期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 57, 期 -, 页码 248-269出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2016.03.048
关键词
Recommender systems; Framework; Integrated semantic resources; Sentiment analysis; Word Sense Disambiguation; Content categorisation
类别
资金
- University of Alicante
- Generalitat Valenciana
- Spanish Government
- European Commission [TIN2015-65136-C2-2-R, TIN2015-65100-R, SAM (FP7-611312), PROMETEOII/2014/001]
In this work we present a semantic framework suitable of being used as support tool for recommender systems. Our purpose is to use the semantic information provided by a set of integrated resources to enrich texts by conducting different NLP tasks: WSD, domain classification, semantic similarities and sentiment analysis. After obtaining the textual semantic enrichment we would be able to recommend similar content or even to rate texts according to different dimensions. First of all, we describe the main characteristics of the semantic integrated resources with an exhaustive evaluation. Next, we demonstrate the usefulness of our resource in different NLP tasks and campaigns. Moreover, we present a combination of different NLP approaches that provide enough knowledge for being used as support tool for recommender systems. Finally, we illustrate a case of study with information related to movies and TV series to demonstrate that our framework works properly. (C) 2016 Elsevier Ltd. All rights reserved.
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