Efficient relational learning from sparse data

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Authors

POPELÍNSKÝ Lubomír

Year of publication 2002
Type Article in Proceedings
Conference Proceedings of AIMSA'02 Conference
MU Faculty or unit

Faculty of Informatics

Citation
Field Computer hardware and software
Keywords relational learning; database schema redesign; mining in spatial dat
Description This work deals with inductive inference of logic programs -relational learning - from examples. The work is, in the first place, application-oriented. It aims at building an easy-to-use relational learner and it focuses on the tasks that are solvable with the tool. Assumption-based learning, the new learning paradigm is introduced and the ABL system WiM is described. A methodology for experimental evaluation of ILP systems is introduced and experiments with WiM are displayed. Two classes of application -- database schema redesign and mining in spatial data - that have been successfully solved with WiM are described.
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