DocumentCode :
189181
Title :
A Collaborative Filtering Approach Based on User´s Reviews
Author :
D´Addio, Rafael Martins ; Garcia Manzato, Marcelo
Author_Institution :
Inst. de Cienc. Mat. e de Comput., Univ. de Sao Paulo, Sao Carlos, Brazil
fYear :
2014
fDate :
18-22 Oct. 2014
Firstpage :
204
Lastpage :
209
Abstract :
This paper proposes a collaborative filtering approach that uses users´ reviews to produce item descriptions that represent a consensus of users regarding items´ features. While earlier works focused on using structured metadata to represent items, recent approaches study how to use user-provided text, such as reviews, to produce better insights about the semantics in the content. Some involved problems, such as noise, personal opinions and false information are reduced by an algorithm based on sentiment analysis and natural language processing. We provide an evaluation using the MovieLens dataset, and the results are promising when compared to recommenders based only on structured metadata.
Keywords :
collaborative filtering; natural language processing; recommender systems; MovieLens dataset; collaborative filtering approach; natural language processing; recommenders; sentiment analysis; structured metadata; user reviews; user-provided text; Collaboration; Feature extraction; Motion pictures; Sentiment analysis; Vectors; Vocabulary; Collaborative Filtering; Item Representation; Recommender Systems; Sentiment Analysis; Unstructured Information;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems (BRACIS), 2014 Brazilian Conference on
Conference_Location :
Sao Paulo
Type :
conf
DOI :
10.1109/BRACIS.2014.45
Filename :
6984831
Link To Document :
بازگشت