Multi-level knowledge-based approach for implicit aspect identification
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Multi-level knowledge-based approach for implicit aspect identification Toqir A. Rana 1,2 & Yu-N Cheah 1 & Tauseef Rana 3
# Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Sentiment analysis or opinion mining is the area of research in Natural Language Processing (NLP) and text mining which deals with the systematic identification of subjective information from user generated text. At a more fine-grained level, aspect-based sentiment analysis focuses on the targets of users’ opinions and determining sentiment orientation of these opinions. Among different tasks of aspect-based sentiment analysis, aspect extraction is the key task which includes extraction of both explicit and implicit aspects. Due to the complexity of implicit aspects, not much effort has been put forward to solve the problem while explicit aspects have been studied extensively in the recent past. Existing approaches for implicit aspect extraction have focused on specific type of aspects and have neglected the actual problem. Therefore, in this paper, we have proposed a multi-level approach which identifies implicit aspects using co-occurrence and similarity-based techniques. This research focuses on the extraction of clues for implicit targets of users’ opinions and identification of true targets of users’ opinions with the help of implicit aspect clues. The proposed approach is divided into two phases: first, several rules are crafted to identify clues for implicit aspects in a review sentence. Secondly, aspects are assigned on the basis of extracted clues using proposed multi-level approach. The proposed model can extract not only implicit aspect clues associated with opinion words but also allocate clues to opinion words where no association is identified. This helps to identify implicit aspects with or without co-occurrences of opinion words with explicit aspects. Experimental evaluation elaborates the importance of implicit aspect clues in the identification of targets of users’ opinions. The proposed approach shows better results as compared with the state-of-the-art approaches for the identification of implicit targets of users’ opinions on a dataset of different product reviews. Keywords Implicit aspect extraction . Multi-level knowledge-based approach . Co-occurrences . IAC . NGD
1 Introduction Among the different granularity levels of sentiment analysis, aspect-based sentiment analysis is a more fine-grained area which not only deals with the users’ opinions but also tends to identify targets of these opinions [1, 2]. There are three major tasks of aspect-based sentiment analysis: (1) aspect and opinion extraction, (2) sentiment orientation of opinions,
* Toqir A. Rana [email protected] 1
School of Computer Sciences, Universiti Sains Malaysia, Penang, Malaysia
2
Department of Computer Science & IT, The University of Lahore, Lahore, Pakistan
3
Department of Computer Software Engineering, MCS, National University of Sciences and Technology, Islamabad, Pakistan
and (3) summarization of extracted aspects
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