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 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.

Publisher

IGI Global

Reference30 articles.

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

2. A Graph-Based Concept Discovery Method for n-Ary Relations

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

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3