NDLI: An efficient model for information gain of sequential pattern from web logs based on dynamic weight constraint

Content Provider	IEEE Xplore Digital Library
Author	Jha, D.K. Rajput, A. Singh, M. Tomar, A.
Copyright Year	2010
Description	Author affiliation: Barkatullah University, Bhopal (M.P.), India (Rajput, A.) \|\| LNCT College, Bhopal (M.P.), India (Tomar, A.) \|\| Bansal College [CSE], Bhopal (M.P.), India (Jha, D.K.; Singh, M.)
Abstract	Data mining is the task of discovering interesting patterns from large amounts of data. There are many data mining tasks, such as classification, clustering, association rule mining, and sequential pattern mining. Many frequent sequential traversal pattern mining algorithms have been developed which mine the set of frequent subsequences traversal pattern satisfying a minimum support constraint in a session database. However, previous frequent sequential traversal pattern mining algorithms give equal weightage to sequential traversal patterns while the pages in sequential traversal patterns have different importance and have different weightage. Another main problem in most of the frequent sequential traversal pattern mining algorithms is that they produce a large number of sequential traversal patterns when a minimum support is lowered and they do not provide alternative ways to adjust the number of sequential traversal patterns other than increasing the minimum support. In this paper, we propose a frequent sequential traversal pattern mining with weights constraint. Our main approach is to add the weight constraints into the sequential traversal pattern while maintaining the downward closure property. A weight range is defined to maintain the downward closure property and pages are given different weights and traversal sequences assign a minimum and maximum weight. In scanning a session database, a maximum and minimum weight in the session database is used to prune infrequent sequential traversal subsequence by doing downward closure property can be maintained. Our method produces a few but important sequential traversal patterns in session databases with a low minimum support, by adjusting a weight range of pages and sequence.
Starting Page	518
Ending Page	523
File Size	232156
Page Count	6
File Format	PDF
ISBN	9781424478170
e-ISBN	9781424478187
DOI	10.1109/CISIM.2010.5643456
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-08
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Algorithm design and analysis Runtime Databases Heuristic algorithms Web usage mining Web pages Periodic Pattern Classification algorithms Data mining Weight constraint Sequential traversal Pattern Mining
Content Type	Text
Resource Type	Article

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