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Conclusions

There is a lot of redundancy in the computations performed by most ILP systems. In this paper we have identified a source of redundancy and proposed a method for avoiding it: execution of query packs. We have discussed how query pack execution can be incorporated in ILP systems. The query pack execution mechanism has been implemented in a new Prolog system called ILPROLOG and dedicated to data mining tasks, and two ILP systems have been re-implemented to make use of the mechanism. We have experimentally evaluated these re-implementations, and the results of these experiments confirm that large speedups may be obtained in this way. We conjecture that the query pack execution mechanism can be incorporated in other ILP systems and that similar speedups can be expected.

The problem setting in which query pack execution was introduced is very general, and allows the technique to be used for any kind of task where many queries are to be executed on the same data, as long as the queries can be organised in a hierarchy.

Future work includes further improvements to the ILPROLOG engine and the implementation of techniques that will increase the suitability of the engine to handle large data sets. In the best case one might hope to combine techniques known from database optimisation and program analysis with our pack execution mechanism to further improve the speed of ILP systems.



Subsections
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Hendrik Blockeel 2002-02-26