Ranking explanatory sentences for opinion summarization

Hyun Duk Kim, Malu G. Castellanos, Meichun Hsu, Cheng Xiang Zhai, Umeshwar Dayal, Riddhiman Ghosh

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

Abstract

We introduce a novel sentence ranking problem called explanatory sentence extraction (ESE) which aims to rank sentences in opinionated text based on their usefulness for helping users understand the detailed reasons of sentiments (i.e., "explanatoriness"). We propose and study several general methods for scoring the explanatoriness of a sentence. We create new data sets and propose a new measure for evaluation. Experiment results show that the proposed methods are effective, outperforming a state of the art sentence ranking method for standard text summarization.

Original languageEnglish (US)
Title of host publicationSIGIR 2013 - Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval
Pages1069-1072
Number of pages4
DOIs
StatePublished - 2013
Event36th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2013 - Dublin, Ireland
Duration: Jul 28 2013Aug 1 2013

Publication series

NameSIGIR 2013 - Proceedings of the 36th International ACM SIGIR Conference on Research and Development in Information Retrieval

Other

Other36th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2013
CountryIreland
CityDublin
Period7/28/138/1/13

Keywords

  • Explanatoriness scoring
  • Explanatory sentence ranking
  • Opinion summarization

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Information Systems

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