Dissertation/Thesis
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Modified Agglomerative Clustering for Web Users Navigation Behavior

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Modified Agglomerative Clustering for Web Users Navigation Behavior
Συγγραφείς: T. Mekala, P. Nandhini
Συνεισφορές: The Pennsylvania State University CiteSeerX Archives
Πηγή: http://www.ijana.in/papers/V5I1-6.pdf.
Συλλογή: CiteSeerX
Θεματικοί όροι: Web users clustering, Navigation, Access time
Περιγραφή: ABSTRACT --- Clustering is the task of finding natural partitioning within a data set such that data items within the same group are more similar than those within different groups. At present all available clustering techniques for web usage mining are based upon usage patterns derived from user’s page preferences. To improve the efficiency of usage pattern, the similarities in user’s access behavior based on time locality of user’s navigational acts are used. The tuning algorithm defines cluster that show similar visiting behavior at the same time period and users page preferences by varying the priority given to the time visit.
Τύπος εγγράφου: Thesis
Περιγραφή αρχείου: application/pdf
Γλώσσα: English
Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.8004
Διαθεσιμότητα: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.8004
http://www.ijana.in/papers/V5I1-6.pdf
Rights: Metadata may be used without restrictions as long as the oai identifier remains attached to it.
Αριθμός Καταχώρησης: edsbas.1BA6CB5
Βάση Δεδομένων: BASE
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  Data: ABSTRACT --- Clustering is the task of finding natural partitioning within a data set such that data items within the same group are more similar than those within different groups. At present all available clustering techniques for web usage mining are based upon usage patterns derived from user’s page preferences. To improve the efficiency of usage pattern, the similarities in user’s access behavior based on time locality of user’s navigational acts are used. The tuning algorithm defines cluster that show similar visiting behavior at the same time period and users page preferences by varying the priority given to the time visit.
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