Data Mining Group

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http://data-mining.ceng.metu.edu.tr/

Data mining can be defined as extraction of interesting knowledge hidden in the data. There are different types of interesting patterns and several different approaches are used for extraction of these patterns, such as classification, clustering and association rule mining. In our department research on data mining is basically focused on multi-relational data mining and web mining. Recent research efforts concentrate on exploitation of semantic information for web mining and multi-relational data mining in order to generate more refined and semantic patterns. These efforts are currently pursued under the TUBITAK-funded project “METU-ISTEC: Work Package on Generation of New Techniques for Semantic Web and Web Mining”. In November 2006, a networking session on “Semantic Web and Web Mining” has been organized by some of members of the group at the IST-EVENT Conferenc

Members

  • Prof. Dr. İsmail Hakkı Toroslu
  • Assoc. Prof. Dr. Ahmet Coşar
  • Asst. Prof. Dr. Pınar Şenkul
  • Dr. Yusuf Kavurucu
  • Dr. Murat Ali Bayır
  • Öznur Kırmemiş Alkan (PhD. Student)
  • Arif Tümer (PhD. Student)
  • Serkan Toprak (PhD Student)
  • Eren Esgin (PhD Student)
  • Banu Deniz Yanık (MS Student)
  • Sefa Kılıç (MS Student)
  • Sinem Demirci (MS Student)
  • Şükrü Bezen (MS Student)
  • Burak Tıknaz (MS Student)

Selected Publications

  • Y. Kavurucu, P. Senkul , I.H. Toroslu, “Concept Discovery on Relational Databases: New Techniques for Search Space Pruning and Rule Quality Improvement”, Knowledge-Based Systems, vol:23, issue:8, 743-756pp, December 2010.(doi:10.1016/j.knosys.2010.04.011.)
  • L. A. Guner, N. I. Karabacak, O. U. Akdemir, P. Senkul Karagoz, S. A. Kocaman, A. Cengel, M. Unlu, “An open-source framework of neural networks for diagnosis of coronary artery disease from myocardial perfusion SPECT”, Journal of Nuclear Cardiology, vol: 17, issue: 3, 405-413pp, June 2010, doi:10.1007/s12350-010-9207-5.
  • A. Mutlu, M. A. Berk, P. Senkul , Improving the Time Efficiency of ILP-based Multi-Relational Concept Discovery with Dynamic Programming Approach, ISCIS 2010, London, UK, Sept 22-24, 2010.
  • E. Esgin, P. Senkul , C. Cimenbicer, A Hybrid Approach for Process Mining: Using From-to Chart Arranged by Genetic Algorithms, HAIS 2010 (LNCS), San Sebastian, Spain, June 2010.
  • Y. Kavurucu, P. Senkul , I. H. Toroslu, ILP-based Concept Discovery in Multi-Relational Data Mining, Expert Systems With Applications, vol: 36, issue: 9, Pages 11418-11428, November 2009, doi: 10.1016/j.eswa.2009.02.100
  • S. D. Toprak, P. Senkul, Y. Kavurucu, I. H. Toroslu, A New ILP-based Concept Discovery Method for Business Intelligence, ICDE Workshop on Data Mining and Business Intelligence, April, 2007.
  • M. A. Bayir, I. H. Toroslu, A. Cosar, “A New Approach for Reactive Web Usage Data Processing”, ICDE-WIRI, April, 2006.
  • M. A. Bayir, I. H. Toroslu, A. Cosar, A Performance Comparison of Pattern Discovery Methods on Web Log Data, AICCSA-06, The 4th ACS/IEEE International Conference on Computer Systems and Applications, September 2005.

research/mining/index.txt · Last modified: 2011/02/17 11:26 by Ali Anil SINACI