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ThinkMind // International Journal On Advances in Internet Technology, volume 13, numbers 1 and 2, 2020 // View article inttech_v13_n12_2020_1


Identifying and Analyzing Obscure Venues Using Obscure Words in User-provided Reviews

Authors:
Masaharu Hirota
Jhih-Yu Lin
Masaki Endo
Hiroshi Ishikawa

Keywords: Tourism information; Text classification; Support Vector Machine; Review Analysis.

Abstract:
When sightseeing, many people visit different places such as restaurants, hotels, and tourist spots. Some of these venues, while worthwhile, are considered obscure, secret, not well-known, or having little popularity. Their extraction and recommendation are vital to improving the satisfaction of tourists. This research proposes a method for discovering obscure venues using classifiers for identifying reviews, including obscure impressions. To achieve this goal, in this research, a model was developed to classify venues as obscure or not obscure using reviews with language indicating their obscurity. In addition, we compare various methods for generating feature vectors and the models for classification. This research also analyzes the differences among venues perceived by reviewers as being obscure. We demonstrate the performance of the proposed approach by indicating that the posting destination of obscure reviews differs for each user.

Pages: 1 to 10

Copyright: Copyright (c) to authors, 2020. Used with permission.

Publication date: June 30, 2020

Published in: journal

ISSN: 1942-2652

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