Improving the efficiency of graph-based concept discovery systems

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2014
Abay, Nazmiye Ceren
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Concept discovery is a process for finding hidden relations from the given set of experiences named as background knowledge [27]. Concept discovery problems are investigated under Inductive Logic Programming (ILP)-based approaches and graph-based approaches [28]. Although ILP-based systems dominate the area, these systems have some problems such as local maxima and local plateaus [15]. Recently, graph based system becomes more popular due to its flexible structure, clear representation of data and ability of overcoming problems of ILP-based systems. Graph based approaches can be classified into two parts defined as structure-based approaches and path-finding approaches according to their methods they use for discovering concepts. The proposed approach can be classified as a combination of both path-finding approaches and methods of association rule mining. It finds paths between the arguments of target instances for concept discovery from the given graph. In addition to path-finding from given graph, association rule mining techniques are used for pruning based on support and confidence. The proposed method is different from the other path-finding approaches because association rule mining techniques are used for reducing search space and finding frequent and strong concept definitions.
Logic programming., Computer programming., Relational databases., Machine learning., Data mining.
http://etd.lib.metu.edu.tr/upload/12618287/index.pdf
https://hdl.handle.net/11511/24281
Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats
N. C. Abay, “Improving the efficiency of graph-based concept discovery systems,” M.S. - Master of Science, Middle East Technical University, 2014.
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