Strategies to Parallelize ILP Systems
Strategies to Parallelize ILP Systems
复制标题
ILP 系统并行化策略
DOI：
10.1007/11536314_9
复制
发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Rui Camacho
中科院分区：
文献类型：
--
作者：
N.A. Fonseca;Fernando M A Silva;Rui Camacho
归纳逻辑编程（ILP）实践者众所周知，ILP 系统通常需要很长时间才能找到有价值的模型（理论）。这个问题对于大型数据集尤其严重，阻止 ILP 系统扩展到更大的应用程序。减少执行时间的一种方法是 ILP 系统的并行化。在本文中，我们概述了并行 ILP 实现的最新技术，并介绍了一些主要 ILP 并行化策略的评估工作。提出了有关每种策略的适用性的结论。
It is well known by Inductive Logic Programming (ILP) practioners that ILP systems usually take a long time to find valuable models (theories). The problem is specially critical for large datasets, preventing ILP systems to scale up to larger applications. One approach to reduce the execution time has been the parallelization of ILP systems. In this paper we overview the state-of-the-art on parallel ILP implementations and present work on the evaluation of some major parallelization strategies for ILP. Conclusions about the applicability of each strategy are presented.