CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

Challenges for Information Retrieval in Big data: Product Review Context

by Sanjib Kumar Sahu, D. P. Mahapatra, R. C. Balabantaray
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 136 - Number 3
Year of Publication: 2016
Authors: Sanjib Kumar Sahu, D. P. Mahapatra, R. C. Balabantaray
10.5120/ijca2016908475

Sanjib Kumar Sahu, D. P. Mahapatra, R. C. Balabantaray . Challenges for Information Retrieval in Big data: Product Review Context. International Journal of Computer Applications. 136, 3 ( February 2016), 27-33. DOI=10.5120/ijca2016908475

@article{ 10.5120/ijca2016908475,
author = { Sanjib Kumar Sahu, D. P. Mahapatra, R. C. Balabantaray },
title = { Challenges for Information Retrieval in Big data: Product Review Context },
journal = { International Journal of Computer Applications },
issue_date = { February 2016 },
volume = { 136 },
number = { 3 },
month = { February },
year = { 2016 },
issn = { 0975-8887 },
pages = { 27-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume136/number3/24135-2016908475/ },
doi = { 10.5120/ijca2016908475 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:36:03.634993+05:30
%A Sanjib Kumar Sahu
%A D. P. Mahapatra
%A R. C. Balabantaray
%T Challenges for Information Retrieval in Big data: Product Review Context
%J International Journal of Computer Applications
%@ 0975-8887
%V 136
%N 3
%P 27-33
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The ever increasing scale of e-commerce has today presented a big range of choice for the customer. Customer uses online product reviews as a primary criterion to make a decision for his purchase. These product reviews are scattered all around the internet, and this data has a great potential value. However, it is also unstructured and written in a natural language, which poses great problems for data mining and data analytics. The scale, non-uniformity and complexity of product reviews make them classic big data elements. This paper discusses the big data challenges and opportunities involved in mining and analytics of product review data. It formally studies the problem under a big data framework and formulates a plan for the extraction, mining and analysis. This paper also reviews some of the mining approaches for product reviews and implemented feature/attributes based method for finding the review of products.

