Mining Semantic Networks for Knowledge Discovery

Authors:
K. Rajaraman;Ah-Hwee Tan
Affiliations:
-;-
Venue:
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Year:
2003

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Abstract

This paper addresses the problem of mining a class ofsemantic networks, called Concept Frame Graphs (CFG's),for knowledge discovery from text. This new representationis motivated by the need to capture richer text content sothat non-trivial mining tasks can be performed. We firstdefine the CFG representation and then describe a rule-basedalgorithm for constructing a CFG from text documents.Treating the CFG as a networked knowledge base,we propose new methods for text mining. On a specific taskof discovering the top companies in an area, we observe thatour approach leads to simpler content mining algorithms,once the CFG has been constructed. Moreover, exploitingthe network structure of CFG results in significant improvementsin precision and recall.