Title
Distant Supervision for Relation Extraction Using Tree Kernels.
Abstract
In this paper we define a simple Relation Extraction system based on SVMs using tree kernels and employing a weakly supervised approach, known as Distant Supervision (DS). Our method uses the simple one-versus-all strategy to handle overlapping relations, i.e., defined on the same pair of entities. The DS data is defined over the New York Times corpus by means of Freebase as an external knowledge base, which indicates the relations of some of the entities of the NYT text. Our experiments show that our simple approach performs well in this domain with respect to the current state of the art.
Year
Venue
Field
2015
IIR
Data mining,Pattern recognition,Computer science,Support vector machine,Tree kernel,Artificial intelligence,Knowledge base,Machine learning,Relationship extraction
DocType
Citations 
PageRank 
Conference
1
0.36
References 
Authors
13
2
Name
Order
Citations
PageRank
Azad Abad131.39
Alessandro Moschitti23262177.68