Improving Hash Table Hit Ratio of an ILP-Based Concept Discovery System with Memoization Capabilities

Conference paper


Although ILP-based concept discovery systems have applications in a wide range of domains, they still suffer from scalability and efficiency issues. One of the reasons for the efficiency problem is high number of query executions necessary in the concept discovery process. Due to refinement operator of ILP-based systems, these queries repeat frequently. In this work we propose a method to improve hash table hit ratio for repeating queries of ILP-based concept discovery systems with memoization capabilities. The proposed method introduces modifications on search space evaluation and covering steps of such systems. Experimental results show that the proposed method improves the hash table hit count of ILP-based concept discovery systems with an affordable cost of extra memory consumption.


Concept discovery ILP Memiozation Hash table hit. 


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Copyright information

© Springer-Verlag London 2013

Authors and Affiliations

  1. 1.Department of Computer EngineeringMiddle East Technical UniversityAnkaraTurkey

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