MultiGranCNN: An architecture for general matching of text chunks on multiple levels of granularity

Wenpeng Yin, Hinrich Schutze

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

68 Scopus citations

Abstract

We present MultiGranCNN, a general deep learning architecture for matching text chunks. MultiGranCNN supports multigranular comparability of representations: shorter sequences in one chunk can be directly compared to longer sequences in the other chunk. Multi-GranCNN also contains a flexible and modularized match feature component that is easily adaptable to different types of chunk matching. We demonstrate stateof-The-Art performance of MultiGranCNN on clause coherence and paraphrase identification tasks.

Original languageEnglish (US)
Title of host publicationACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages63-73
Number of pages11
ISBN (Electronic)9781941643723
DOIs
StatePublished - 2015
Event53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015 - Beijing, China
Duration: Jul 26 2015Jul 31 2015

Publication series

NameACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference
Volume1

Other

Other53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015
Country/TerritoryChina
CityBeijing
Period7/26/157/31/15

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Software

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