6533b829fe1ef96bd12896a9

RESEARCH PRODUCT

Ontology-Guided Approach to Feature-Based Opinion Mining

Francisco García-sánchezRafael Valencia-garcíaIsidro Peñalver-martinez

subject

Information retrievalComputer scienceFeature extractionSentiment analysisFeature (machine learning)Selection (linguistics)Computational linguisticsOntology (information science)Social webData scienceSemantic Web

description

The boom of the Social Web has had a tremendous impact on a number of different research topics. In particular, the possibility to extract various kinds of added-value, informational elements from users' opinions has attracted researchers from the information retrieval and computational linguistics fields. However, current approaches to socalled opinion mining suffer from a series of drawbacks. In this paper we propose an innovative methodology for opinion mining that brings together traditional natural language processing techniques with sentimental analysis processes and Semantic Web technologies. The main goals of this methodology is to improve feature-based opinion mining by employing ontologies in the selection of features and to provide a new method for sentimental analysis based on vector analysis. The preliminary experimental results seem promising as compared against the traditional approaches.

yearjournalcountryeditionlanguage
2011-01-01
https://doi.org/10.1007/978-3-642-22327-3_20