Warehousing and Mining Web Logs
| dc.contributor.author | Joshi, Karuna P. | |
| dc.contributor.author | Joshi, Anupam | |
| dc.contributor.author | Yesha, Yelena | |
| dc.contributor.author | Krishnapuram, Raghu | |
| dc.date.accessioned | 2019-02-01T16:18:54Z | |
| dc.date.available | 2019-02-01T16:18:54Z | |
| dc.date.issued | 1999-11-02 | |
| dc.description | WIDM '99 Proceedings of the 2nd international workshop on Web information and data management | |
| dc.description.abstract | 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. | en_US |
| dc.description.sponsorship | This work was partially supported by cooperative NSF awards (IIS 9801711 & IIS 980089) to Joshi and Krishnapuram respectively. | en_US |
| dc.description.uri | https://dl.acm.org/citation.cfm?id=319792 | en_US |
| dc.format.extent | 6 pages | en_US |
| dc.genre | conference papers and proceedings | en_US |
| dc.genre | preprints | |
| dc.identifier | doi:10.13016/m2ljgs-irux | |
| dc.identifier.citation | Karuna 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 | en_US |
| dc.identifier.uri | 10.1145/319759.319792 | |
| dc.identifier.uri | http://hdl.handle.net/11603/12686 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | ACM | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Information Systems Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department | |
| dc.rights | This item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author. | |
| dc.subject | web mining | en_US |
| dc.subject | clustering | en_US |
| dc.subject | user interface | en_US |
| dc.subject | ad hoc analysis | en_US |
| dc.subject | web logs | en_US |
| dc.subject | UMBC Ebiquity Research Group | en_US |
| dc.title | Warehousing and Mining Web Logs | en_US |
| dc.type | Text | en_US |