ROM - Review Opinion Mining a Novelized Framework
K. Vivekanandan1 , V.L. Helen Josephine2
Section:Review Paper, Product Type: Journal Paper
Volume-2 ,
Issue-11 , Page no. 86-89, Nov-2014
Online published on Nov 30, 2014
Copyright © K. Vivekanandan , V.L. Helen Josephine . 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: K. Vivekanandan , V.L. Helen Josephine, “ROM - Review Opinion Mining a Novelized Framework,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.11, pp.86-89, 2014.
MLA Style Citation: K. Vivekanandan , V.L. Helen Josephine "ROM - Review Opinion Mining a Novelized Framework." International Journal of Computer Sciences and Engineering 2.11 (2014): 86-89.
APA Style Citation: K. Vivekanandan , V.L. Helen Josephine, (2014). ROM - Review Opinion Mining a Novelized Framework. International Journal of Computer Sciences and Engineering, 2(11), 86-89.
BibTex Style Citation:
@article{Vivekanandan_2014,
author = {K. Vivekanandan , V.L. Helen Josephine},
title = {ROM - Review Opinion Mining a Novelized Framework},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {11 2014},
volume = {2},
Issue = {11},
month = {11},
year = {2014},
issn = {2347-2693},
pages = {86-89},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=309},
publisher = {IJCSE, Indore, INDIA},
}
RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=309
TI - ROM - Review Opinion Mining a Novelized Framework
T2 - International Journal of Computer Sciences and Engineering
AU - K. Vivekanandan , V.L. Helen Josephine
PY - 2014
DA - 2014/11/30
PB - IJCSE, Indore, INDIA
SP - 86-89
IS - 11
VL - 2
SN - 2347-2693
ER -
VIEWS | XML | |
3696 | 3469 downloads | 3620 downloads |
Abstract
Today, as a result of the global internet viewers increased rapidly, consumers are more focused than ever on searching the best product and the best prices. Consequently, e-commerce corporations also invested their time, money and efforts to know the feedback and comments about their products. That would help the corporations to modernize their product at low prices, which in turn help them to extend and prosper in their business. Customer / Product review is an evaluation of the product performance and comment on the reliability and whether or not the product delivers on these promises. Now-a-days, online reviews are the recent media world-of-mouth, they are enormously influential and may have an enormous effect on however business is perceived. Since, overwhelming information on one product is available in the form of review, individuals or corporation finds very difficult to analyse each and every review to extract knowledge from that pool of unstructured data. So, to analyse and to extract knowledge from these large amounts of data automatic method must be developed. This paper describes the ROM framework for developing such an automatic method to mine the opinion from the online product reviews.
Key-Words / Index Term
Opinion Mining, Sentiment Analysis, Framework for Opinion Mining
References
[1] Liu, B. 2010. Sentiment analysis and subjectivity. In Handbook of Natural Language Processing, Second Edition, N. Indurkhya and F. J. Damerau, Eds. CRC Press, Taylor and Francis Group, Boca Raton, FL. ISBN 978-1420085921.
[2] Pang, B. and Lee, L. 2008. Opinion mining and sentiment analysis. Found. Trends Inf. Retr. 2, 1-2, 1–135.
[3] Bing Liu. Sentiment Analysis and Opinion Mining, Morgan & Claypool Publishers, May 2012.
[4] Hemalatha, G.P. Saradhi Varma, A. Govardan, Preprocessing the Informal Text for efficient Sentiment Analysis, IJETTCS, Volume 1, Issue 2, July-August 2012, ISSN: 2278-6856
[5] Kushal Bafna, Durga Toshniwal, Feature Based Summarization of Customers' Reviews of Online Products, Elsevier Procedia Computer Science 22(2013) 142-151.
[6] Alexandra Blahur, Mijali Kabadjov, Josef Steinberger, Ralf Steinberger, Andres Montoyo, Challenges and solutions in the opinion summarization of user-generated content, Springer Science, J Intell Inf Syst (2012) 39: 375-398
[7] Bakhtawar Seerat, Farouque Azam, Opinion Mining : Issues and Challengers (A Survey), IJCA, (0975-8887), Volume 48 – No. 9 July 2012.
[8] Kim, Hyun Duk, Ganesan Kavita A., Sondhi Parikshit, and Zhai ChengXiang, Comprehensive Review on Opinion Summarization, 2011.
[9] Dingding Wang, Shenghuo Zhu, Tao Li, SumView: A Web-based engine for summarizing product reviews and customer opinions, Elsevier, Expert Systems with Applications 40 (2013) 27-33
[10] Radev, D., Jing, H., Stys, M., & Tam, D. (2004). Centroid-based summarization of multiple documents. Information Processing and Management, 919–938.
[11] Mihalcea, R., & Tarau, P. (2005). A language independent algorithm for single and multiple document summarization. In Proceedings of IJCNLP 2005.
[12] Wan, X., Yang, J., & Xiao, J. (2007). Manifold-ranking based topic-focused multi-document summarization. In Proceedings of IJCAI (pp. 2903–2908).
[13] Gong, Y., & Liu, X. (2001). Generic text summarization using relevance measure and latent semantic analysis. In Proceedings of SIGIR (pp. 75–95).
[14] Li, T., & Ding, C. (2006). The relationships among various nonnegative matrix factorization methods for clustering. In Proceedings of IEEE international conference on data mining (pp. 362–371).
[15] Shen, D., Sun, J.-T., Li, H., Yang, Q., & Chen, Z. (2007). Document summarization using conditional random fields. In Proceedings of IJCAI (pp. 2862–2867).
[16] Conroy, J., & O’Leary, D. (2001). Text summarization via hidden markov models. In Proceedings of SIGIR (pp. 406–407.
[17] Dhanashri Chafale and Amit Pimpalkar, "Review on Developing Corpora for Sentiment Analysis Using Plutchik’s Wheel of Emotions with Fuzzy Logic", International Journal of Computer Sciences and Engineering, Volume-02, Issue-10, Page No (14-18), Oct -2014, E-ISSN: 2347-2693