標題: Automatic Restaurant Information and Keyword Extraction by Mining Blog Data for Chinese Restaurant Search
作者: Chou, Chien-Li
Tsai, Min-Ho
Chao, Chien-Ho
Lin, Hsiao-Jung
Chen, Hua-Tsung
Lee, Suh-Yin
Ho, Chien-Peng
資訊工程學系
Department of Computer Science
關鍵字: Information retrieval;Opinion mining;TFIDF;Food and restaurants;Restaurant search
公開日期: 1-一月-2014
摘要: Restaurant search and recommendation system is a very popular service in many countries. In those systems, most of the restaurant information such as restaurant name, address, phone number, and introduction are collected manually. In this paper, we propose a restaurant information extraction method which can automatically extract restaurant information from online reviews of restaurants in blogs. In addition, by calculating TFIDFs of words in blog posts, the hot keywords can be discovered and ranked. For restaurant search, users are allowed to search by keywords, areas, and/or extracted hot keywords. The experimental results show that the proposed method can achieve over 90 % average accuracy of hot keyword extraction and about 95 % mean average precision for restaurant search. In user study, the fact that the proposed system is more useful than Google search in restaurant search is presented.
URI: http://dx.doi.org/10.1007/978-3-319-13186-3_62
http://hdl.handle.net/11536/125149
ISBN: 978-3-319-13186-3; 978-3-319-13185-6
ISSN: 0302-9743
DOI: 10.1007/978-3-319-13186-3_62
期刊: TRENDS AND APPLICATIONS IN KNOWLEDGE DISCOVERY AND DATA MINING
Volume: 8643
起始頁: 700
結束頁: 711
顯示於類別:會議論文


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  1. 000354705300062.pdf