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2011 | OriginalPaper | Chapter

Mining Popular Menu Items of a Restaurant from Web Reviews

Authors : Yeong Hyeon Gu, Seong Joon Yoo

Published in: Web Information Systems and Mining

Publisher: Springer Berlin Heidelberg

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We propose a novel method to mine popular menu items from online reviews. In order to extract popular menu items, a crawler that uses the wrapper on search web sites was used to collect online reviews, restaurant names, and menu items. Then, unnecessary posts were removed by using the patterns. Also, post frequency was used to find the most frequently appearing menu items from online reviews in order to select the most popular menu items. In the result, the total average accuracy was 0.900.

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previous chapter A Rapid Method to Extract Multiword Expressions with Statistic Measures and Linguistic Rules
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Metadata
Title
Mining Popular Menu Items of a Restaurant from Web Reviews
Authors
Yeong Hyeon Gu
Seong Joon Yoo
Copyright Year
2011
Publisher
Springer Berlin Heidelberg
Book
Web Information Systems and Mining

Print ISBN: 978-3-642-23981-6

Electronic ISBN: 978-3-642-23982-3

Copyright Year: 2011

DOI
https://doi.org/10.1007/978-3-642-23982-3_31

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