JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2017, Vol. 52 ›› Issue (7): 44-51.doi: 10.6040/j.issn.1671-9352.1.2016.PC6

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A semi-supervised spam review classification method based on heuristic rules

ZHANG Peng1, WANG Su-ge1,2*, LI De-yu1,2, WANG Jie1   

  1. 1. School of Computer and Information Technology SXU, Taiyuan 030006, Shanxi, China;
    2. Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education, Taiyuan 030006, Shanxi, China
  • Received:2016-11-25 Online:2017-07-20 Published:2017-07-07

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Abstract: Nowadays the Internet has affected everyones lives. E-commercial websites such as online-shopping, group purchases, and online consumption have already become most popular consumption patterns. Almost every e-commercial websites enable and encourage their customers to write a review on their products and services. These customers generative reviews are valuable to potential consumers and merchants, which leads a situation that spam reviews are added into the e-commercial websites manually on purpose of promoting products or damaging reputation of other merchants. Based on this application background, the spam reviews detection research aims to get rid of spam reviews and to make full use of normal customer reviews. This paper focus on COAE2015-TASK4, which sets up a public task of spam review detection. We proposed a semi-supervised spam review classification method based on heuristic rules using the corpora resources provided by the COAE2015-TASK4. Experiments showed our method can effectively detect spam reviews and keep a high classification accuracy of normal customer reviews.

Key words: spam review classification, heuristic rules, semi-supervised learning

CLC Number: 

  • TP391
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