Title: Inducing probabilistic relational rules from probabilistic examples
Abstract: We study the problem of inducing logic programs in a probabilistic setting, in which both the example descriptions and their classification can be probabilistic. The setting is incorporated in the probabilistic rule learner ProbFOIL+, which combines principles of the rule learner FOIL with ProbLog, a probabilistic Prolog. We illustrate the approach by applying it to the knowledge base of NELL, the Never-Ending Language Learner.
Publication Year: 2015
Publication Date: 2015-07-25
Language: en
Type: article
Access and Citation
Cited By Count: 51
AI Researcher Chatbot
Get quick answers to your questions about the article from our AI researcher chatbot