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Information Resources Management Association
Advancing the Concepts & Practices of Information Resources Management in Modern Organizations

Graph-Based Concept Discovery

Graph-Based Concept Discovery
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Author(s): Alev Mutlu (Kocaeli University, Turkey), Pinar Karagoz (Middle East Technical University, Turkey) and Yusuf Kavurucu (Turkish Naval Research Center Command, Turkey)
Copyright: 2018
Pages: 10
Source title: Encyclopedia of Information Science and Technology, Fourth Edition
Source Author(s)/Editor(s): Mehdi Khosrow-Pour, D.B.A. (Information Resources Management Association, USA)
DOI: 10.4018/978-1-5225-2255-3.ch171


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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 paper, we 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.

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