Exploiting structured ontology to organize scattered online opinions

  • Authors:
  • Yue Lu;Huizhong Duan;Hongning Wang;ChengXiang Zhai

  • Affiliations:
  • University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign

  • Venue:
  • COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics
  • Year:
  • 2010

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Abstract

We study the problem of integrating scattered online opinions. For this purpose, we propose to exploit structured ontology to obtain well-formed relevant aspects to a topic and use them to organize scattered opinions to generate a structured summary. Particularly, we focus on two main challenges in implementing this idea, (1) how to select the most useful aspects from a large number of aspects in the ontology and (2) how to order the selected aspects to optimize the readability of the structured summary. We propose and explore several methods for solving these challenges. Experimental results on two different data sets (US Presidents and Digital Cameras) show that the proposed methods are effective for selecting aspects that can represent the major opinions and for generating coherent ordering of aspects.