Relational Clustering Based on a New Robust Estimator with Application to Web Mining
| dc.contributor.author | Nasraoui, Olfa | |
| dc.contributor.author | Krishnapuram, Raghu | |
| dc.contributor.author | Joshi, Anupam | |
| dc.date.accessioned | 2019-02-06T16:57:52Z | |
| dc.date.available | 2019-02-06T16:57:52Z | |
| dc.date.issued | 1999-10-24 | |
| dc.description | 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397) | en_US |
| dc.description.abstract | Mining typical user profiles and URL associations from the vast amount of access logs is an important component of Web personalization. In this paper, we define the notion of a ""user session" as being a temporally compact sequence of Web accesses by a user. We also define a dissimilarity measure between two Web sessions that captures the organization of a Web site. To cluster the user sessions based on the pairwise dissimilarities, we introduce the relational fuzzy c-maximal density estimator (RFC-MDE) algorithm. RFC-MDE is robust and can deal with outliers that are typical in this application. We show real examples of the use of RFC-MDE for extraction of user profiles from log data, and and compare its performance to the standard non-Euclidean fuzzy c-means. | en_US |
| dc.description.sponsorship | This work was partially supported by cooperative NSF awards (IIS 9801711 and IIS 9800899) to Joshi and Krishnapuram respectively, and an IBM faculty development award to A. Joshi. | en_US |
| dc.description.uri | https://ieeexplore.ieee.org/document/781785 | en_US |
| dc.format.extent | 5 pages | en_US |
| dc.genre | conference papers and proceedings preprints | en_US |
| dc.identifier | doi:10.13016/m2vo57-tumr | |
| dc.identifier.citation | Olfa Nasraoui, Raghu Krishnapuram, and Anupam Joshi, Relational Clustering Based on a New Robust Estimator with Application to Web Mining, 18th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.99TH8397), 1999, DOI: 10.1109/NAFIPS.1999.781785 | en_US |
| dc.identifier.uri | 10.1109/NAFIPS.1999.781785 | |
| dc.identifier.uri | http://hdl.handle.net/11603/12720 | |
| dc.language.iso | en_US | en_US |
| dc.publisher | IEEE | en_US |
| dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
| dc.relation.ispartof | UMBC Computer Science and Electrical Engineering Department Collection | |
| dc.relation.ispartof | UMBC Faculty Collection | |
| 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.rights | © 1999 IEEE | |
| dc.subject | web mining | en_US |
| dc.subject | uniform resource locators | en_US |
| dc.subject | data mining | en_US |
| dc.subject | noise robustness | en_US |
| dc.subject | pollution measurement | en_US |
| dc.subject | databases | en_US |
| dc.subject | search engines | en_US |
| dc.subject | information resources | en_US |
| dc.subject | pattern clustering | en_US |
| dc.subject | fuzzy set theory | en_US |
| dc.subject | relational algebra | en_US |
| dc.subject | data loggers | en_US |
| dc.subject | UMBC Ebiquity Research Group | en_US |
| dc.title | Relational Clustering Based on a New Robust Estimator with Application to Web Mining | en_US |
| dc.type | Text | en_US |