Towards a Unified Supervised Approach for Ranking Triples of Type-Like Relations
نویسندگان
چکیده
Knowledge bases play a crucial role in modern search engines and provide users with information about entities. A knowledge base may contain many facts (i.e., RDF triples) about an entity, but only a handful of them are of significance for a searcher. Identifying and ranking these RDF triples is essential for various applications of search engines, such as entity ranking and summarization. In this paper, we present the first effort towards a unified supervised approach to rank triples from various type-like relations in knowledge bases. We evaluate our approach using the recently released test collections from the WSDM Cup 2017 and demonstrate the effectiveness of the proposed approach despite the fact that no relation-specific feature is used.
منابع مشابه
Supervised Ranking of Triples for Type-Like Relations - The Cress Triple Scorer at the WSDM Cup 2017
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