Opinion Target Extraction Using a Shallow Semantic Parsing Framework

Authors

  • Shoushan Li Soochow University
  • Rongyang Wang Soochow University
  • Guodong Zhou Soochow University

DOI:

https://doi.org/10.1609/aaai.v26i1.8346

Keywords:

Opinion Mining, Sentiment Analysis, Opinon Target Extraction

Abstract

In this paper, we present a simplified shallow semantic parsing approach to extracting opinion targets. This is done by formulating opinion target extraction (OTE) as a shallow semantic parsing problem with the opinion expression as the predicate and the corresponding targets as its arguments. In principle, our parsing approach to OTE differs from the state-of-the-art sequence labeling one in two aspects. First, we model OTE from parse tree level, where abundant structured syntactic information is available for use, instead of word sequence level, where only lexical information is available. Second, we focus on determining whether a constituent, rather than a word, is an opinion target or not, via a simplified shallow semantic parsing framework. Evaluation on two datasets shows that structured syntactic information plays a critical role in capturing the domination relationship between an opinion expression and its targets. It also shows that our parsing approach much outperforms the state-of-the-art sequence labeling one.

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Published

2021-09-20

How to Cite

Li, S., Wang, R., & Zhou, G. (2021). Opinion Target Extraction Using a Shallow Semantic Parsing Framework. Proceedings of the AAAI Conference on Artificial Intelligence, 26(1), 1671-1677. https://doi.org/10.1609/aaai.v26i1.8346

Issue

Section

AAAI Technical Track: Natural Language Processing