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Frequent Pattern Mining of Web Log Files Working Principles
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 157 - Number 3 |
| Year of Publication: 2017 |
| Authors: K. Suguna, K. Nandhini |
10.5120/ijca2017912642
|
K. Suguna, K. Nandhini . Frequent Pattern Mining of Web Log Files Working Principles. International Journal of Computer Applications. 157, 3 ( Jan 2017), 1-5. DOI=10.5120/ijca2017912642
Abstract
Frequent pattern mining plays a major role in mining of web log files. Web usage mining is the one of the web mining process that involves application of mining techniques to web server logs to extract the behavior of users. A web usage mining consists of three important phases: data preprocessing, patterns discovery and pattern analysis. In data preprocessing phase the unwanted data are removed and that are structured into necessary format for mining. It enables the user to translate the unprocessed data which is from server log files into useful data. The appropriate analysis of a web server log proves that the websites efficiently from the administrative and users’ prospective. Preprocessing results also more useful for the next phases of web usage mining.
References
- Jiawei Han and Michelin Kamber, “Datamining Concepts and Techniques”, Elsevier publication, Edition 2006.
- Rajan Chattamvelli, “Data Mining Methods”, Narosa publications, Edition 2009.
- Rahul Mishra and Abha Choubey, “FP from web log data using FP Growth for web usage mining”, ijarcsse publications, vol.2, Edition 2012.
- Christian Borgelt,”Implementation of FP Growth”, osdm publications,
- Santhosh Kumar and Rukumani ,” Implementation of Web Usage Mining Using Apriori And FP Growth Algorithm”, ijana publication, vol.1, pages 400-404, Edition 2010.
- Divya and Vinod Kumar,”AIS,Apriori and FP Tree Algorithm”, ijcsmr publication, vol.2, paper 30.
- Renáta Iváncsy and István Vajk,”Frequent Pattern Mining in Web Logs”,Vol.3,No.1,2006.
- Chen Wang, Mingsheng Hong, Jian Pei, Haofeng Zhou, Wei Wang and Baile Shi ,“Efficient Pattern Growth Method For Frequent Tree Pattern Mining”,Springer publication,2002.
- Jiaweihan, “Mining Frequent Pattern Without Candidate Generation:A Frequent-Pattern Tree Approach,Springer Publication,2004.
- Liping Sun and Xiuzhen Zhang, “Research and Application on Web Information Retrieval Based on Improved FP Growth Algorithm “,Springer publications, , Volume 11, Issue 5, pp 1065-1068, September 2006.
- Khattak M, KhanA. M., sungyoung lee*, andyoung-koo lee, Analyzing Association Rule Mining and Clustering on sales day Data with XLMiner and Weka
- Rajan Chattamvelli, “Data Mining Methods”, Narosa publications, Edition 2009.
- Jiawei Han, Ian Pei, Yiwen Tin, Runying Mao, “Mining Frequent Pattern without Candidate Generation: A Frequent Pattern Tree Approach”, Volume-8.
- Jian Pei, Jiawei Han, Behzad Mortazavi-asl, Hua Zhu, “Mining Access Pattern Efficient from Web Logs”
- J.Han and Kamber,”Data Mining: Concepts and Techniques”, Morgan Kaufman Publishers, 2000.
- Gomathi,sakthivel B”Implementing Fusion to Improve the Efficiency of Information Retrieval Using Clustering and Map Reduction”springer ,2016.
- WenfeiFan,Xin Wang, YinghuiWu, “Answering Pattern Queries Using Views”IEEE Feb-2016.
- Zhun (Jerry) Yu, Fariborz Haghighat, Benjamin C.M. Fung “Advances and challenges in building engineering and data mining applications for energy-efficient communities”Elsevier-2016.
- Wilson Castillo Rojasa, Fernando Medina Quispea, Claudio Meneses Villegasb “Augmented visualization for data-mining models”Elsevier-2015.
- Giulio Mattioli, Jillian Anable, Katerina Vrotsou,”Car dependent practices: Findings from a sequence pattern mining study of UK time use data”Elsevier-2016
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