research-article

Ensemble based Parallel k means using Map Reduce for Aspect Based Summarization

Authors:

K. UmamaheswariAuthors Info & Claims

ICIA-16: Proceedings of the International Conference on Informatics and Analytics

Article No.: 26, Pages 1 - 9

https://doi.org/10.1145/2980258.2980308

Published: 25 August 2016 Publication History

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Abstract

Aspect based summarization is very useful for all the stake holders in analysing voluminous reviews in the web. Even though many parallel algorithms had been available for text summarization, they could not be explicitly used for generating aspect based summaries in the field of opinion mining. In this paper, we have proposed a new parallel k means clustering approach based on Map Reduce framework for aspect based summary generation, which particularly incorporates bagging and ensembling techniques. The performance of the system generated summary is evaluated using ROUGE tool kit with human standard reference summaries and it was found to improve considerably than other state of art approaches.

References

[1]

Boiy, E. & Moens, M. (2009). A machine learning approach to sentiment analysis in multilingual Web texts. J. Info Retrieval 12(5): 526--558. DOI = http://link.springer.com/article/10.1007%2Fsl0791-008-9070-z

Digital Library

[2]

Dean. J, Ghemawat. S., MapReduce: Simplified Data Processing on Large Clusters Comm of the ACM, January, 2008, 51(1) 107--113. DOI= http://dl.acm.org/citation.cfm?doid=1327452.1327492

Digital Library

[3]

Deerwester. S, Dumais. S. T., Furnas. G. W., Landauer. T. K., and Harshman. R Indexing by latent semantic analysis. J. of the American Soc for Info Science 41(sep 1990), 391--407.

[4]

Dietterich. T.G, Machine Learning Research: Four Current Directions AI Magazine 18(1997), 97--136.

[5]

Fellbaum, C. (1998). WordNet: An Electronic Lexical Database. MIT Press.

[6]

Han.J, Kamber.M 2000. Data Mining: Concepts and Techniques, Morgan Kaufmann Publishers.

Digital Library

[7]

Ion Androutsopoulos, Prodromos Malakasiotis, A Survey of Paraphrasing and Textual Entailment Methods, J of Arti Int Res 38 (2010), 135--187.

Digital Library

[8]

Jayashri Khairnar and Mayura Kinikar Latent Semantic Analysis Used for Mobile Rating and Review Summarization Int Journal of Comp Sci and Telecom 4 6(June 2013), 61--67.

[9]

JeremyBejarano, Koushiki Bose, Tyler Brannan, Anita Thomas Sampling Within k-Means Algorithm to Cluster Large Dataset Technical Report 2011 UMBC High Performance Computing Facility, University of Maryland, Baltimore County.

[10]

Kavita Ganesan and ChengXiangZhai and Jiawei Han Opinosis: A Graph-Based Approach to Abstractive Summarization of Highly Redundant Opinions In Proceedings of the 23rd International Conference on Computational Linguistics (Beijing, Aug 23, 2010) 340--348.

Digital Library

[11]

Lin, D. (1998a). Automatic retrieval and clustering of similar words. In Proceedings of the 36th Annual Meeting of ACL and 17th Int. Conf. on Comp. Linguistics (Montreal, Quebec, Canada.,1998) 768--774.

Digital Library

[12]

Lin, Chin-Yew. 2004 ROUGE: a Package for Automatic Evaluation of Summaries In Proceedings of the Workshop on Text Summarization Branches Out (WAS, Barcelona, Spain, July 2004)25--26.

[13]

J. B. MacQueen Some Methods for Classification and Analysis of Multivariate Observations Fifth Berkeley Symposium: Mac Queen: University of California Press, 281--297.

[14]

Rafeal faerriria et.al Assessing sentence scoring techniques for extractive text summarization Expert systems with Applications Elsevier 40(oct 2013), 5755--5764.DOI= http://dx.doi.org/10.1016/j.eswa.2013.04.023

[15]

Ryosuke Tadano, Kazutaka Shimada, and Tsutomu Endo Multi-aspects Review Summarization Based on Identification of Important Opinions and their Similarity In Proceedings of the 24th Pacific Asia Conference on Language, Information and Computation PACLIC 24(Tohoku University, Japan Nov 4-7, 2010) 685--692.

