Efficient Data Mining for Path Traversal Patterns
Journal
IEEE Transactions on Knowledge and Data Engineering
Journal Volume
10
Journal Issue
2
Pages
209-221
Date Issued
1998
Date
1998
Author(s)
Abstract
In this paper, we explore a new data mining capability that involves mining path traversal patterns in a distributed information-providing environment where documents or objects are linked together to facilitate interactive access. Our solution procedure consists of two steps. First, we derive an algorithm to convert the original sequence of log data into a set of maximal forward references. By doing so, we can filter out the effect of some backward references, which are mainly made for ease of traveling and concentrate on mining meaningful user access sequences. Second, we derive algorithms to determine the frequent traversal patterns - i.e., large reference sequences - from the maximal forward references obtained. Two algorithms are devised for determining large reference sequences; one is based on some hashing and pruning techniques, and the other is further improved with the option of determining large reference sequences in batch so as to reduce the number of database scans required. Performance of these two methods is comparatively analyzed. It is shown that the option of selective scan is very advantageous and can lead to prominent performance improvement. Sensitivity analysis on various parameters is conducted. © 1998 IEEE.
Subjects
Data mining; Distributed information system; Performance analysis; Traversal patterns; World Wide Web
Other Subjects
Algorithms; Database systems; Distributed computer systems; Interactive computer systems; Online systems; Sensitivity analysis; Wide area networks; Data mining; Distributed information system; Traversal patterns; World wide web; Data acquisition
Type
journal article
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