META: A unified toolkit for text retrieval and analysis

Sean Massung, Chase Geigle, Chengxiang Zhai

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

Abstract

META is developed to unite machine learning, information retrieval, and natural language processing in one easy-to-use toolkit. Its focus on indexing allows it to perform well on large datasets, supporting online classification and other out-of-core algorithms. META's liberal open source license encourages contributions, and its extensive online documentation, forum, and tutorials make this process straightforward. We run experiments and show META's performance is competitive with or better than existing software.

Original languageEnglish (US)
Title of host publication54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - System Demonstrations
PublisherAssociation for Computational Linguistics (ACL)
Pages91-96
Number of pages6
ISBN (Electronic)9781510827615
DOIs
StatePublished - 2016
Event54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - Berlin, Germany
Duration: Aug 7 2016Aug 12 2016

Publication series

Name54th Annual Meeting of the Association for Computational Linguistics, ACL 2016 - System Demonstrations

Other

Other54th Annual Meeting of the Association for Computational Linguistics, ACL 2016
CountryGermany
CityBerlin
Period8/7/168/12/16

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence
  • Linguistics and Language
  • Language and Linguistics

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