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Recent approaches have shown the significance of dependency-based rules for the given task. These rules are heavily dependent on the dependency parser and generated with the help of grammatical rules. In this article, we are proposing to learn from user\u2019s behaviour to identify the relation among aspects and opinions. The use of sequential patterns has been proposed for the extraction of aspects. The key purpose of this research is to study the impact of sequential pattern mining in the phase of aspect extraction. Our experimental results show that the approach proposed in our work produced better results as compared with the state-of-the-art approaches.<\/jats:p>","DOI":"10.1177\/0165551518808195","type":"journal-article","created":{"date-parts":[[2018,10,23]],"date-time":"2018-10-23T09:41:13Z","timestamp":1540287673000},"page":"643-655","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":33,"title":["Sequential patterns rule-based approach for opinion target extraction from customer reviews"],"prefix":"10.1177","volume":"45","author":[{"given":"Toqir A","family":"Rana","sequence":"first","affiliation":[{"name":"School of Computer Sciences, Universiti Sains Malaysia, Malaysia; Department of Computer Science & IT, The University of Lahore, Pakistan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu-N","family":"Cheah","sequence":"additional","affiliation":[{"name":"School of Computer Sciences, Universiti Sains 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