Generating comparative summaries of contradictory opinions in text

Kim, Hyun Duk

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https://hdl.handle.net/2142/14680 Copy

Description

Title

Generating comparative summaries of contradictory opinions in text

Author(s)

Kim, Hyun Duk

Issue Date

2010-01-06T16:21:09Z

Director of Research (if dissertation) or Advisor (if thesis)

Zhai, ChengXiang

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

M.S.

Degree Level

Thesis

Keyword(s)

• Opinion Summarization
• Contrastive Opinion Summary
• Text mining

Abstract

This thesis presents a study of a novel summarization problem called contrastive opinion summarization (COS). Given two sets of positively and negatively opinionated sentences which are often the output of an existing opinion summarizer, COS aims to extract comparable sentences from each set of opinions and generate a comparative summary containing a set of contrastive sentence pairs. We formally formulate the problem as an optimization problem and propose two general methods for generating a comparative summary using the framework, both of which rely on measuring the content similarity and contrastive similarity of two sentences. We study several strategies to compute these two similarities. We also create a test data set for evaluating such a novel summarization problem. Experiment results on this test set show that the proposed methods are effective for generating comparative summaries of contradictory opinions. In addition, we implemented two demo systems which show the usefulness of the algorithm intuitively.

Graduation Semester

2009-12

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http://hdl.handle.net/2142/14680

Copyright and License Information

Copyright 2009 by Hyun Duk Kim. All rights reserved.

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