Combining Probabilistic Language Models for Aspect-Based Sentiment Retrieval
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Altres documents de l'autoria: García Moya, Lisette; Anaya Sánchez, Henry; Berlanga Llavori, Rafael
Metadades
Mostra el registre complet de l'elementcomunitat-uji-handle:10234/9
comunitat-uji-handle2:10234/7038
comunitat-uji-handle3:10234/54899
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INVESTIGACIONMetadades
Títol
Combining Probabilistic Language Models for Aspect-Based Sentiment RetrievalData de publicació
2012Editor
Springer Berlin HeidelbergISBN
978-3-642-28996-5ISSN
0302-9743; 1611-3349Cita bibliogràfica
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. 561-564Tipus de document
info:eu-repo/semantics/bookPartVersió de l'editorial
http://link.springer.com/chapter/10.1007/978-3-642-28997-2_64#Paraules clau / Matèries
Resum
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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