Int. J. of Information Technology and Management   »   2015 Vol.14, No.2/3

 

 

Title: A distributed maximal frequent itemset mining with multi agents system on bitmap join indexes selection

 

Authors: Hamid Necir; Habiba Drias

 

Addresses:
Research Laboratory in Artificial Intelligence (LRIA), Department of Computer Science, Faculty of Electrical and Computer Science, University Science and Technology Houari Boumediene (USTHB), El Alia BP 32, Bab Ezzouar, Algiers, 00332021751555, Algeria
Research Laboratory in Artificial Intelligence (LRIA), Department of Computer Science, Faculty of Electrical and Computer Science, University Science and Technology Houari Boumediene (USTHB), El Alia BP 32, Bab Ezzouar, Algiers, 00332021751555, Algeria

 

Abstract: The amount of information in a data warehouse tends to be extremely large and queries may involve several complex join and aggregate operations at the same time. By using the right indices, the database administrator can speed up these OLAP queries and dramatically shorten processing times. However, selection of an optimal set of indices is a very hard task because of the exponential number of attribute candidates that can be used in the selection process. Addressing this problem, we propose a new approach with two main phases. The first involves pruning the search space to reduce the number of indices candidates. To that end, we use a distributed maximal itemsets mining approach based on a multi agent system that can significantly reduce the complexity of the selection process. We also incorporate a convertible anti-monotone constraint that contains information on the profit of index. The second phase uses also a multi agent's architecture to select final indices using a subset of attribute candidates. This final configuration will provide benefit to OLAP queries, but will also respect the disk space constraint. We validate our proposed approach using an experimental evaluation.

 

Keywords: bitmap join indices; BJIs; data mining; data warehouse; multi-agent systems; MAS; agent-based systems; distributed itemsets; maximal frequent itemset mining; OLAP queries; disk space constraints.

 

DOI: 10.1504/IJITM.2015.068470

 

Int. J. of Information Technology and Management, 2015 Vol.14, No.2/3, pp.201 - 214

 

Available online: 18 Mar 2015

 

 

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