TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Jakob, Niklas
A1  - Weber, Stefan Hagen
A1  - Müller, Mark-Christoph
A1  - Gurevych, Iryna
ED  - Cheung, David
ED  - Song, Il-Yeol
ED  - Chu, Wesley
ED  - Hu, Xiaohua
ED  - Lin, Jimmy
ED  - Li, Jiexun
ED  - Peng, Zhiyong
T1  - Beyond the stars: exploiting free-text user reviews to improve the accuracy of movie recommendations
T2  - TSA '09: Proceedings of the 1st international CIKM workshop on topic-sentiment analysis for mass opinion. Hong Kong, China, 6 November 2009
N2  - In this paper we show that the extraction of opinions from free-text reviews can improve the accuracy of movie recommendations. We present three approaches to extract movie aspects as opinion targets and use them as features for the collaborative filtering. Each of these approaches requires different amounts of manual interaction. We collected a data set of reviews with corresponding ordinal (star) ratings of several thousand movies to evaluate the different features for the collaborative filtering. We employ a state-of-the-art collaborative filtering engine for the recommendations during our evaluation and compare the performance with and without using the features representing user preferences mined from the free-text reviews provided by the users. The opinion mining based features perform significantly better than the baseline, which is based on star ratings and genre information only.
KW  - natural language processing
KW  - text analysis
KW  - database applications
KW  - data mining
KW  - algorithms
KW  - Rezension
KW  - Film
KW  - Empfehlung
KW  - Kollaborative Filterung
KW  - Datensatz
KW  - Benutzer
KW  - Automatische Sprachanalyse
KW  - Textanalyse
KW  - Datenbank
KW  - Data Mining
KW  - Algorithmus
KW  - measurement
KW  - experimentation
KW  - movie recommendation
KW  - opinion extraction
KW  - user preference
KW  - Empfehlungssystem
KW  - opinion mining
KW  - sentiment analysis
KW  - collaborative filtering
KW  - recommendation system
KW  - multi-relational learning
Y1  - 2009
UN  - https://nbn-resolving.org/urn:nbn:de:bsz:mh39-111390
SN  - 978-1-60558-805-6
SB  - 978-1-60558-805-6
U6  - https://doi.org/10.1145/1651461.1651473
DO  - https://doi.org/10.1145/1651461.1651473
SP  - 57
EP  - 64
PB  - Association for Computing Machinery
CY  - New York
ER  -