STARLET: Multi-document Summarization of Service and Product Reviews with Balanced Rating Distributions
Data Mining Workshops（2011）
摘要
Reviews about products and services are abundantly available online. However, selecting information relevant to a potential buyer involves a significant amount of time reading user's reviews and weeding out comments unrelated to the important aspects of the reviewed entity. In this work, we present STARLET, a novel approach to multi-document summarization for evaluative text that considers the rating distribution as summarization feature to consistently preserve the overall opinion distribution expressed in the original reviews. We demonstrate how this method improves traditional summarization techniques and leads to more readable summaries.
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关键词
product reviews,original review,balanced rating distributions,abundantly available online,traditional summarization technique,important aspect,rating distribution,novel approach,multi-document summarization,evaluative text,overall opinion distribution,summarization feature,potential buyer,text analysis,multi document summarization,information retrieval,summarization
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