BLAŤÁK, Jan and Lubomír POPELÍNSKÝ. dRAP: A Framework for Distributed Mining Firts-Order Frequent Patterns. In 16th International Conference on Inductive Logic Programming. 1st ed. Santiago de Compostela, Spain: University of Coruna, 2006, p. 25-27. ISBN 84-9749-206-4.
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Basic information
Original name dRAP: A Framework for Distributed Mining Firts-Order Frequent Patterns
Name in Czech dRAP: Systém pro distribuované dolování prvořádových častých vzorů
Name (in English) dRAP: A Framework for Distributed Mining Firts-Order Frequent Patterns
Authors BLAŤÁK, Jan (203 Czech Republic, guarantor) and Lubomír POPELÍNSKÝ (203 Czech Republic).
Edition 1. vyd. Santiago de Compostela, Spain, 16th International Conference on Inductive Logic Programming, p. 25-27, 3 pp. 2006.
Publisher University of Coruna
Other information
Original language Czech
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
RIV identification code RIV/00216224:14330/06:00017160
Organization unit Faculty of Informatics
ISBN 84-9749-206-4
Keywords in English inductive logic programming; parallel and distributed mining
Tags inductive logic programming, parallel and distributed mining
Changed by Changed by: doc. RNDr. Lubomír Popelínský, Ph.D., učo 1945. Changed: 1/1/2007 17:19.
Abstract
In this paper dRAP, a framework for distributed mining first-order frequent patterns is presented. It extends the RAP system for running on parallel shared-nothing architecture. It utilizes several well-known methods for parallel mining propositional frequent patterns and new algorithm that minimizes communication overhead. We show that the new algorithm require significantly smaller number of messages passed than the other methods.
Abstract (in English)
In this paper dRAP, a framework for distributed mining first-order frequent patterns is presented. It extends the RAP system for running on parallel shared-nothing architecture. It utilizes several well-known methods for parallel mining propositional frequent patterns and new algorithm that minimizes communication overhead. We show that the new algorithm require significantly smaller number of messages passed than the other methods.
Links
MSM0021622418, plan (intention)Name: DYNAMICKÁ GEOVIZUALIZACE V KRIZOVÉM MANAGEMENTU
Investor: Ministry of Education, Youth and Sports of the CR, Dynamic Geovisualisation in Crises Management
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