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標題A template approach for summarizing restaurant reviews

學年110

學期1

出版（發表）日期2021/08/09

作品名稱A template approach for summarizing restaurant reviews

作品名稱（其他語言）

著者Yenliang Chen; Chialing Chang; Jeryeu Gan

單位

出版者

著錄名稱、卷期、頁數IEEE ACCESS 9, p.115548-115562

摘要In the era of rapid development of social networks, user reviews of restaurant review websites have grown rapidly. In order to allow users to quickly grasp the key points of review information on review sites, this paper provides an abstractive multi-text summary method that can automatically generate template-based review summaries based on predefined topics and sentiments. In particular, for each predefined topic and each type of sentiment (positive or negative), this study uses the TextRank algorithm to find the most representative sentences to form a summary. This method allows users to quickly grasp the positive and negative opinions of each important aspect of the restaurant. The previous research on generating abstracts from reviews either did not generate abstracts based on topics, or they were based on topics generated by random models. However, the latter method cannot guarantee that the topics generated by the random model are really the topics that the user needs. For a restaurant review, some topics are indispensable. In order to ensure that abstracts can be generated for these essential topics, our method predefines the topics that must be generated, and then generates abstracts for these topics. In the evaluation, this study compared the template method with the Refresh and Gensim systems based on criteria such as informativeness, clarity, usefulness and likes. The results show that the method proposed in this paper is superior to the other two summary methods.

關鍵字Restaurant reviews; sentiment analysis; summarization; template;, TextRank

語言英文

ISSN2169-3536

期刊性質國外

收錄於,SCI,其他

產學合作

通訊作者Chia-Ling Chang

審稿制度是

國別美國

公開徵稿

出版型式電子版

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