Distributed and Parallel Databases

On Using a Warehouse to Analyze Web Logs

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Analyzing Web Logs for usage and access trends can not only provide important information to web site developers and administrators, but also help in creating adaptive web sites. While there are many existing tools that generate fixed reports from web logs, they typically do not allow ad-hoc analysis queries. Moreover, such tools cannot discover hidden patterns of access embedded in the access logs. We describe a relational OLAP (ROLAP) approach for creating a web-log warehouse. This is populated both from web logs, as well as the results of mining web logs. We discuss the design criteria that influenced our choice of dimensions, facts and data granularity. A web based ad-hoc tool for analytic queries on the warehouse was developed. We present some of the performance specific experiments that we performed on our warehouse.


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adaptive websites, data mining, data warehouse, ecommerce, web logs, web mining

InCollection

Springer

ISSN:0926-8782

13

Issue 2 (March

Downloads: 2369 downloads

Google Scholar Citations: 20 citations

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