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

Abay, Nazmiye Ceren
Karagöz, Pınar
Concept discovery is a multi-relational data mining task for inducing definitions of a specific relation in terms of other relations in the data set. Such learning tasks usually have to deal with large search spaces and hence have efficiency and scalability issues. In this paper, we present a hybrid approach that combines association rule mining methods and graph-based approaches to cope with these issues. The proposed method inputs the data in relational format, converts it into a graph representation, and traverses the graph to find the concept descriptors. Graph traversal and pruning are guided based on association rule mining techniques. The proposed method distinguishes from the state-of-the art methods as it can work on n-ary relations, it uses path finding queries to extract concepts and can handle numeric values. Experimental results show that the method is superior to the state-of-the art methods in terms of accuracy and the coverage of the induced concept descriptors and the running time.


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In the multi-relational data mining, concept discovery is the problem of inducing definitions of a relation in terms of other relations provided. In this paper, we present a method that combines graph-based and association rule mining-based methods for concept discovery in graphs. The proposed method is related to graphs as the data, which is initially stored in a relational database, is represented as a graph and concept descriptors are the paths that connect certain vertices; and it is related to associat...
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Concept discovery systems are concerned with learning definitions of a specific relation in terms of other relations provided as background knowledge. Although such systems have a history of more than 20 years and successful applications in various domains, they are still vulnerable to scalability and efficiency issues - mainly due to large search spaces they build. In this study we propose a heuristic to select a target instance that will lead to smaller search space without sacrificing the accuracy. The p...
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Citation Formats
N. C. Abay, A. MUTLU, and P. Karagöz, “A Graph-Based Concept Discovery Method for n-Ary Relations,” 2015, vol. 9263, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43712.