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dRAP-Independent: A Data Distribution Algorithm for Mining First-Order Frequent Patterns

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BLAŤÁK Jan POPELÍNSKÝ Lubomír

Rok publikování 2007
Druh Článek v odborném periodiku
Časopis / Zdroj Computing and Informatics
Fakulta / Pracoviště MU

Fakulta informatiky

Citace
Obor Informatika
Klíčová slova data mining; inductive logic programming; frequent patterns; distributed data mining
Popis In this paper we present drapi, an algorithm for independent distributed mining of first-order frequent pattern. This system is based on RAP, an algorithm for finding maximal frequent patterns in first-order logic. drapi utilizes a modified data partitioning schema introduced by Savasere et al. and offers good performance and low communication overhead. We analyze the performance of the algorithm on four different tasks: Mutagenicity prediction - a standard ILP benchmark, information extraction from biological texts, context-sensitive spelling correction, and morphological disambiguation of Czech. The results of the analysis show that the algorithm can generate more patterns than the serial algorithm RAP in the same overall time.
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