Web Mining for Personalization: A Survey in the Fuzzy Framework

Authors

  • Noopur Saxena
  • Bineet kr Gupta
  • Himanshu Pandey
  • Prabhat Kr Singh

Keywords:

web mining, personalization, fuzzy, clustering

Abstract

Web mining is the use of data mining techniques to automatically discover and extract information from Web documents and services. When comparing web mining with traditional data mining, there are three main differences to consider: Scale, Access and Structure. Web personalization is the process of tailoring content that web user experiences according to his needs, goals and preferences. In this survey paper we have discussed various researches done in the field of web mining for personalization in last fifteen which used fuzzy as their framework for study. We also discussed a fuzzy c-means clustering algorithm which we will consider in our further research.

References

Dragos Arotariteia, Sushmita Mitrab, “Web mining: a survey in the fuzzy frameworkâ€. Elsevier- Fuzzy Sets and Systems, 2004.

Fernando Crespoa, Richard Weberb, “A methodology for dynamic data mining based on fuzzy clusteringâ€. Elsevier- Fuzzy Sets and Systems, March ,2004.

Raghu Krishnapuram, , Anupam Joshi, Olfa Nasraoui, “Low-Complexity Fuzzy Relational Clustering Algorithms for Web Miningâ€. IEEE Transactions on fuzzy systems, Vol 9, No. 4, August 2001.

Chunlai Chai, Biwei Li, “A Novel Association Rules Method Based on Genetic Algorithm and Fuzzy Set Strategy for Web Miningâ€. Journal of computers, Vol. 5, No. 9, September 2010.

. Sendhilkumar, K. Selvakumar and G.S. Mahalakshmi, “Applications of fuzzy logic for user classification in personalized webâ€. International Journal on Cybernetics & Informatics (IJCI) Vol. 3, No. 3, June 2014.

Suruchi Chawla,†Clusterwise optimization of clicked web pages using Genetic algorithm for effective Personalized Web Search†International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 4, Issue 1, January – February 2015.

Setu Kumar Chaturvedi , Deepak Kumar Niware ,†Web Usage Mining through Efficient Genetic Fuzzy C-Meansâ€. IJCSNS International Journal of Computer Science and Network Security, VOL.14 No.6, June 2014.

Anupam Joshi, Raghu Krishnapuram, “Robust Fuzzy Clustering Methods to Support Web Miningâ€. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.41.4287&rep=rep1&type=pdf

Kyung-Joong Kim , Sung-Bae Cho, “Personalized mining of web documents using link structures and fuzzy concept networksâ€. Elsevier- Fuzzy Sets and Systems ,September 2005.

Neelam Sain, Prof. Sitendra Tamrakar, “A Survey of Web Usage Mining based on Fuzzy Clustering and HMMâ€. (IJCSIT) International Journal of Computer Science and Information Technologies, Vol. 3 (4) , 2012.

Dibya Jyoti Bora, Dr. Anil Kumar Gupta, “A Comparative study Between Fuzzy Clustering Algorithm and Hard Clustering Algorithmâ€. International Journal of Computer Trends and Technology (IJCTT) – volume 10 number 2 – Apr 2014.

M.S.. Yang, “A Survey of Fuzzy Clusteringâ€. Mathl. Comput. Modelling Vol. 18, No. 11, pp. 1-16, 1993, Great Britain.

K. M. Bataineh,a, M. Najia, M. Saqera , “A Comparison Study between Various Fuzzy Clustering Algorithmsâ€. 343 Jordan Journal of Mechanical and Industrial Engineering, Volume 5, Number 4, Aug. 2011.

Md. Ehsanul Karim, Feng Yun, Sri Phani Venkata Siva Krishna Madani, “Fuzzy Clustering Analysisâ€. Thesis in Mathematical Modelling and Simulation , Blekinge institute of technology,2010-august.

Leehter Yao and Kuei-Sung Weng, “On A Type-2 Fuzzy Clustering Algorithmâ€. PATTERNS 2012: The Fourth International Conferences on Pervasive Patterns and Applications.

,[16] James C Bedzec, Roberst Ehrlich, William Full, â€FCM : The fuzzy c- means clustering algorithmâ€. Computers and geosciences, vol. 10 , no. 2-3, 1984, USA.

Pooja Mehtaa, Brinda Parekh, Kirit Modi, and Paresh Solanki,†Web Personalization Using Web Mining: Concept and Research Issueâ€. International Journal of Information and Education Technology, Vol. 2, No. 5, October 2012.

Mr. Ankit R. Deshmukh, Prof. Sunil R. Gupta,†DATA MINING BASED SOFT COMPUTING METHODS FOR WEB INTELLIGENCEâ€, International Journal of Application or Innovation in Engineering & Management (IJAIEM), Volume 3, Issue 3, March 2014.

M. Gomathi ,†A Survey on Web Mining Using Fuzzy Logicâ€, International Journal of Advanced Research in Computer Science and Software Engineering,Volume 5, Issue 3, March 2015.

Fernando Crespoa, Richard Weberb,†A methodology for dynamic data mining based on fuzzy clusteringâ€, Elsevier- science direct, Fuzzy Sets and Systems 150 (2005) 267–284.

María J. Martín-Bautista, María-Amparo Vila, “Obtaining user profiles via web usage miningâ€, IADIS European Conference Data Mining, Granada (Spain),2008.

Bo Pang and Lillian Lee, “Opinion Mining and Sentiment Analysis “. Foundations and Trends in Information Retrieval ,Vol. 2, Nos. 1–2 ,2008 .

Limin Ren, “ Research of Web Data Mining Based on Fuzzy Logic and Neural Networksâ€. IEEE: Fuzzy Systems and Knowledge Discovery FSKD’09,Vol. 3, 2009.

Binu Thomas and G. Raju, “A Novel Web Classification Algorithm Using Fuzzy Weighted Association Rulesâ€. Article in ISRN Artificial Intelligence Volume 2013, Hindawi Publishing Corporation – 2013.

Pawan Lingras, Chad West, “Interval Set Clustering of Web Users with Rough K –Meansâ€. Journal of Intelligent Information Systems, Springer ,Volume 23, Issue 1, July 2004.

Francisco Herrera, “Genetic fuzzy systems: taxonomy, current research trends and prospectsâ€. Evolutionary Intelligence – Springer, Volume 1, Issue 1, pp 27-46, March 2008.

Qingyu Zhang and Richard S. Segall, “Web mining “ a survey of current research , techniques, and softwareâ€. Article in KYBERNETES , MAY 2010.

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How to Cite

Saxena, N., Gupta, B. kr, Pandey, H., & Singh, P. K. (2016). Web Mining for Personalization: A Survey in the Fuzzy Framework. Asian Journal of Computer and Information Systems, 4(1). Retrieved from https://www.ajouronline.com/index.php/AJCIS/article/view/3619

Issue

Vol. 4 No. 1 (2016): February 2016

Section

Articles

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