Personalized Nonlinear Ranking Using Full-text Preferences

  • Today Internet systems commonly use a total ranking to present search results. These rankings are typically cut off at arbitrary points which are hard to understand. In this paper we present a new approach for rankings based on partial orders, which model personal preferences. It naturally groups large result sets according to the quality of results and presents only the top ones. It is possible for the user to expand these result sets selectively along chains of the partial order. We expect a considerable gain in comprehensibility, clarity and user friendliness. A pilot application is being implemented and first encouraging evaluation results are reported.

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Metadaten
Author:Achim Leubner, Werner KießlingGND
URN:urn:nbn:de:bvb:384-opus4-1596
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/208
Series (Serial Number):Reports / Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg (1999-05)
Type:Report
Language:English
Publishing Institution:Universität Augsburg
Release Date:2006/06/08
Tag:Personalized Information Systems; Full-text Preferences; Nonlinear Ranking; Partial Orders; Preference SQL
GND-Keyword:Datenbanksystem; Personalisierung
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Datenbanken und Informationssysteme
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik