Video suggestion and discovery for youtube: taking random walks through the view graph
Proceedings of the 17th international conference on World Wide Web
Entity categorization over large document collections
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
A graph-based approach for ontology population with named entities
Proceedings of the 21st ACM international conference on Information and knowledge management
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Automatically populating ontology with named entities extracted from the unstructured text has become a key issue for Semantic Web. This issue naturally consists of two subtasks: (1) for the entity mention whose mapping entity does not exist in the ontology, attach it to the right category in the ontology (i.e., fine-grained named entity classification), and (2) for the entity mention whose mapping entity is contained in the ontology, link it with its mapping real world entity in the ontology (i.e., entity linking). Previous studies only focus on one of the two subtasks. This paper proposes APOLLO, a general weakly supervised frAmework for POpuLating ontoLOgy with named entities. APOLLO leverages the rich semantic knowledge embedded in the Wikipedia to resolve this task via random walks on graphs. An experimental study has been conducted to show the effectiveness of APOLLO.