Clustering web page sessions using sequence alignment method

G. Poornalatha; S. Raghavendra Prakash

doi:10.1007/978-3-642-25734-6_79

Clustering web page sessions using sequence alignment method

G. Poornalatha, S. Raghavendra Prakash

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

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.

Original language	English
Title of host publication	Computational Intelligence and Information Technology - First International Conference, CIIT 2011, Proceedings
Pages	479-483
Number of pages	5
Volume	250 CCIS
DOIs	https://doi.org/10.1007/978-3-642-25734-6_79
Publication status	Published - 2011
Event	1st International Conference on Computational Intelligence and Information Technology, CIIT 2011 - Pune, India Duration: 07-11-2011 → 08-11-2011

Publication series

Name	Communications in Computer and Information Science
Volume	250 CCIS
ISSN (Print)	1865-0929

Conference

Conference	1st International Conference on Computational Intelligence and Information Technology, CIIT 2011
Country/Territory	India
City	Pune
Period	07-11-11 → 08-11-11

All Science Journal Classification (ASJC) codes

Computer Science(all)

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10.1007/978-3-642-25734-6_79

Cite this

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title = "Clustering web page sessions using sequence alignment method",

abstract = "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.",

author = "G. Poornalatha and Prakash, {S. Raghavendra}",

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note = "1st International Conference on Computational Intelligence and Information Technology, CIIT 2011 ; Conference date: 07-11-2011 Through 08-11-2011",

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Poornalatha, G & Prakash, SR 2011, Clustering web page sessions using sequence alignment method. in Computational Intelligence and Information Technology - First International Conference, CIIT 2011, Proceedings. vol. 250 CCIS, Communications in Computer and Information Science, vol. 250 CCIS, pp. 479-483, 1st International Conference on Computational Intelligence and Information Technology, CIIT 2011, Pune, India, 07-11-11. https://doi.org/10.1007/978-3-642-25734-6_79

Clustering web page sessions using sequence alignment method. / Poornalatha, G.; Prakash, S. Raghavendra.
Computational Intelligence and Information Technology - First International Conference, CIIT 2011, Proceedings. Vol. 250 CCIS 2011. p. 479-483 (Communications in Computer and Information Science; Vol. 250 CCIS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Prakash, S. Raghavendra

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N2 - 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.

AB - 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.

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Clustering web page sessions using sequence alignment method

Abstract

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All Science Journal Classification (ASJC) codes

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