Authors:
Yoshimi Suzuki
and
Fumiyo Fukumoto
Affiliation:
University of Yamanashi, Japan
Keyword(s):
Text Segmentation, Reviews, Thesaurus, Wikipedia.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Data Engineering
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Pattern Recognition
;
Symbolic Systems
Abstract:
Recently, we can refer to user reviews in the shopping or hotel reservation sites. However, with the exponential
growth of information of the Internet, it is becoming increasingly difficult for a user to read and understand all
the materials from a large-scale reviews that is potentially of interest. In this paper, we propose a method for
review texts segmentation by guest’s criteria, such as service, location and facilities. Our system firstly extracts
words which represent criteria from hotel review texts. We focused on topic markers such as ``ha'' in Japanese
to extract guest’s criteria. The extracted words are classified into classes with similar words. The classification
is proceeded by using Japanese WordNet. Then, for each hotel, each text with all of the guest reviews is
segmented into word sequence by using criteria classes. Review text segmentation is difficult because of short
text. We thus used Japanese WordNet, extracted similar word pairs, and indexes of Wikipedia. We p
erformed
text segmentation of hotel review. The results showed the effectiveness of our method and indicated that it can
be used for review summarization by guest’s criteria.
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