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..

A comparison of two learning algorithms for text categorization

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

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

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

Training algorithms for linear text classifiers

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

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

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

Representation and Learning in Information Retrieval

David D. Lewis, D. Lewis, 1991 .

Evaluating Text Categorization I

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

Evaluating and optimizing autonomous text classification systems

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

A sequential algorithm for training text classifiers

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

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

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

Threading Electronic Mail - A Preliminary Study

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

Feature Selection and Feature Extraction for Text Categorization

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

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

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

Reuters-21578 Text Categorization Test Collection, Distribution 1.0

David D. Lewis, D. Lewis, 1997 .

Heterogeneous Uncertainty Sampling for Supervised Learning

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

Boosting for document routing

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

Text categorization of low quality images

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

Approximating matrix multiplication for pattern recognition tasks

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

Large-Scale Bayesian Logistic Regression for Text Categorization

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

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

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

Sparse Bayesian Classifiers for Text Categorization ( U )

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

Filtering in MUC-3 and MUC-4 Introduction

D. Lewis, 2015 .

Pattern Taxonomy Mining for Text Categorization

Christopher D. Manning, D. Lewis, P. Raghavan, 2017 .

TARexp: A Python Framework for Technology-Assisted Review Experiments

D. Lewis, Eugene Yang, 2022, SIGIR.

Use of Natural Language Processing at TREC

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

An Approach to Natural Language Processing for Document Retrieval.

W. Bruce Croft, David Lewis, D. Lewis, 1987, Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.

An Advanced Fuzzy Constructing Algorithm for Feature Discovery in Text Mining

D. Lewis, T. Rose, 2018 .

Constructing informative prior distributions from domain knowledge in text classification

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

DIMACS AT THE TREC 2004 GENOMICS TRACK (DRAFT)

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

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

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

Feature Selection and Feature Extraction for Text Categorization

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

Natural language processing for information retrieval

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

Learning in Intelligent Information Retrieval

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

Information Retrieval and the Statistics of Large Data Sets

David Lewis, D. Lewis, 1996 .

Active by Accident: Relevance Feedback in Information Retrieval

David Lewis, D. Lewis, 1995 .

Term clustering of syntactic phrases

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

TREC 2006 Legal Track Overview

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

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 .

The use of phrases and structured queries in information retrieval

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

Building a test collection for complex document information processing

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

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

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

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

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

Representation Quality in Text Classification: An Introduction and Experiment

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

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.

Retrieval and Richness when Querying by Document

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

Evaluation of information retrieval for E-discovery

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

Sparse Bayesian Classifiers for Text Categorization

D. Madigan, D. Lewis, S. Eyheramendy, 2003 .

Fax: An Alternative to SGML

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

Language‐oriented information retrieval

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

Approximating Matrix Multiplicationfor Pattern Recognition

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

On the Naive Bayes Model for Text Categorization

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

Certifying One-Phase Technology-Assisted Reviews

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

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

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

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

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

TAR on Social Media: A Framework for Online Content Moderation

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

Guest Editorial - Special Issue on Text Categorization

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

A Sequential Algorithm for Training Text Classifiers

D. Lewis, W. Gale, 1994, cmp-lg/9407020.

The TREC-5 Filtering Track

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

AT&T at TREC-7

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

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.

Automatic classification of Web queries using very large unlabeled query logs

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

Automatic web query classification using labeled and unlabeled training data

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

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.

Challenges in machine learning for text classification

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

Information retrieval for e-discovery

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