A Pareto-dominant clustering approach for Pareto-frontiers

  • anaging large and confusing sets of increasing data is a well-known problem in Data Mining. Since compromises in many use cases like Recommender Systems or preference-based applications are becoming more and more usual, it is very useful to cluster sets of promising results in order to get an overview and present them properly. In this paper we present the Pareto-dominance as a very suitable and promising approach to cluster objects over better than relationships. In order to meet someones desires, one can tip the balance of the final results to the more favored dimension if no decision for allocating objects is possible.

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Author:Johannes KastnerGND, Markus EndresGND, Werner KießlingGND
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/59422
Parent Title (English):Nineteenth International Workshop on Design, Optimization, Languages and Analytical Processing of Big Data (DOLAP 2017), colocated with EDBT/ICDT 2017, Venice, Italy, March 21, 2017
Type:Conference Proceeding
Year of first Publication:2017
Release Date:2020/01/22
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Datenbanken und Informationssysteme