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Product-oriented review summarization and scoring

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Abstract

Currently, there are many online review web sites where consumers can freely write comments about different kinds of products and services. These comments are quite useful for other potential consumers. However, the number of online comments is often large and the number continues to grow as more and more consumers contribute. In addition, one comment may mention more than one product and contain opinions about different products, mentioning something good and something bad. However, they share only a single overall score. Therefore, it is not easy to know the quality of an individual product from these comments.

This paper presents a novel approach to generate review summaries including scores and description snippets with respect to each individual product. From the large number of comments, we first extract the context (snippet) that includes a description of the products and choose those snippets that express consumer opinions on them. We then propose several methods to predict the rating (from 1 to 5 stars) of the snippets. Finally, we derive a generic framework for generating summaries from the snippets. We design a new snippet selection algorithm to ensure that the returned results preserve the opinion-aspect statistical properties and attribute-aspect coverage based on a standard seat allocation algorithm. Through experimentswe demonstrate empirically that our methods are effective. We also quantitatively evaluate each step of our approach.

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Author information

Authors and Affiliations

  1. Institute of Data Science and Engineering, Shanghai Key Laboratory of Trustworthy Computing, East China Normal University, Shanghai, 200062, China

    Rong Zhang, Wenzhe Yu, Xiaofeng He & Aoying Zhou

  2. School of Computer Science, Fudan University, Shanghai, 200433, China

    Chaofeng Sha

Authors
  1. Rong Zhang
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  2. Wenzhe Yu
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  3. Chaofeng Sha
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  4. Xiaofeng He
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  5. Aoying Zhou
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Corresponding author

Correspondence to Xiaofeng He.

Additional information

Rong Zhang received her BS degree in computer science from Northeastern University, China in 2001 and PhD degree in computer science from Fudan University in 2007, China. She joined East China Normal University (ECNU) since 2011 and is currently an associated professor in this university. From 2007 to 2010, she worked as an expert researcher in NICT, Japan. Her current research interests include knowledge management and distributed data management.

Wenzhe Yu is currently pursuing her MS degree in Center for Cloud Computing and Big Data (CCCBD), Institute of Software Engineering, East China Normal University (ECNU), China. Before that, she received her BS degree in software engineering from ECNU in 2012. Her current research interests include Web data mining and data integration.

Chaofeng Sha is an assistant professor in Fudan University. He received the BS degree in applied mathematics in 1998 from Xidian University, China, the MS degree in 2001 and the PhD degree in 2009 from Fudan University, China, both in computer science. Since 2001, he has been in the School of Computer Science at Fudan University. His work is in the area of data mining and data management.

Xiaofeng He is a professor at Institute of Software Engineering, East China normal University (ECNU), China. He obtained his PhD degree from the Pennsylvania State University, USA. Xiaofeng’s research interests include machine learning, data mining, information retrieval. Prior to joining ECNU, Xiaofeng worked with Microsoft, Yahoo and Lawrence Berkeley National Laboratory.

Aoying Zhou is a professor in computer science at East China Normal University (ECNU), China, where he is heading the Institute ofMassive Computing. Before joining ECNU in 2008, Aoying worked for Fudan University at the Computer Science Department for 15 years. He is the winner of the National Science Fund for Distinguished Young Scholars supported by the National Natural Science Foundation of China and the professorship appointment under Changjiang Scholars Program of Ministry of Education. He is now acting as a vicedirector of ACM SIGMOD China and Database Technology Committee of China Computer Federation. He is serving as a member of the editorial boards VLDB Journal, www Journal, etc. His research interests include data management, memory cluster computing, big data benchmarking and performance optimization.

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Zhang, R., Yu, W., Sha, C. et al. Product-oriented review summarization and scoring. Front. Comput. Sci. 9, 210–223 (2015). https://doi.org/10.1007/s11704-014-3492-0

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  • DOI: https://doi.org/10.1007/s11704-014-3492-0

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