Semantic Web Dog Food

Presented at: 20th International World Wide Web Conference (WWW2011)

by Wei Shen, Jianyong Wang, Ping Luo, Min Wang, Conglei Yao

Relation extraction from Web data has attracted a lot of attention in recent years. However, little work has been done when it comes to relation extraction from enterprise data regardless of the urgent needs to such work in real applications (e.g., E-discovery). In this paper, we propose a novel unsupervised hybrid framework, called REACTOR (abbreviated for a fRamework for sEmantic relAtion extraCtion and Tagging Over enteRprise data). We evaluate REACTOR over a real-world enterprise data set and empirical results show the effectiveness of REACTOR.

REACTOR: A Framework for Semantic Relation Extraction and Tagging Over Enterprise Data was presented at this event.

Keywords: World Wide Web

Resource URI on the dog food server: http://data.semanticweb.org/conference/www/2011/poster/reactor-a-framework-for-semantic-relation-extracti

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