<reponame>FudanYuan/neo4j
{"title": "Estimating Rule Quality for Knowledge Base Completion with the Relationship between Coverage Assumption.", "fields": ["open world assumption", "learning theory", "definite clause grammar", "truth value", "knowledge base"], "abstract": "Currently, there are many large, automatically constructed knowledge bases (KBs). One interesting task is learning from a KB to generate new knowledge either in the form of inferred facts or rules that define regularities. One challenge for learning is that KBs are necessarily open world: we cannot assume anything about the truth values of facts not included in the KB. From a learning perspective, this means we lack negative examples. To address this problem, we propose a novel score function for evaluating the quality of a first-order definite clause learned from a KB. Our metric attempts to include information about the facts not in the KB when evaluating the quality of a potential rule. Empirically, we find that our metric results in more precise predictions than previous approaches.", "citation": "Citations (3)", "departments": ["University of Ljubljana", "Katholieke Universiteit Leuven"], "authors": ["<NAME>.....http://dblp.org/pers/hd/z/Zupanc:Kaja", "<NAME>.....http://dblp.org/pers/hd/d/Davis:Jesse"], "conf": "www", "year": "2018", "pages": 9}