Conference Papers
Permanent URI for this collectionhttps://idr.nitk.ac.in/handle/123456789/28506
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Item Web user session clustering using modified K-means algorithm(2011) Poornalatha, G.; Raghavendra, P.S.The proliferation of internet along with the attractiveness of the web in recent years has made web mining as the research area of great magnitude. Web mining essentially has many advantages which makes this technology attractive to researchers. The analysis of web user's navigational pattern within a web site can provide useful information for applications like, server performance enhancements, restructuring a web site, direct marketing in e-commerce etc. The navigation paths may be explored based on some similarity criteria, in order to get the useful inference about the usage of web. The objective of this paper is to propose an effective clustering technique to group users' sessions by modifying K-means algorithm and suggest a method to compute the distance between sessions based on similarity of their web access path, which takes care of the issue of the user sessions that are of variable length. © 2011 Springer-Verlag.Item Clustering web page sessions using sequence alignment method(2011) Poornalatha, G.; Raghavendra, S.R.This paper illustrates clustering of web page sessions in order to identify the users' navigation pattern. In the approach presented here, user sessions of variable lengths are compared pair wise, numbers of alignments are found between them and the distances are measured. Web page sessions are clustered by employing the modified k-means algorithm. A couple of web access logs including the well known NASA data set are used to illustrate the effectiveness of the clustering. R-squared measure is applied to determine the optimal number of clusters and chi-squared test is carried out to see the association between the various web page sessions that are clustered. These two measures show the goodness of the clusters formed. © 2011 Springer-Verlag.