Alignment Based Similarity distance Measure for Better Web Sessions Clustering | Zendy

G Poornalatha | Zendy; Prakash Raghavendra | Zendy

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Alignment Based Similarity distance Measure for Better Web Sessions Clustering

Author(s) -

G Poornalatha,

Prakash Raghavendra

Publication year - 2011

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2011.07.058

Subject(s) - computer science , measure (data warehouse) , cluster analysis , similarity (geometry) , similarity measure , data mining , the internet , information retrieval , web mining , popularity , web page , world wide web , machine learning , artificial intelligence , psychology , social psychology , image (mathematics)

The evolution of the internet along with the popularity of the web has attracted a great attention among the researchers to web usage mining. Given that, there is an exponential growth in terms of amount of data available in the web that may not give the required information immediately; web usage mining extracts the useful information from the huge amount of data available in the web logs that contain information regarding web pages accessed. Due to this huge amount of data, it is better to handle small group of data at a time, instead of dealing with entire data together. In order to cluster the data, similarity measure is essential to obtain the distance between any two user sessions. The objective of this paper is to propose a technique, to measure the similarity between any two user sessions based on sequence alignment technique that uses the dynamic programming method

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