Feature Extraction From Product Review Using Ontology
|Drashti Naik1 , Jitali Patel2|
1 Dept. of CSE, Institute of Technology- Nirma University, Ahmedabad, , India .
2 Dept. of CSE, Institute of Technology- Nirma University, Ahmedabad, , India .
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Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-8 , Page no. 88-93, Aug-2017
Online published on Aug 30, 2017
Copyright © Drashti Naik, Jitali Patel . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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IEEE Style Citation: Drashti Naik, Jitali Patel, “Feature Extraction From Product Review Using Ontology”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.88-93, 2017.
MLA Style Citation: Drashti Naik, Jitali Patel "Feature Extraction From Product Review Using Ontology." International Journal of Computer Sciences and Engineering 5.8 (2017): 88-93.
APA Style Citation: Drashti Naik, Jitali Patel, (2017). Feature Extraction From Product Review Using Ontology. International Journal of Computer Sciences and Engineering, 5(8), 88-93.
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|Opinion mining is accepting more attention because of the development of blogs, e-commerce, news, reports, forums and additional web sources where individuals tend to express their opinions. Different people have different opinions. People`s thought may vary according to the domain and opinion may contain both positive and negative words. For a product, user may like or dislike some of its features. Filtering this review and extract domain related features is the important task of this paper. In this paper, ontology is used to extract the features and adjectives are used as the sentiment word. Sentiment Analysis is used to obtain positive or negative feature of the review.|
|Key-Words / Index Term :|
 B. Liu,”Sentiment analysis and opinion mining”, Synthesis lectures on human language technologies, vol.5, no.1, pp.1-167, 2012.
 T.Ahmad and M.N.Doja,”Opinion mining using frequent pattern growth method from unstructured text”, pp. 92-95, 2013.
 S.Mishra, D.Mishra, and S.K.Satapathy,”Fuzzy pattern tree approach for mining frequent patterns from gene expression data”, vol.2, pp.359-363,2011.
 H.Wang and J.Chen,”Extracting two-noun phrases from customer reviews”, pp.1-4, 2009.
 G.Altenbek and R.Sun,”Kazakh noun phrase extraction based on n-gram and rules”, pp.305-308, 2010.
 A.Jeyapriya and C.K.Selvi,”Extracting aspects and mining opinions in product reviews using supervised learning algorithm”, pp. 548-552, 2015.
 M.Yamamoto, T.Yamasaki, and K.Aizawa,”Service annotation and profling by review analysis”, pp.357-364, 2016.
 H.Hamdan, P.Bellot, and F.Bechet,”Supervised methods for aspect-based sentiment analysis”, pp. 596-600, 2014.
 W.Ding, X.Song, L.Guo, Z.Xiong, and X.Hu,”A novel hybrid hdp-lda model for sentiment analysis”, pp. 329-336, 2013.
 H.S.Le, T.Van Le, and T.V.Pham,”Aspect analysis for opinion mining of Vietnamese text”, pp. 118-123, 2015.
 S.Thirumaran and M.Sangeetha, "Ontology Founded Mesh Flatterer Aimed at Removal Facilities info Result", International Journal of Computer Sciences and Engineering, Vol.3, Issue.1, pp.224-227, 2015.
 Yaakub, R.M, Li and Feng Y,”Integration of Opinion into Customer Analysis Model”, IEEE International Conference on e-Business Engineering, pp. 90-95, 2011.
 Priyanka Sharma, R.K. Gupta, "A Novel Web Usage Mining Technique Analyzing Users Behaviour Using Dynamic Web log", International Journal of Computer Sciences and Engineering, Vol.5, Issue.6, pp.106-111, 2017.
 Shein, Khin Phyu Phyu and Thi Thi Soe Nyunt,”Sentiment classification based on Ontology and SVM Classifier”, IEEE Communication Software and Networks, pp. 169-172 ,2010.
 Freitas, Larissa A, and Renata Vieira,”Ontology based feature level opinion mining for portuguese reviews”, 22nd International Conference on World Wide Web. ACM, pp. 367-370 ,2013.
 Hazman, Maryam, Samhaa R.El-Beltagy and Ahmed Rafea,”A survey of ontology learning approaches”, vol. 22, No. 9,2011.
 Penalver-Martinez, Isidro, et al,”Feature-based opinion mining through ontologies”, Expert Systems with Application, pp.5995-6008 ,2014.
 Ali, Farman, Kyung-Sup Kwak and Yong-Gi Kim,”Opinion mining based on fuzzy domain ontology and Support Vector Machine: A proposal to automate online review classification”, Applied Soft Computing, pp. 235- 250, 2016.
 Kontopoulos, Efstratios, et al,”Ontology-based sentiment analysis of twitter posts”, Expert systems with applications, pp.4065-4074, 2013.