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Summarization and Negative Reviews Opinion Mining of Multiple User Reviews in Text Domain

by Anita K. Bodke, M. G. Bhandare
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 145 - Number 13
Year of Publication: 2016
Authors: Anita K. Bodke, M. G. Bhandare
10.5120/ijca2016910885

Anita K. Bodke, M. G. Bhandare . Summarization and Negative Reviews Opinion Mining of Multiple User Reviews in Text Domain. International Journal of Computer Applications. 145, 13 ( Jul 2016), 31-33. DOI=10.5120/ijca2016910885

@article{ 10.5120/ijca2016910885,
author = { Anita K. Bodke, M. G. Bhandare },
title = { Summarization and Negative Reviews Opinion Mining of Multiple User Reviews in Text Domain },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 145 },
number = { 13 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 31-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume145/number13/25342-2016910885/ },
doi = { 10.5120/ijca2016910885 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:48:47.692729+05:30
%A Anita K. Bodke
%A M. G. Bhandare
%T Summarization and Negative Reviews Opinion Mining of Multiple User Reviews in Text Domain
%J International Journal of Computer Applications
%@ 0975-8887
%V 145
%N 13
%P 31-33
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As all uses online services so it become tedious job to kind opinion about needed things likes,publication,restaurant etc.so here develop system which take input reviews and tips(micro-review) from different sites and provide user a compact and informative set of review. Problem of selection reviews which cover maximum number of tips is NP-hard, so provide a maximum solution, use greedy approach to solve problem. Also provide user a reason behind negative review. For this develop our own algorithm. For the project data collect from webKB,Fouresquare.com,yelp.com.Proposed system select here tips for selecting informative review because tips are highly concise, authentic(user place it when he/her check in at that place),content relevant data.

References
  1. Thanh-Son Nguyen, Hady W. Lauw, Member, IEEE, andPanayiotis Tsaparas, Member, IEEEReview Selection UsingMicro-Reviews in IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 27, NO. 4, APRIL 2015.
  2. E. Kouloumpis, T. Wilson, and J. Moore, Twitter sentiment analysis: The good the bad and the omg, in. 5th Int. Conf.Weblogs Social Media., 2011, pp. 538541. 1110.
  3. Q. Yuan, G. Cong, Z. Ma, A. Sun, and N. M. Thalmann,Timeaware point-of-interest recommendation, in Proc. 36th Int. ACM SIGIR Conf. Res. Develop. Inf. Retrieval., 2013, pp.363372.
  4. W. Yu, R. Zhang, X. He, and C. Sha, Selecting a diversified set of reviews, in Proc. 15th Asia-Pacific Web Conf, Jun. 2013, pp. 31663173.
  5. M. A. Vasconcelos, S. Ricci, J. Almeida, F. Benevenuto, and V. Almeida, Tips, dones and todos: Uncovering userprofiles in foursquare, in in Proc. 5th ACM Int. Conf. Web Search Data Mining, 2012, pp. 653662.
  6. K. Ganesan, C. Zhai, and E. Viegas, Micropinion generation:An unsupervised approach to generating ultraconcise summaries of opinions, in Proc. 21st Int. Conf. World Wide Web., 2012, pp. 869878 SIGCHI Conference on Human Factors in Computing Systems
  7. T. Lapps, M. Cornella, and E. Teri, Selecting a characteristic set of reviews, in Proc. 18th ACM SIGKDD Int. Conf. Know.Disco. Data Mining, 2012, pp. 832840
  8. P. Sinha, S. Mehrotra, and R. Jain, Summarization of personal photologs using multidimensional content and context, in Proc. 1st ACM Int. Conf. Multimedia Retrieval, 2011.
  9. P. Tsiaris, A. Ntoulas, and E. Terzi, Selecting a comprehensiveset of reviews, in Proc. 17th ACM SIGKDD Int. Conf. Knowl. Discov. Data Mining. 2011, pp. 168176.
  10. T. Lappas and D. Gunopulos, Efficient confident search in large review corpora, in Proc. Eur. Conf. Mach. Learn. Knowl. Discovery Databases: Part II., 2010, pp. 195210
  11. K. Ganesan, C. Zhai, and J. Han, Opinosis: A graphbasedapproach to abstractive summarization of highly redundant opinions, in Proc. 23rd Int. Conf. Comput. Linguistics. 2010, pp. 340348.
  12. Y. Lu, P. Tsaparas, A. Ntoulas, and L. Polanyi, Exploiting social context for review quality prediction, in Proc. 19th Int. Conf. World Wide Web., Jun. 2009, pp. 15971604.
  13. B. J. Jansen, M. Zhang, K. Sobel, and A. Chowdury, Twitter power: Tweets as electronic word of mouth, in J.Amer. Soc. Inf. Sci. Technol.,, vol. 60, no. 11, pp. 21692188,2009.
  14. A. Ghose and P. G. Ipeirotis, Designing novel reviewranking systems: Predicting the usefulness and impact of reviews, in Proc. 9th Int. Conf. Electron.Commerce 2007.
Index Terms

Computer Science
Information Sciences

Keywords

Sentimental syntactic semantic similarity Review Micro review coverage efficiency.

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