TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 15, No 1: March 2017

Automatic Summarization in Chinese Product Reviews

Li zhen Liu (Capital Normal University)
Wan di Du (Capital Normal University)
Han shi Wang (Capital Normal University)
Wei Song (Capital Normal University)



Article Info

Publish Date
01 Mar 2017

Abstract

With the increasing number of online comments, it was hard for buyers to find useful information in a short time so it made sense to do research on automatic summarization which fundamental work was focused on product reviews mining. Previous studies mainly focused on explicit features extraction whereas often ignored implicit features which hadn't been stated clearly but containing necessary information for analyzing comments. So how to quickly and accurately mine features from web reviews had important significance for summarization technology. In this paper, explicit features and “feature-opinion” pairs in the explicit sentences were extracted by Conditional Random Field and implicit product features were recognized by a bipartite graph model based on random walk algorithm. Then incorporating features and corresponding opinions into a structured text and the abstract was generated based on the extraction results. The experiment results demonstrated the proposed methods outpreferred baselines.

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Journal Info

Abbrev

TELKOMNIKA

Publisher

Subject

Computer Science & IT

Description

Submitted papers are evaluated by anonymous referees by single blind peer review for contribution, originality, relevance, and presentation. The Editor shall inform you of the results of the review as soon as possible, hopefully in 10 weeks. Please notice that because of the great number of ...