[16]

VivekNarayanan, Ishan Arora, Arjun Bhatia Fast and accurate sentiment classification using an enhanced Naive Bayes model Intelligent Data Engineering and Automated Learning IDEAL 2013, Lecture notes in comp sci, LNCS 8206 194--201.

Digital Library

[17]

Weizhong Zhao, Huifang Ma and Qing He Parallel K-Means Clustering Based on Map Reduce 2009 Lecture notes in comp sci, LNCS 5931 674--679 2009.

Digital Library

[18]

X. Wu, V. Kumar, J.-R. Quinlan, J. Ghosh, Q. Yang, H. Motoda, G. Mclachlan, A. Ng, B. Liu, P. Yu, Z.-H.Zhou, M. Steinbach, D. Hand, and D.Steinberg Top 10 Algorithms in Data Mining Knowledge and Information Systems (Jan 2008 14(1) 1--37. DOI=http://link.springer.com/article/10.1007/s10115-007-0114-2

Digital Library

[19]

Large Movie Review Dataset. (n.d.). Retrieved from http://ai.stanford. edu/~amaas/data/sentiment/

[20]

http://www.text-analytics101.com/

Cited By

Qureshi MAsif MKhan MKamal AShahid B(2023)Roman Urdu Sentiment Analysis of Songs‘ ReviewsVFAST Transactions on Software Engineering10.21015/vtse.v11i1.139911:1(101-108)Online publication date: 31-Mar-2023
https://doi.org/10.21015/vtse.v11i1.1399
Gupta VSingh VMukhija PGhose U(2019)Aspect-based sentiment analysis of mobile reviewsJournal of Intelligent & Fuzzy Systems10.3233/JIFS-17902136:5(4721-4730)Online publication date: 14-May-2019
https://doi.org/10.3233/JIFS-179021
Shama ADhage S(2018)A Meticulous Critique on Prevailing Techniques of Aspect-Level Sentiment Analysis2018 International Conference on Current Trends towards Converging Technologies (ICCTCT)10.1109/ICCTCT.2018.8551066(1-7)Online publication date: Mar-2018
https://doi.org/10.1109/ICCTCT.2018.8551066
Show More Cited By

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ICIA-16: Proceedings of the International Conference on Informatics and Analytics

August 2016

868 pages

ISBN:9781450347563

DOI:10.1145/2980258

Copyright © 2016 ACM.

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Published: 25 August 2016

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ICIA-16: International Conference on Informatics and Analytics

August 25 - 26, 2016

Pondicherry, India

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Cited By

Qureshi MAsif MKhan MKamal AShahid B(2023)Roman Urdu Sentiment Analysis of Songs‘ ReviewsVFAST Transactions on Software Engineering10.21015/vtse.v11i1.139911:1(101-108)Online publication date: 31-Mar-2023
https://doi.org/10.21015/vtse.v11i1.1399
Gupta VSingh VMukhija PGhose U(2019)Aspect-based sentiment analysis of mobile reviewsJournal of Intelligent & Fuzzy Systems10.3233/JIFS-17902136:5(4721-4730)Online publication date: 14-May-2019
https://doi.org/10.3233/JIFS-179021
Shama ADhage S(2018)A Meticulous Critique on Prevailing Techniques of Aspect-Level Sentiment Analysis2018 International Conference on Current Trends towards Converging Technologies (ICCTCT)10.1109/ICCTCT.2018.8551066(1-7)Online publication date: Mar-2018
https://doi.org/10.1109/ICCTCT.2018.8551066
Dhage SShama A(2018)An Atypical Approach for Uncovering the Essence of Emotions in Consumer Reviews2018 4th International Conference on Computer and Information Sciences (ICCOINS)10.1109/ICCOINS.2018.8510587(1-6)Online publication date: Aug-2018
https://doi.org/10.1109/ICCOINS.2018.8510587
Boongoen TIam-On N(2018)Cluster ensembles: A survey of approaches with recent extensions and applicationsComputer Science Review10.1016/j.cosrev.2018.01.00328(1-25)Online publication date: May-2018
https://doi.org/10.1016/j.cosrev.2018.01.003

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