Aspect Based Sentiment Analysis with Text Compression
|Apoorva T.1 , Pradeep N.2|
|Correspondence should be addressed to: Department of CSE, Bapuji Institute of Engineering and Technology, Davanagere, India|Department of CSE, Bapuji Institute of Engineering and Technology, Davanagere, India.|
Section:Review Paper, Product Type: Journal Paper
Volume-5 , Issue-8 , Page no. 63-66, Aug-2017
Online published on Aug 30, 2017
Copyright © Apoorva T., Pradeep N. . 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: Apoorva T., Pradeep N., “Aspect Based Sentiment Analysis with Text Compression”, International Journal of Computer Sciences and Engineering, Vol.5, Issue.8, pp.63-66, 2017.
MLA Style Citation: Apoorva T., Pradeep N. "Aspect Based Sentiment Analysis with Text Compression." International Journal of Computer Sciences and Engineering 5.8 (2017): 63-66.
APA Style Citation: Apoorva T., Pradeep N., (2017). Aspect Based Sentiment Analysis with Text Compression. International Journal of Computer Sciences and Engineering, 5(8), 63-66.
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|Sentiment Analysis measures the aptitude of people’s opinions through Natural Language Processing, Computational Lingus tics and Text analysis, which are used to extract and analyse subjectivity of information. This paper focuses on Aspect Based Sentiment Analysis, where Text Compression is performed before Aspect Based analysis. For a given huge text is compressed using Text compression model, which is considered as pre-processing task for Aspect Based Sentiment Analysis.|
|Key-Words / Index Term :|
|Aspect Based sentiment analysis, text compression|
 Supriya B. Moralwar and Sachin N. Deshmukh, "Different Approaches of Sentiment Analysis", International Journal of Computer Sciences and Engineering, Vol.3, Issue.3, pp.160-165, 2015.
 U. Aggarwal, G. Aggarwal, "Sentiment Analysis : A Survey", International Journal of Computer Sciences and Engineering, Vol.5, Issue.5, pp.222-225, 2017.
 Reshma Bhonde1, Binita Bhagwat2, Sayali Ingulkar, “Sentiment Analysis Based on Dictionary Approach” International Journal of Emerging Engineering Research and Technology Vol.3, Issue.1, pp.51-55, 2015.
 C. Nanda, M. Dua, "A Survey on Sentiment Analysis", International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.67-70, 2017.
 Jeonghee yi, Tetsuya, “Sentiment analysizer: Extracting Sentiments abut a text with Natural Language processing techniques”, Department of Computer Science, university of texas, Austin, TX 78712, USA.
 Shabina Dhuria, “Natural Language Processing Techniques for Sentimenyal analysis”, International Journal of Emerging Trends and Technology in computer science, Vol.1, Issue.2, July 2015.
 Navpreet Kaur, Mohit Kakkar, “A balanced sentiment analysis approach with stemming porter for neutralized emotion weightage”, International Journal of Advanced Research in Computer and Communication Engineering Vol.4, Issue.10, October 2015.
 Norjihan Abd Ghani1 and Siti Syahidah Mohamad Kamal, “A Sentiment-Based Filteration”, Proceedings of the 5th International Conference on Computing and Informatics, International Conference on Computer and Communication Technology (ICOCT) 2015 11-13 August, 2015 Istanbul, Turkey, University Utara Malaysia.
 Anais Collomb, Crina Costea, “A Compariative study of sentiment analysis methods”, university of lyon, INSA-Lyon, F-69621 Villeurbanne, France.
 Hassan Saif,1 Miriam Fernandez,1 Yulan He,2 Harith Alani, “On Stopwords, Filtering and Data Sparsity for Sentiment Analysis”, School of Engineering and Applied Science, Aston University, UK.
 T. Cohn and M. Lapata, “An abstractive approach to sentence compression”, ACM Trans. Intell. Syst. Technol., Vol.4, pp. 1–35, 2013.
 Rehab Duwairi, Mahmoud El-Orfali, “Effects of Preprocessing Strategies on Sentiment Analysis”, Journal of Information Science 1–14, 2013.
 Hemalatha, Dr. G. O Saradhi Varma, “ Preprocessing the Informal Text for efficient Sentiment Analysis”, International Jounal of Emerging And Technology in Computer Science Vol.1, Issue.2, 2012.
 G. Qiu, B. Liu, J. Bu, and C. Chen, “Opinion word expansion and target extraction through double propagation”, Computer Linguist., vol. 37, no. 1, pp. 9–27, 2011.
 Dr.V.Maniraj, V.Krishnaveni, "K-Nearest Neighbor Grouping in Excess of Semantically Secure Encryption Interactive Evidence", International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.288-291, 2016.
 Vivek Narayanan, Ishan Arora , Arjun Bhatia, “Fast and accurate sentiment classification using an enhanced Naive Bayes model”, Proceedings of the 49th annual meeting of the Association for Computational Linguistics: Human Language Technologies. Vol.1. 2011.
 B. Pang and L. Lee, “Opinion mining and sentiment analysis”, Found. Trends Informatics Retr., Vol.2, no. 1–2, pp. 1–135, Jan. 2008.
 K. Knight and D and Marcu,M. Galley and K. McKeown, “Lexicalized Markov grammars for sentence compression”, in Proceedings Human Language Technology: Conference North Amer. Chapter Associates for Computer Linguist.; Proc. Main Conf., Rochester, NY, USA, Apr. 2007, pp. 180–187,
 V. Hatzivassiloglou and K. R. McKeown. “Predicting the semantic orientation of adjectives”, In Proceedings of the 35th ACL Conference, pages 174–181.
 T. Nomoto, “Discriminative sentence compression with conditional random fields”, Information Process Management, Vol.43, pp. 1571–1587.
 J. Guo, W. Che, H. Wang, and T. Liu, “Revisiting embedding features for simple semi-supervised learning”, in Proceedings EMNLP 14, 2014.
 J. Kaur, S.S. Sehra, S.K. Sehra, "A Systematic Literature Review of Sentiment Analysis Techniques", International Journal of Computer Sciences and Engineering, Vol.5, Issue.4, pp.22-28, 2017.
 Naveen Kumar Laskari, Suresh Kumar Sanampudi, “Aspect Based Sentiment analysis”, IOSR Journal of Computer Engineering, Vol.18, Issue.2, pp. 24-28, 2016.