Product review summarization from a deeper perspective

Authors:
Duy Khang Ly;Kazunari Sugiyama;Ziheng Lin;Min-Yen Kan
Affiliations:
National University of Singapore, Singapore, Singapore;National University of Singapore, Singapore, Singapore;National University of Singapore, Singapore, Singapore;National University of Singapore, Singapore, Singapore
Venue:
Proceedings of the 11th annual international ACM/IEEE joint conference on Digital libraries
Year:
2011

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Abstract

With product reviews growing in depth and becoming more numerous, it is growing challenge to acquire a comprehensive understanding of their contents, for both customers and product manufacturers. We built a system that automatically summarizes a large collection of product reviews to generate a concise summary. Importantly, our system not only extracts the review sentiments but also the underlying justification for their opinion. We solve this problem through a novel application of clustering and validate our approach through an empirical study, obtaining good performance as judged by F-measure (the harmonic mean of purity and inverse purity).