Çizge tabanlı kavram keşfi sistemlerinin verimliliğinin artırılması.

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.M.S. - Master of Scienc