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ICDM
2008
IEEE

Generalized Framework for Syntax-Based Relation Mining

8 years 10 months ago
Generalized Framework for Syntax-Based Relation Mining
Supervised approaches to Data Mining are particularly appealing as they allow for the extraction of complex relations from data objects. In order to facilitate their application in different areas, ranging from protein to protein interaction in bioinformatics to text mining in computational linguistics research, a modular and general mining framework is needed. The major constraint to the generalization process concerns the feature design for the description of relational data. In this paper, we present a machine learning framework for the automatic mining of relations, where the target objects are structurally organized in a tree. Object types are generalized by means of the use of roles, whereas the relation properties are described by means of the underlying tree structure. The latter is encoded in the learning algorithm thanks to kernel methods for structured data, which represent structures in terms of their all possible subparts. This approach can be applied to any kind of data ...
Bonaventura Coppola, Alessandro Moschitti, Daniele
Added 30 May 2010
Updated 30 May 2010
Type Conference
Year 2008
Where ICDM
Authors Bonaventura Coppola, Alessandro Moschitti, Daniele Pighin
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