Warehousing and Mining Web Logs
Links to Fileshttps://dl.acm.org/citation.cfm?id=319792
MetadataShow full item record
Type of Work6 pages
conference papers and proceedings
Citation of Original PublicationKaruna Pande Joshi, Anupam Joshi, Yelena Yesha, and Raghu Krishnapuram, Warehousing and Mining Web Logs, Workshop on Web Information and Data Management, 1999 ACM Conference on Information and Knowledge Management (CIKM'99), DOI: 10.1145/319759.319792
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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 also present a web based ad-hoc tool for analytic queries on the warehouse. We discuss the design criteria that influenced our choice of dimensions, facts and data granularity, and present the results from analyzing and mining the logs.