DoctorUnderstanding entity is important to solve many entity-related problems such as information retrieval, recommendation, and question answering. To help machines understand entities, knowledge bases have been constructed. However, these knowledge bases suffer from the incomplete problem. To solve this incomplete problem, we extract and add three interesting relationship types: 1) social, 2) comparable, and 3) verb relationships. For each relationship type, we propose a solution to extract relationships from external resource by utilizing knowledge bases. We also show their effectiveness empirically
International audienceThis paper describes a business relation extraction system that combines conte...
Much of the work on conceptual modeling involves the use of an entity-relationship model in which bi...
With popularization of Web, there are billions of pages on Web, which contain affluent information o...
Relation extraction is the task of ex-tracting predicate-argument relationships between entities fro...
A unified framework for knowledge base systems is proposed based on Entity-Relationship (ER) approac...
Knowledge bases like DBpedia, Yago or Google’s Knowledge Graph contain huge amounts of ontological k...
Relationship extraction is the task of extracting semantic relationships between en- tities from a t...
Abstract. We address the issue of extracting implicit and explicit relationships between entities in...
Relation linking is an important problem for knowledge graph-based Question Answering. Given a natur...
Abstract. Relationships are an integral part of conceptual database design because they represent as...
We address the issue of extracting implicit and explicit relationships between entities in biomedica...
Our research focuses on searching relations between entities with context constraints. In particular...
Relational learning, statistical relational models, statistical relational learning, relational data...
A traditional page link-based search system is not adequate for users intending to query data effici...
With popularization of Web, there are billions of pages on Web, which contain affluent information o...
International audienceThis paper describes a business relation extraction system that combines conte...
Much of the work on conceptual modeling involves the use of an entity-relationship model in which bi...
With popularization of Web, there are billions of pages on Web, which contain affluent information o...
Relation extraction is the task of ex-tracting predicate-argument relationships between entities fro...
A unified framework for knowledge base systems is proposed based on Entity-Relationship (ER) approac...
Knowledge bases like DBpedia, Yago or Google’s Knowledge Graph contain huge amounts of ontological k...
Relationship extraction is the task of extracting semantic relationships between en- tities from a t...
Abstract. We address the issue of extracting implicit and explicit relationships between entities in...
Relation linking is an important problem for knowledge graph-based Question Answering. Given a natur...
Abstract. Relationships are an integral part of conceptual database design because they represent as...
We address the issue of extracting implicit and explicit relationships between entities in biomedica...
Our research focuses on searching relations between entities with context constraints. In particular...
Relational learning, statistical relational models, statistical relational learning, relational data...
A traditional page link-based search system is not adequate for users intending to query data effici...
With popularization of Web, there are billions of pages on Web, which contain affluent information o...
International audienceThis paper describes a business relation extraction system that combines conte...
Much of the work on conceptual modeling involves the use of an entity-relationship model in which bi...
With popularization of Web, there are billions of pages on Web, which contain affluent information o...