International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 111 - Issue 13 |
Published: February 2015 |
Authors: Shivaprasad G., N.V. Subba Reddy, U. Dinesh Acharya |
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Shivaprasad G., N.V. Subba Reddy, U. Dinesh Acharya . Knowledge Discovery from Web Usage Data: An Efficient Implementation of Web Log Preprocessing Techniques. International Journal of Computer Applications. 111, 13 (February 2015), 27-32. DOI=10.5120/19600-1451
@article{ 10.5120/19600-1451, author = { Shivaprasad G.,N.V. Subba Reddy,U. Dinesh Acharya }, title = { Knowledge Discovery from Web Usage Data: An Efficient Implementation of Web Log Preprocessing Techniques }, journal = { International Journal of Computer Applications }, year = { 2015 }, volume = { 111 }, number = { 13 }, pages = { 27-32 }, doi = { 10.5120/19600-1451 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2015 %A Shivaprasad G. %A N.V. Subba Reddy %A U. Dinesh Acharya %T Knowledge Discovery from Web Usage Data: An Efficient Implementation of Web Log Preprocessing Techniques%T %J International Journal of Computer Applications %V 111 %N 13 %P 27-32 %R 10.5120/19600-1451 %I Foundation of Computer Science (FCS), NY, USA
Web Usage Mining (WUM) refers to extraction of knowledge from the web log data by application of data mining techniques. WUM generally consists of Web Log Preprocessing, Web Log Knowledge Discovery and Web Log Pattern Analysis. Web Log Preprocessing is a major and complex task of WUM. Elimination of noise and irrelevant data, thereby reducing the burden on the system leads to efficient discovery of patterns by further stages of WUM. In this paper, Web Log Preprocessing Methods to efficiently identify users and user sessions have been implemented and results have been analyzed.