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Computers 2018, 7(4), 70; https://doi.org/10.3390/computers7040070

Sentence Level Domain Independent Opinion and Targets Identification in Unstructured Reviews

1
Department of Computer Science, University of Science & Technology, 28100 Bannu, Pakistan
2
Department of Computer Science and Software Engineering, International Islamic University, Islamabad 44000, Pakistan
*
Author to whom correspondence should be addressed.
Received: 5 November 2018 / Revised: 29 November 2018 / Accepted: 4 December 2018 / Published: 11 December 2018
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Abstract

User reviews, blogs, and social media data are widely used for various types of decision-making. In this connection, Machine Learning and Natural Language Processing techniques are employed to automate the process of opinion extraction and summarization. We have studied different techniques of opinion mining and found that the extraction of opinion target and opinion words and the relation identification between them are the main tasks of state-of-the-art techniques. Furthermore, domain-independent features extraction is still a challenging task, since it is costly to manually create an extensive list of features for every domain. In this study, we tested different syntactic patterns and semantic rules for the identification of evaluative expressions containing relevant target features and opinion. We have proposed a domain-independent framework that consists of two phases. First, we extract Best Fit Examples (BFE) consisting of short sentences and candidate phrases and in the second phase, pruning is employed to filter the candidate opinion targets and opinion words. The results of the proposed model are significant. View Full-Text
Keywords: sentiment analysis; advanced analytics; opinion targets sentiment analysis; advanced analytics; opinion targets
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Khan, K.; Khan, W. Sentence Level Domain Independent Opinion and Targets Identification in Unstructured Reviews. Computers 2018, 7, 70.

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