Temporal web log mining using olap techniques
ICCMSE '03 Proceedings of the international conference on Computational methods in sciences and engineering
Incremental click-stream tree model: Learning from new users for web page prediction
Distributed and Parallel Databases
Efficient algorithms for incremental maintenance of closed sequential patterns in large databases
Data & Knowledge Engineering
Sequential pattern mining -- approaches and algorithms
ACM Computing Surveys (CSUR)
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Enterprise-class web sites receive a large amountof traffic, from both registered and anonymous users.Data warehouses are built to store and help analyze the click streams within this traffic to providecompanies with valuable insights into the behaviorof their customers. This article proposes a parallelsequence mining algorithm, webSPADE, to analyzethe click streams found in site web logs. In this process, raw web logs are first cleaned and inserted intoa data warehouse. The click streams are then minedby webSPADE. An innovative web-based front-endis used to visualize and query the sequence miningresults. The webSPADE algorithm is currently usedby Verizon to analyze the daily traffic of the Verizon.com web site.