Current literature offers a number of different approaches to what could generally be called “probabilistic logic programming”. These are usually based on Horn clauses. Here, ...
Joost Vennekens, Sofie Verbaeten, Maurice Bruynoog...
We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. denite clause programs containing probabilistic facts with a ...
Probabilistic Logic Programming is an active field of research, with many proposals for languages, semantics and reasoning algorithms. One such proposal, Logic Programming with A...
The K framework, based on rewriting logic semantics, provides a powerful logic for defining the semantics of programming languages. While most work in this area has focused on de...
In this paper, we propose an information retrieval model called Latent Interest Semantic Map (LISM), which features retrieval composed of both Collaborative Filtering(CF) and Prob...