Skip to main content
SpringerLink
Log in
Book cover

Computer and Information Sciences pp 373–376Cite as

Improving the Time Efficiency of ILP-based Multi-Relational Concept Discovery with Dynamic Programming Approach

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 62))

Abstract

Large amount of relational data is stored in databases. There- fore, working directly on the data stored in database is an important feature for multi-relational concept discovery systems. In addition to concept rule quality, time efficiency is an important performance dimension for concept discovery since dealing with large amount of data is a must. In this work, we present a dynamic programming based approach for improving the time efficiency on an ILP-based concept discovery system, namely CRIS (Concept Rule Induction System), which combines ILP and Apriori and directly works on databases.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Dfizeroski, S.: Multi-relational data mining: an introduction. SIGKDD Explorations 5(1) (2003) 1–16

    Article  Google Scholar 

  2. Muggleton, S.: Inductive Logic Programming. In: The MIT Encyclopedia of the Cognitive Sciences (MITECS). MIT Press (1999)

    Google Scholar 

  3. Goutte, C., Gaussier, E.: newblock A probabilistic interpretation of precision, re-call and f-score, with implication for evaluation. In: European Colloquium on IR Research (ECIR’05), Xerox Research Centre Europe 6, chemin de Maupertuis F-38240 Meylan, France, Springer (2005) 345–359

    Google Scholar 

  4. Agrawal, R., Mannila, H., Srikant, R., Toivonen, H., Verkamo, A.I.: Fast discov- ery of association rules. In: Advances in Knowledge Discovery and Data Mining. AAAI/MIT Press (1996) 307–328

    Google Scholar 

  5. Sedgewich R.: Algorithms, Second Edition Addison-Wesley Publishing Company (1988) 232–245

    Google Scholar 

  6. Kavurucu Y., Senkul P., Toroslu I.H.: ILP-based Concept Discovery in Multi-Relational Data Mining. Expert System with Applications, 36(9) (2009) 11418–11428

    Article  Google Scholar 

  7. Kavurucu Y., Senkul P., Toroslu I.H.: Concept Discovery on Relational Databases: New Techniques for Search Space Pruning and Rule Quality Improvement. In Press, Accepted Manuscript, Knowledge-Based Systems, doi:10.1016/j.knosys.2010.04.011

    Google Scholar 

Download references

Author information

Authors and Affiliations

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

    Alev Mutlu & Pinar Senkul

  2. Aselsan Inc., Ankara, Turkey

    Mehmet Ali Berk

Authors
  1. Alev Mutlu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mehmet Ali Berk
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Pinar Senkul
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Alev Mutlu .

Editor information

Editors and Affiliations

  1. , EEE Dept., Imperial College, Exhibition Road, London, SW72BT, United Kingdom

    Erol Gelenbe

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

    Ricardo Lent

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

    Georgia Sakellari

  4. , School of Biomedical Eng., Sci. and Heal, Drexel University, Bossone 702, 3120 Market Street, Philadelphia, 19104, Pennsylvania, USA

    Ahmet Sacan

  5. , Dept. of Computer Engineering, Middle East Technical University, Ankara, 06531, Turkey

    Hakki Toroslu

  6. Fac. Engineering, Dept. Computer Engineering, Middle East Technical University - METU, Ankara, 06531, Turkey

    Adnan Yazici

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer Science+Business Media B.V.

About this paper

Cite this paper

Mutlu, A., Berk, M.A., Senkul, P. (2011). Improving the Time Efficiency of ILP-based Multi-Relational Concept Discovery with Dynamic Programming Approach. In: Gelenbe, E., Lent, R., Sakellari, G., Sacan, A., Toroslu, H., Yazici, A. (eds) Computer and Information Sciences. Lecture Notes in Electrical Engineering, vol 62. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-9794-1_69

Download citation

  • DOI: https://doi.org/10.1007/978-90-481-9794-1_69

  • Published:

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-90-481-9793-4

  • Online ISBN: 978-90-481-9794-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation