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

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Computer and Information Sciences III

Abstract

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.

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Authors and Affiliations

  1. Department of Computer Engineering, Middle East Technical University, Ankara, Turkey

    Alev Mutlu & Pinar Senkul

Authors
  1. Alev Mutlu
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  2. Pinar Senkul
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Corresponding author

Correspondence to Alev Mutlu .

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Editors and Affiliations

  1. , Dept of Electrical and Electronics Eng'g, Imperial College, London, SW7 2BT, United Kingdom

    Erol Gelenbe

  2. , EEE Dept., Imperial College, Exhibition Rd., London, SW72AZ, United Kingdom

    Ricardo Lent

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Mutlu, A., Senkul, P. (2013). Improving Hash Table Hit Ratio of an ILP-Based Concept Discovery System with Memoization Capabilities. In: Gelenbe, E., Lent, R. (eds) Computer and Information Sciences III. Springer, London. https://doi.org/10.1007/978-1-4471-4594-3_27

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  • DOI: https://doi.org/10.1007/978-1-4471-4594-3_27

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  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-4593-6

  • Online ISBN: 978-1-4471-4594-3

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