Mutual information based clustering of market basket data for profiling users

Attraction and commercial success of web sites depend heavily on the additional values visitors may find. Here, individual, automatically obtained and maintained user profiles are the key for user satisfaction. This cont
Attraction and commercial success of web sites depend heavily on the additional values visitors may find. Here, individual, automatically obtained and maintained user profiles are the key for user satisfaction. This contribution shows for the example of a cooking information site how user profiles might be obtained using category information provided by cooking recipes. It is shown that metrical distance functions and standard clustering procedures lead to erroneous results. Instead, we propose a new mutual information based clustering approach and outline its implications for the example of user profiling.
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Metadaten
Author:Bartholomäus Ende, Rüdiger W. Brause
URN:urn:nbn:de:hebis:30-79251
Document Type:Article
Language:English
Date of Publication (online):2010/09/08
Year of first Publication:2007
Publishing Institution:Univ.-Bibliothek Frankfurt am Main
Release Date:2010/09/08
Source:in: IEEE 19th Int. Conf on Tools with Art. Intell. ICTAI-2007, Patras 2007, IEEE Press 2007
HeBIS PPN:228091292
Institutes:Informatik
E-Finance Lab e.V.
Dewey Decimal Classification:004 Datenverarbeitung; Informatik
Sammlungen:Universitätspublikationen
Licence (German):License Logo Veröffentlichungsvertrag für Publikationen

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