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Event recognition based on time series characteristics

  • Harbin Institute of Technology

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

Abstract

Event recognition and temporal information analysis are important subtasks in information extraction (IE). In this paper, event recognition based on time series characteristics is proposed. In the pipeline of event recognition, trigger word table is extracted from training corpus and extended based on the field and thesaurus, which is regarded as a priori knowledge. Then event recognition is carried out using trigger words and support vector machine (SVM). Temporal expressions are normalized primarily when recognizing event time. Especially, keywords on time and their priorities are taken into account. Finally, events are sorted by time series characteristics. The results show that methods proposed in this paper are valid and effective.

Original languageEnglish
Title of host publicationProceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011
Pages1807-1811
Number of pages5
DOIs
StatePublished - 2011
Event2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11 - Shanghai, China
Duration: 26 Jul 201128 Jul 2011

Publication series

NameProceedings - 2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011
Volume3

Conference

Conference2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11
Country/TerritoryChina
CityShanghai
Period26/07/1128/07/11

Keywords

  • event recognition
  • information extraction
  • time recognition
  • time series characteristic

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