caa a22 4500 475799283 CHVBK 20180406123733.0 cr unu---uuuuu 170329e20000301xx s 000 0 eng 10.1023/A:1008740003826 doi (NATIONALLICENCE)springer-10.1023/A:1008740003826 Weber Irene Institut für Informatik, Universität Stuttgart, Breitwiesenstr. 20-22, 70565, Stuttgart, Germany aut Levelwise Search and Pruning Strategies for First-Order Hypothesis Spaces [Elektronische Daten] [Irene Weber] The discovery of interesting patterns in relational databases is an important data mining task. This paper is concerned with the development of a search algorithm for first-order hypothesis spaces adopting an important pruning technique (termed subset pruning here) from association rule mining in a first-order setting. The basic search algorithm is extended by so-called requires and excludes constraints allowing to declare prior knowledge about the data, such as mutual exclusion or generalization relationships among attributes, so that it can be exploited for further structuring and restricting the search space. Furthermore, it is illustrated how to process taxonomies and numerical attributes in the search algorithm. Several task settings using different interestingness criteria and search modes with corresponding pruning criteria are described. Three settings serve as test beds for evaluation of the proposed approach. The experimental evaluation shows that the impact of subset pruning is significant, since it reduces the number of hypothesis evaluations in many cases by about 50%. The impact of generalization relationships is shown to be less effective in our experimental set-up. Kluwer Academic Publishers, 2000 data mining nationallicence inductive logic programming nationallicence levelwise search nationallicence interesting pattern discovery nationallicence first order patterns nationallicence Journal of Intelligent Information Systems Kluwer Academic Publishers 14/2-3(2000-03-01), 217-239 0925-9902 14:2-3<217 2000 14 10844 https://doi.org/10.1023/A:1008740003826 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1023/A:1008740003826 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Weber Irene Institut für Informatik, Universität Stuttgart, Breitwiesenstr. 20-22, 70565, Stuttgart, Germany aut NATIONALLICENCE 773 0- Journal of Intelligent Information Systems Kluwer Academic Publishers 14/2-3(2000-03-01), 217-239 0925-9902 14:2-3<217 2000 14 10844 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer