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Value-Oriented Ranking of Online Reviews Based on Reviewer-Influenced Graph

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Database Systems for Advanced Applications (DASFAA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11448))

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Abstract

To mitigate the uncertainty of online purchases, people rely on reviews written by customers who already bought the product to make their decisions. The key challenge in this situation is how to identify the most helpful reviews among a large number of candidate reviews with different quality. Existing work normally employs diversified text and sentiment analysis algorithms to analyze the helpfulness of reviews. Voting on reviews is another popular valuation way adopted by many websites, which also has difficulties to reflect the real helpfulness of the reviews due to the problem of data sparseness. In this paper, a reviewer-influenced graph model is constructed based on the reviewers’ historical reviews and voting information to measure the influence of reviewers’ quality on the helpfulness of reviews. Experimental results with actual review data from Amazon.com demonstrate the effectiveness of our approach.

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Notes

  1. 1.

    http://snap.stanford.edu/data/web-Amazon.html.

  2. 2.

    https://www.amazon.cn.

References

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Acknowledgements

The research work was supported by the NSFC (91846205, 61572295), National Key R&D Program (2017YFB1400102, 2016YFB1000602), SDNSFC (No. ZR2017ZB0420, No. ZR2018MF014, No. ZR2017MF065), and Shandong Major scientific and technological innovation projects (2018YFJH0506).

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Authors and Affiliations

  1. Shandong University, Jinan, China

    Yiming Cao, Lizhen Cui & Wei He

Authors
  1. Yiming Cao
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  2. Lizhen Cui
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  3. Wei He
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Corresponding author

Correspondence to Lizhen Cui .

Editor information

Editors and Affiliations

  1. Tsinghua University, Beijing, China

    Guoliang Li

  2. Duke University, Durham, NC, USA

    Jun Yang

  3. University of Porto, Porto, Portugal

    Joao Gama

  4. Chiang Mai University, Chiang Mai, Thailand

    Juggapong Natwichai

  5. Beihang University, Beijing, China

    Yongxin Tong

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Cao, Y., Cui, L., He, W. (2019). Value-Oriented Ranking of Online Reviews Based on Reviewer-Influenced Graph. In: Li, G., Yang, J., Gama, J., Natwichai, J., Tong, Y. (eds) Database Systems for Advanced Applications. DASFAA 2019. Lecture Notes in Computer Science(), vol 11448. Springer, Cham. https://doi.org/10.1007/978-3-030-18590-9_24

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  • DOI: https://doi.org/10.1007/978-3-030-18590-9_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-18589-3

  • Online ISBN: 978-3-030-18590-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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