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A Comparative Analysis of Web Usage Mining Techniques

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Paridhi Nigam, Rajesh K. Chakrawarti
10.5120/ijca2016911790

Paridhi Nigam and Rajesh K Chakrawarti. A Comparative Analysis of Web Usage Mining Techniques. International Journal of Computer Applications 152(5):26-29, October 2016. BibTeX

@article{10.5120/ijca2016911790,
	author = {Paridhi Nigam and Rajesh K. Chakrawarti},
	title = {A Comparative Analysis of Web Usage Mining Techniques},
	journal = {International Journal of Computer Applications},
	issue_date = {October 2016},
	volume = {152},
	number = {5},
	month = {Oct},
	year = {2016},
	issn = {0975-8887},
	pages = {26-29},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume152/number5/26316-2016911790},
	doi = {10.5120/ijca2016911790},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Web usage mining is the application of data mining techniques and is used to extract the important data which are present in the web. Nowadays web log mining is a very popular and computationally expensive task. Preprocessing, pattern discovery, and pattern analysis are the major task of web usage mining. In this paper we are presenting an overview of existing algorithms used in pattern discovery phase for mining the frequent item set by designing comparative analysis table i.e. Apriori, K-Apriori, FP growth which are used in pattern discovery phase.

References

  1. Suhasini Parvatikar, Bharti Joshi, “Analysis of User Behavior through Web Usage Mining”, Department of Computing.
  2. R. Kousalya, V Sarvanan, “Improving efficiency of Web Usage Mining using K-Apriori and Fp-Growth Algorithm”
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  4. Li Chaofeng School of Management, “Research and Development of Data Preprocessing in Web Usage,” South-Central University for Nationalities ,Wuhan 430074, P.R. China.
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Keywords

Web mining; Web log mining; Apriori; K-Apriori; FP growth;