Opinion Words and Opinion Techniques for Ecommerce
Komal Urkude1, Jignyasa Sanghavi2

1Komal Urkude, M.Tech Scholar, Nagpur University, Ramdeobaba college of engineering & management, Nagpur, India.

2Jignyasa Sanghavi, Assistant professor, Nagpur University, Ramdeobaba college of engineering & management, Nagpur, India.

Manuscript received on 09 June 2019 | Revised Manuscript received on 14 June 2019 | Manuscript Published on 08 July 2019 | PP: 549-552 | Volume-8 Issue-8S3 June 2019 | Retrieval Number: H10780688S319/19©BEIESP

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In the present era loads of items are purchased online, due to this rating system become very useful for getting direct data about the item. The rating system does opinion mining i.e. extraction of the opinion targets and opinion words from data of online reviews. Be that as it may, there are numerous problems associated with the precision of the system. Proposed method minimizes the negative impact of parsing errors in comparison to the previous existing methodologies. This existing methods are usually syntax based. The proposed model can achieve better accuracy as compared to existing unsupervised word alignment model. It is because of the use of incomplete supervision model. Opinion mining techniques can be prove to be a vital method for the analyses of user reviews. In this study, we will do the investigation of the previous researches on extracting opinion words and opinion target system.

Keywords: User Opinion mining, Opinion word extraction, Opinion Target Extraction, Text Mining, Word Alignment Model, Co-Ranking.
Scope of the Article: e-Commerce