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Authors: Fumiyo Fukumoto ; Chihiro Motegi and Suguru Matsuyoshi

Affiliation: Univ. of Yamanashi, Japan

Keyword(s): Collaborative Filtering, Recommendation System.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Collaborative Filtering ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Symbolic Systems ; User Profiling and Recommender Systems

Abstract: Collaborative filtering (CF) is identifies the preference of a consumer/guest for a new product/hotel by using only the information collected from other consumers/guests with similar products/hotels in the database. It has been widely used as filtering techniques because it is not necessary to apply more complicated content analysis. However, it is difficult to take users criteria into account. Some of the item-based collaborative filtering take users preferences or votes for the item into account. One problem of these approaches is a data sparseness problem that the user preferences were not tagged all the items. In this paper, we propose a new recommender method incorporating the results of sentiment analysis of guest reviews. The results obtained by our method using real-world data sets demonstrate a performance improvement compared to the four baselines.

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Paper citation in several formats:
Fukumoto, F.; Motegi, C. and Matsuyoshi, S. (2012). Collaborative Filtering based on Sentiment Analysis of Guest Reviews for Hotel Recommendation. In Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2012) - KDIR; ISBN 978-989-8565-29-7; ISSN 2184-3228, SciTePress, pages 193-198. DOI: 10.5220/0004130901930198

@conference{kdir12,
author={Fumiyo Fukumoto. and Chihiro Motegi. and Suguru Matsuyoshi.},
title={Collaborative Filtering based on Sentiment Analysis of Guest Reviews for Hotel Recommendation},
booktitle={Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2012) - KDIR},
year={2012},
pages={193-198},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004130901930198},
isbn={978-989-8565-29-7},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (IC3K 2012) - KDIR
TI - Collaborative Filtering based on Sentiment Analysis of Guest Reviews for Hotel Recommendation
SN - 978-989-8565-29-7
IS - 2184-3228
AU - Fukumoto, F.
AU - Motegi, C.
AU - Matsuyoshi, S.
PY - 2012
SP - 193
EP - 198
DO - 10.5220/0004130901930198
PB - SciTePress

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