STARLET: Multi-document Summarization of Service and Product Reviews with Balanced Rating Distributions

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.