Graph-Based Concept Discovery

Author:

Mutlu Alev1,Karagoz Pinar2ORCID,Kavurucu Yusuf3

Affiliation:

1. Kocaeli University, Turkey

2. Middle East Technical University, Turkey

3. Turkish Naval Research Center Command, Turkey

Abstract

Multi-relational data mining (MRDM) is concerned with discovering hidden patterns from multiple tables in a relational database. One of the most commonly addressed tasks in MRDM is concept discovery in which the problem is inducing logical definitions of a specific relation, called target relation, in terms of other relations, called background knowledge. Inductive logic programming-based and graph-based approaches are two main competitors in this research. In this chapter, the authors aim to introduce concept discovery problem and compare state-of-the-art methods in graph-based concept discovery by means of data representation, search method, and concept descriptor evaluation mechanism.

Publisher

IGI Global

Reference30 articles.

1. A path-finding based method for concept discovery in graphs

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3. The minimum description length principle in coding and modeling. Information Theory;A.Barron;IEEE Transactions on,1998

4. Improving parallelism in structural data mining;M.Cai;Parallel Processing and Applied Mathematics,2005

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