A CLUSTERING ALGORITHM FOR DECOMPOSITION OF PROBABILISTIC LOGIC FORMULA SET
自然语言中时间信息的模型化

In order that the probabilistic logic reasoning under uncertainty can be used for large scale knowledge base, this paper presents a clustering algorithm for decomposition of probabilistic logic formula set based on the general consistence assigning algorithm for probabilistic logic and the experience of developing the knowledge base in an practical expert system. It ensures that the united model of Dantzig Wolfe decomposition can be used for probabilistic logic reasoning on probabilistic logic knowledge base with different background, provided the formula set hold certain hierarchical structure. Experiments show that the algorithm performs successfully on instances with dozens of variables and clauses.