REACTOR: a framework for semantic relation extraction and tagging over enterprise data

Authors:
Wei Shen;Jianyong Wang;Ping Luo;Min Wang;Conglei Yao
Affiliations:
Tsinghua University, Beijing, China;Tsinghua University, Beijing, China;HP Labs China, Beijing, China;HP Labs China, Beijing, China;HP Labs China, Beijing, China
Venue:
Proceedings of the 20th international conference companion on World wide web
Year:
2011

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Abstract

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.