Skip to main navigation Skip to search Skip to main content

A key component extraction method based on HMM and dependency parsing

  • Jianchu Kang*
  • , Songsong Pang
  • , Jian Dong
  • , Bowen Du
  • , Jian Huang
  • *Corresponding author for this work
  • Beihang University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Increasing attention has been paid for POI (Point of Interest) data query for travel information service. The correct extraction of key components in question is crucial for improving the accuracy of query results. The paper proposes a key component extraction method based on HMM (Hidden Markov Model) and dependency parsing. Firstly, the sentence pattern classifier is established by HMM. And then, questions are classified by classifier. Finally, combination of sentence pattern's structure, the four key components are extracted by dependency parsing. The results show that the F1-Measure is 0.83, which well proves the effectiveness of the method.

Original languageEnglish
Title of host publication2012 6th International Conference on Application of Information and Communication Technologies, AICT 2012 - Proceedings
DOIs
StatePublished - 2012
Event2012 6th International Conference on Application of Information and Communication Technologies, AICT 2012 - Tbilisi, Georgia
Duration: 17 Oct 201219 Oct 2012

Publication series

Name2012 6th International Conference on Application of Information and Communication Technologies, AICT 2012 - Proceedings

Conference

Conference2012 6th International Conference on Application of Information and Communication Technologies, AICT 2012
Country/TerritoryGeorgia
CityTbilisi
Period17/10/1219/10/12

Keywords

  • HMM
  • dependency parsing
  • key component
  • segmentation
  • sentence pattern

Fingerprint

Dive into the research topics of 'A key component extraction method based on HMM and dependency parsing'. Together they form a unique fingerprint.

Cite this