Specifying Mining Algorithms with Iterative User-Defined Aggregates
Giannotti F, Manco G, Turini F
User-defined aggregates Computational Theory and Mathematics Cons Constraint and logic languages Computer Science Applications Information Systems Data mining Association rules
We present a way of exploiting domain knowledge in the design and implementation of data mining algorithms, with special attention to frequent patterns discovery, within a deductive framework. In our framework, domain knowledge is represented by way of deductive rules, and data mining algorithms are specified by means of iterative user-defined aggregates and implemented by means of user-defined predicates. This choice allows us to exploit the full expressive power of deductive rules without loosing in performance. Iterative user-defined aggregates have a fixed scheme, in which user-defined predicates are to be added. This feature allows the modularization of data mining algorithms, thus providing a way to integrate the proper domain knowledge exploitation in the right point. As a case study, the paper presents how user-defined aggregates can be exploited to specify and implement a version of the a priori algorithm. Some performance analyzes and comparisons are discussed in order to show the effectiveness of the approach.
Source: IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING (PRINT), vol. 16 (issue 10), pp. 1232-1246
Metrics
Back to previous page
@article{oai:it.cnr:prodotti:169203,
title = {Specifying Mining Algorithms with Iterative User-Defined Aggregates},
author = {Giannotti F and Manco G and Turini F},
doi = {10.1109/tkde.2004.64},
year = {2004}
}
0000-0003-3099-3835