distribution 1.0

David D. Lewis, D. Lewis, 1997 .

DIMACS AT THE TREC 2004 GENOMICS TRACK (DRAFT)

Dmitriy Fradkin, David Madigan, David D. Lewis, 2004 .

On the Naive Bayes Model for Text Categorization

David Madigan, David D. Lewis, Susana Eyheramendy, 2003, AISTATS.

Representation Quality in Text Classification: An Introduction and Experiment

David D. Lewis, D. Lewis, 1990, HLT.

The TREC-4 Filtering Track

David D. Lewis, 1995, TREC.

Web Service Integration for Next Generation Localisation

Andy Way, John Keeney, Kevin Feeney, 2009 .

Feature Selection and Feature Extraction for Text Categorization

David D. Lewis, D. Lewis, 1992, HLT.

Sequential testing in classifier evaluation yields biased estimates of effectiveness

Douglas W. Oard, William Webber, Mossaab Bagdouri, 2013, SIGIR.

Report on the Workshop on Operational Text Classification systems (OTC-01)

Fabrizio Sebastiani, David D. Lewis, 2001, SIGF.

DIMACS at the TREC 2005 Genomics Track

Paul B. Kantor, David Madigan, David D. Lewis, 2005, TREC.

XML Developer's Resource Library

Michael Leventhal, David D. Lewis, David Megginson, 1998 .

Report on the workshop on Operational Text Classification Systems (OTC-02)

Susan T. Dumais, Fabrizio Sebastiani, David D. Lewis, 2002, SIGF.

Device generating interpreter to analyze data

William A. Gale, David D. Lewis, Jason A. Catlett, 1995 .

Heterogeneous Uncertainty Sampling for Supervised Learning

David D. Lewis, Jason Catlett, D. Lewis, 1994, ICML.

Rutgers Filtering Work at TREC 2002: Adaptive and Batch

Paul B. Kantor, Endre Boros, David D. Lewis, 2002, TREC.

Evaluating Text Categorization I

David D. Lewis, D. Lewis, 1991, HLT.

Afterword: data, knowledge, and e-discovery

David D. Lewis, 2010, Artificial Intelligence and Law.

On minimizing cost in legal document review workflows

Ophir Frieder, David D. Lewis, Eugene Yang, 2021, DocEng.

Heuristic stopping rules for technology-assisted review

Ophir Frieder, David D. Lewis, Eugene Yang, 2021, DocEng.

Goldilocks: Just-Right Tuning of BERT for Technology-Assisted Review pdf

Ophir Frieder, Sean MacAvaney, David D. Lewis, 2021, ECIR.

Certifying One-Phase Technology-Assisted Reviews

Ophir Frieder, David D. Lewis, Eugene Yang, 2021, CIKM.

TAR on Social Media: A Framework for Online Content Moderation

Ophir Frieder, David D. Lewis, Eugene Yang, 2021, DESIRES.

Sparse Bayesian Classifiers for Text Categorization ( U )

Wen-Hua Ju, David Madigan, David D. Lewis, 2003 .

Approximating Matrix Multiplicationfor Pattern Recognition

David D. Lewis, D. Lewis, TasksEdith Cohen, 1997 .