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Volume 26 Issue 4
July  2011
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Feng Jin, Min-Lie Huang, Xiao-Yan Zhu. Guided Structure-Aware Review Summarization[J]. Journal of Computer Science and Technology, 2011, 26(4): 676-684. DOI: 10.1007/s11390-011-1167-y
Citation: Feng Jin, Min-Lie Huang, Xiao-Yan Zhu. Guided Structure-Aware Review Summarization[J]. Journal of Computer Science and Technology, 2011, 26(4): 676-684. DOI: 10.1007/s11390-011-1167-y
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Guided Structure-Aware Review Summarization

  • State Key Laboratory of Intelligent Technology and Systems, Tsinghua National Laboratory for Information Science and Technology, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China

Funds: This work was partly supported by the National Natural Science Foundation of China under Grant Nos. 60973104 and 60803075, and with the aid of a grant from the International Development Research Center, Ottawa, Canada IRCI Project.
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  • Received Date: November 02, 2010
  • Revised Date: June 09, 2011
  • Published Date: July 04, 2011
    Abstract
  • Although the goal of traditional text summarization is to generate summaries with diverse information, most of those applications have no explicit definition of the information structure. Thus, it is difficult to generate truly structure-aware summaries because the information structure to guide summarization is unclear. In this paper, we present a novel framework to generate guided summaries for product reviews. The guided summary has an explicitly defined structure which comes from the important aspects of products. The proposed framework attempts to maximize expected aspect satisfaction during summary generation. The importance of an aspect to a generated summary is modeled using Labeled Latent Dirichlet Allocation. Empirical experimental results on consumer reviews of cars show the effectiveness of our method.
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    • References (25)
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