Use of multi-lexicons to analyse semantic features for summarization of touring reviews

Hei Chia Wang, Yu Hung Chiang, Yi Feng Sun

研究成果: Article同行評審


Purpose: This paper aims to improve a sentiment analysis (SA) system to help users (i.e. customers or hotel managers) understand hotel evaluations. There are three main purposes in this paper: designing an unsupervised method for extracting online Chinese features and opinion pairs, distinguishing different intensities of polarity in opinion words and examining the changes in polarity in the time series. Design/methodology/approach: In this paper, a review analysis system is proposed to automatically capture feature opinions experienced by other tourists presented in the review documents. In the system, a feature-level SA is designed to determine the polarity of these features. Moreover, an unsupervised method using a part-of-speech pattern clarification query and multi-lexicons SA to summarize all Chinese reviews is adopted. Findings: The authors expect this method to help travellers search for what they want and make decisions more efficiently. The experimental results show the F-measure of the proposed method to be 0.628. It thus outperforms the methods used in previous studies. Originality/value: The study is useful for travellers who want to quickly retrieve and summarize helpful information from the pool of messy hotel reviews. Meanwhile, the system will assist hotel managers to comprehensively understand service qualities with which guests are satisfied or dissatisfied.

頁(從 - 到)185-206
期刊Electronic Library
出版狀態Published - 2019 五月 15

All Science Journal Classification (ASJC) codes

  • 電腦科學應用
  • 圖書館與資訊科學


深入研究「Use of multi-lexicons to analyse semantic features for summarization of touring reviews」主題。共同形成了獨特的指紋。