Combining Probabilistic Language Models for Aspect-Based Sentiment Retrieval
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Other documents of the author: García Moya, Lisette; Anaya Sánchez, Henry; Berlanga Llavori, Rafael
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Show full item recordcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/54899
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INVESTIGACIONMetadata
Title
Combining Probabilistic Language Models for Aspect-Based Sentiment RetrievalDate
2012Publisher
Springer Berlin HeidelbergISBN
978-3-642-28996-5ISSN
0302-9743; 1611-3349Bibliographic citation
García Moya, Lisette; Anaya Sánchez, Henry, Berlanga Llavori,Rafael " Combining Probabilistic Language Models for Aspect-Based Sentiment Retrieval ". En: Advances in Information Retrieval– 34th European Conference on IR Research, ECIR 2012, Barcelona, Spain, April 1-5, 2012. Proceedings / Baeza-Yates, Ricardo [et al.] (Eds.). Berlin : Springer, 2012. (Lecture Notes in Computer Science; 7224) . ISBN 978-3-642-28996-5, pp. 561-564Type
info:eu-repo/semantics/bookPartPublisher version
http://link.springer.com/chapter/10.1007/978-3-642-28997-2_64#Subject
Abstract
In this paper, we present a new methodology aimed at retrieving relevant product aspects from a collection of customer reviews, as well as the most salient sentiments expressed about them. Our proposal is both unsup ... [+]
In this paper, we present a new methodology aimed at retrieving relevant product aspects from a collection of customer reviews, as well as the most salient sentiments expressed about them. Our proposal is both unsupervised and domain independent, and does not relies on NLP techniques such as parsing or dependence analysis. In our experiments, the proposed method achieves good values of precision. It is also shown that our approach is capable of properly retrieving the relevant aspects and their sentiments even from individual reviews. [-]
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