Topic Models and Metadata for Visualizing Text Corpora

Justin Snyder, Rebecca Knowles, Mark Dredze, Matthew R. Gormley, Travis Wolfe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Effectively exploring and analyzing large text corpora requires visualizations that provide a high level summary. Past work has relied on faceted browsing of document metadata or on natural language processing of document text. In this paper, we present a new web-based tool that integrates topics learned from an unsupervised topic model in a faceted browsing experience. The user can manage topics, filter documents by topic and summarize views with metadata and topic graphs. We report a user study of the usefulness of topics in our tool.

Original languageEnglish (US)
Title of host publication2013 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Subtitle of host publicationHuman Language Technologies, NAACL-HLT 2013 - Demonstration Session
EditorsChris Dyer, Derrick Higgins
PublisherAssociation for Computational Linguistics (ACL)
Pages5-9
Number of pages5
ISBN (Electronic)9781937284473
StatePublished - 2013
Event2013 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2013 - Demonstration Session - Atlanta, United States
Duration: Jun 10 2013Jun 12 2013

Publication series

Name2013 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2013 - Demonstration Session

Conference

Conference2013 Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2013 - Demonstration Session
Country/TerritoryUnited States
CityAtlanta
Period6/10/136/12/13

ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Science Applications
  • Linguistics and Language

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