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EXPRS: An extended pagerank method for product feature extraction from online consumer reviews

Information & ManagementPublished 7 March 2015
Zhijun Yan, Meiming Xing, Dongsong Zhang, Baizhang Ma
Citations124
SJR quartileQ1
SJR score2.92
SNIP2.74

TL;DR

A novel method called EXPRS is proposed that integrates an extended PageRank algorithm, synonym expansion, and implicit feature inference to extract product features automatically to reduce product uncertainty before making a purchase decision.

Abstract

Online consumer product reviews are a main source for consumers to obtain product information and reduce product uncertainty before making a purchase decision. However, the great volume of product reviews makes it tedious and ineffective for consumers to peruse individual reviews one by one and search for comments on specific product features of their interest. This study proposes a novel method called EXPRS that integrates an extended PageRank algorithm, synonym expansion, and implicit feature inference to extract product features automatically. The empirical evaluation using consumer reviews on three different products shows that EXPRS is more effective than two baseline methods.

Keywords

Computer ScienceSocial Sciences