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Ranking entities on the basis of users’ opinions

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Abstract

Online opinions are one of the most important sources of information on which users base their purchasing decisions. Unfortunately, the large quantity of opinions makes it difficult for an individual to consume in a reasonable amount of time. Unlike standard information retrieval problems, the task here is to retrieve entities whose relevance is dependent upon other people’s opinions regarding the entities and how well those sentiments match the user’s own preferences. We propose novel techniques that incorporate aspect subjectivity measures into weighting the relevance of opinions of entities based on a user’s query keywords. We calculate these weights using sentiment polarity of terms found proximity close to keywords in opinion text. We have implemented our techniques, and we show that these improve the overall effectiveness of the baseline retrieval task. Our results indicate that on entities with long opinions our techniques can perform as good as state-of-the-art query expansion approaches.

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Notes

  1. An aspect is a particular part or feature of an entity.

  2. Opinions are obtained from http://www.tripadvisor.com

  3. http://www.tripadvisor.com

  4. http://www.Edmunds.com

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Authors and Affiliations

  1. Department of Computer Science, Bahria University, Islamabad, Pakistan

    Shariq Bashir

  2. Faculty of Computing - Department of Computer Science, M. A. Jinnah University, Islamabad, Pakistan

    Shariq Bashir

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  1. Shariq Bashir
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Correspondence to Shariq Bashir.

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Bashir, S. Ranking entities on the basis of users’ opinions. Multimed Tools Appl 76, 59–81 (2017). https://doi.org/10.1007/s11042-015-3022-6

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