Designing Ranking System for Chinese Product Search Engine Based on Customer Reviews

نویسندگان

  • Samira Chaabna
  • Hu Wang
  • Mohammed Lutf
چکیده

With the spread of e-commerce platforms, it becomes extremely difficult for the costumer to choose the right product from a large number of products, and different sellers based only on his/her own experience, product picture and meta-data. Customer’s reviews present a rich source of information that have an enormous impact on the purchasing decision of the potential consumers, but reading all of the available reviews is a hard task and time consuming. Thus, the automated mining of these reviews and extract product features in order to generate a raking system present a valuable and useful tool for consumers to make well-versed decision. In this paper, we propose a product search ranking mechanism based on costumers reviews written in Chinese language. We score each product using the features extracted from the reviews. Also, a ranking function has been developed. The proposed research evaluated using customer reviews of two famous brands of mobile phones: Apple and Samsung from taobao.com. The evaluation shows a promising result compared to the existing

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تاریخ انتشار 2014