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Information 2019, 10(2), 42;

Using Opinion Mining in Context-Aware Recommender Systems: A Systematic Review

Institute of Mathematics and Computer Science—University of São Paulo, Avenida Trabalhador São Carlense, 400, São Carlos SP 13566-590, Brazil
Department of Informatics—State University of Maringá, Avenida Colombo, 5790, Maringá PR 87020-900, Brazil
Federal University of Mato Grosso do Sul—Três Lagoas Campus, Avenida Ranulpho Marques Leal, 3484, P.O. Box 210, Três Lagoas MS 79620-080, Brazil
Author to whom correspondence should be addressed.
Received: 14 December 2018 / Revised: 19 January 2019 / Accepted: 22 January 2019 / Published: 28 January 2019
(This article belongs to the Special Issue Modern Recommender Systems: Approaches, Challenges and Applications)
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Recommender systems help users by recommending items, such as products and services, that can be of interest to these users. Context-aware recommender systems have been widely investigated in both academia and industry because they can make recommendations based on a user’s current context (e.g., location and time). Moreover, the advent of Web 2.0 and the growing popularity of social and e-commerce media sites have encouraged users to naturally write texts describing their assessment of items. There are increasing efforts to incorporate the rich information embedded in user’s reviews/texts into the recommender systems. Given the importance of this type of texts and their usage along with opinion mining and contextual information extraction techniques for recommender systems, we present a systematic review on the recommender systems that explore both contextual information and opinion mining. This systematic review followed a well-defined protocol. Its results were based on 17 papers, selected among 195 papers identified in four digital libraries. The results of this review give a general summary of the current research on this subject and point out some areas that may be improved in future primary works. View Full-Text
Keywords: recommender systems; context-aware recommender systems; contextual information; opinion mining; systematic review recommender systems; context-aware recommender systems; contextual information; opinion mining; systematic review

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Sundermann, C.V.; Domingues, M.A.; Sinoara, R.A.; Marcacini, R.M.; Rezende, S.O. Using Opinion Mining in Context-Aware Recommender Systems: A Systematic Review. Information 2019, 10, 42.

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