References
  1. Watson, Peter (2005). Ideas: A History of Thought and Invention from Fire to Freud. New York: Harper Collins Publishers. ISBN 978-0-06-621064-3.
  2. Raven, Peter V., Xiaoqing Huang, and Ben B. Kim. "E-business in developing countries: a comparison of China and India." International Journal of E-Business Research 3.1 (2008).
  3. McAuley, Julian, and Jure Leskovec. "Hidden factors and hidden topics: understanding rating dimensions with review text." Proceedings of the 7th ACM conference on Recommender systems. ACM, 2013.
  4. Xindong Wu; Xingquan Zhu; Gong-Qing Wu; Wei Ding, "Data mining with big data," Knowledge and Data Engineering, IEEE Transactions on , vol.26, no.1, pp.97,107, Jan. 2014.
  5. Sagiroglu, S.; Sinanc, D., "Big data: A review," Collaboration Technologies and Systems (CTS), 2013 International Conference on , vol., no., pp.42,47, 20-24 May 2013.
  6. Dave, Kushal, Steve Lawrence, and David M. Pennock. "Mining the peanut gallery: Opinion extraction and semantic classification of product reviews."Proceedings of the 12th international conference on World Wide Web. ACM, 2003.
  7. Morinaga, Satoshi, et al. "Mining product reputations on the web." Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2002.
  8. Cardie, Claire, et al. "Combining Low-Level and Summary Representations of Opinions for Multi-Perspective Question Answering." New directions in question answering. 2003.
  9. Hu, Minqing, and Bing Liu. "Mining and summarizing customer reviews."Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2004.
  10. Olson, David L.; and Delen, Dursun (2008); Advanced Data Mining Techniques, Springer, 1st edition (February 1, 2008), page138,ISBN3-540-76916-1
  11. Chen Mosha,”Combining Dependency Parsing with Shallow Semantic Analysis for Chinese Opinion-Element Relation Identification”, IEEE, 2010, pp.299-305.
  12. Yuanbin Wu, Qi Zhang, Xuanjing Huang, Lide Wu,”Phrase Dependency Parsing for Opinion Mining”, EMNLP '09 Proceedings of the Conference on Empirical Methods in Natural Language Processing, Volume 3,2009
  13. Qi Zhang, Yuanbin Wu, Tao Li, Mitsunori Ogihara, Joseph Johnson, Xuanjing Huang,”Mining Product Reviews Based on Shallow Dependency Parsing”, SIGIR '09, Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval, 2009
  14. Cost, R. S., Finin, T., Joshi, A., Peng, Y., Nicholas, C., Soboroff, I., Chen, H., Kagal, L., Perich, F., Zou, Y., and Tolia, S. ‘ITTALKS: A Case Study in the Semantic Web and DAML+OIL.’ IEEE Intelligent Systems 17(1):40-47, 2002.
  15. Davies, J., Weeks, R. and Krohn, U. ‘QuizRDF: Search technology for the Semantic Web.’ In WWW2002 Workshop on RDF and Semantic Web Applications, Hawaii, 2002.
  16. Deutsch, A.,Fernandez, M., Florescu, D., Levy, A. and Suciu, D. ‘XML-QL: A query language for XML.’ In Proceedings of the Eighth International World Wide Web Conference, 1999.
  17. Ding, L,. Lina Zhou, and Tim Finin, ‘Trust Based Knowledge Outsourcing for Semantic Web Agents,’ 2003 IEEE/WIC International Conference on Web Intelligence (WI 2003), October 2003, Halifax, Canada.
  18. Ding, L., Tim Finin, Anupam Joshi, Rong Pan, R. Scott Cost, Joel Sachs, Vishal Doshi, Pavan Reddivari, and Yun Peng, Swoogle: A Search and Metadata Engine for the Semantic Web, Thirteenth ACM Conference on Information and Knowledge Management (CIKM'04), Washington DC, November 2004.
  19. Marc Abrams, editor, World WideWeb:Beyond the basics, Printice Hall, 1998
  20. Mohd Wazih Ahmed, Dr. M. A. Ansari ”A survey: Soft computing in Intelligent Information Retrieval Systems,” International Conference on Computational Science and Its Applications, IEEE 2012
  21. S. Kalaivani, K. Duraiswamy, ”Comparison of Question Answering Systems Based on Ontology and Semantic Web in Different Environment”, Journal of Computer Science 8 (9): 1407-1413, 2012
  22. Hany M. Harb, Khaled M. Fouad, Nagdy M. Nagdy, “Semantic Retrieval Approach for Web Documents”, (IJACSA) International Journal of Advanced Computer Science and Applications, 9, 2011
  23. Jianguo Jiang, Zhongxu Wang, Chunyan Liu, Zhiwen Tan, Xiaoze Chen, Min Li “The Technology of Intelligent Information Retrieval Based on the Semantic Web” 2nd International Conference on Signal Processing Systems (ICSPS), IEEE 2010
  24. Nicholas J. Belkin “Intelligent Information Retrieval: Whose Intelligence,” Department of Information Studies, University of Tampere
  25. LIU Yong-Min, CHENG Shu “Artificial Intelligent Information Retrieval Using Assigning Context of Documents,” International Conference on Networks Security, Wireless Communications and Trusted Computing, IEEE 2009
  26. Wenjie Li, Xiaohuan Zhang, Xiaofei Wei, “Semantic Web-Oriented Intelligent Information Retrieval System,” International Conference on BioMedical Engineering and Informatics, IEEE 2008
  27. Yi Xiao, Ming Xiao, Fan Jhang “Intelligent Information Retrieval Model Based on Multi-Agents,”, IEEE 2007
  28. Pan Ying, Wang Tianjiang, Jiang Xueling, “Building Intelligent Information Retrieval System Based on Ontology” The Eighth International Conference on Electronic Measurement and Instruments, IEEE 2007
  29. Tanveer J. Siddiqui, U. S. Tiwary “Integrating Notion of Agency and Semantic in Information Retrieval multi-agent model”, Proceeding of the 2005 5th International Conference on Intelligent Systems Design and Applications(ISDA’05) , IEEE 2005
  30. https://en.wikipedia.org/wiki/Precision_and_recall
Index Terms

Computer Science
Information Sciences

Keywords

Big Data Information Retrieval Data Mining Product Reviews Text Mining Sentiment Classification e-commerce

Powered by PhDFocusTM