In the last decade, the focus of the Opinion Mining field moved to detection of the pairs “aspect-polarity” instead of limiting approaches in the computation of the general polarity of a text. In this work, we propose an aspect-based opinion mining system based on the use of semantic resources for the extraction of the aspects from a text and for the computation of their polarities. The proposed system participated at the third edition of the Semantic Sentiment Analysis (SSA) challenge took place during ESWC 2018 achieving the runner-up place in the Task #2 concerning the aspect-based sentiment analysis. Moreover, a further evaluation performed on the SemEval 2015 benchmarks demonstrated the feasibility of the proposed approach.

The KABSA System at ESWC-2018 Challenge on Semantic Sentiment Analysis

Mauro Dragoni
2018

Abstract

In the last decade, the focus of the Opinion Mining field moved to detection of the pairs “aspect-polarity” instead of limiting approaches in the computation of the general polarity of a text. In this work, we propose an aspect-based opinion mining system based on the use of semantic resources for the extraction of the aspects from a text and for the computation of their polarities. The proposed system participated at the third edition of the Semantic Sentiment Analysis (SSA) challenge took place during ESWC 2018 achieving the runner-up place in the Task #2 concerning the aspect-based sentiment analysis. Moreover, a further evaluation performed on the SemEval 2015 benchmarks demonstrated the feasibility of the proposed approach.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/317908
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