Pattern-based rule disambiguation

Jie Zheng, Gang Cheng, Shoushan Li, Fang Kong, Chu-ren Huang, Guodong Zhou

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

The biggest challenges to rules-based approaches to Natural Language Processing (NLP) are the resources required to do an exhaustive search for rule-matching, and the decision to select the optimal rule when there are multiple possible matches. In this paper, we propose a novel approach named pattern-based rule disambiguation (PRD) to face these challenges. PRD helps to determine which rule is activated by a pattern when the pattern activates more than one rule. To tackle this task, we first collect and annotate the samples following the same pattern, but activating different rules; Then, we leverage the corpus to train a statistic classifier to disambiguate the pattern. This new approach is applied to the task of emotion cause detection, adopting a linguistic rule-drive paradigm which was the only one available for this task. The experimental results demonstrated the effectiveness of our PRD approach and offered a promising solution of the resolution of multiple-matched rules challenge for future NLP tasks.
Original languageEnglish
Title of host publication2015 12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015
PublisherIEEE
Pages1444-1449
Number of pages6
ISBN (Electronic)9781467376822
DOIs
Publication statusPublished - 13 Jan 2016
Event12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015 - Zhangjiajie, China
Duration: 15 Aug 201517 Aug 2015

Conference

Conference12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015
CountryChina
CityZhangjiajie
Period15/08/1517/08/15

Keywords

  • Natural Language Processing
  • Pattern-based approach
  • Rules-based approaches

ASJC Scopus subject areas

  • Discrete Mathematics and Combinatorics
  • Modelling and Simulation
  • Computer Networks and Communications
  • Control and Systems Engineering

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