M. Sulaiman Khan
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BackgroundMuhammad Sulaiman Khan is a member of the Intelligent and Distributed Systems (IDS) and a PhD research student specialising in Fuzzy Association Rule Mining with Weighted and Composite Items at Liverpool Hope University. He has a MSc in Computing (Lahore) and another MSc in Distributed Systems from Liverpool Hope University. He has several years of industrial experience as a programmer in Java and Visual basic, including internet and database applications. He has worked on HEIF-II (funded £9000) project in 2006 for over 1 year under the supervision of Dr. Maybin Muyeba as a research assistant at Liverpool Hope University. He has published in several international conferences and is currently authoring journal papers. |
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Research InterestsWorked on HEIF-II (funded £9000) project in 2006 with Dr. Maybin Muyeba at Liverpool Hope University: PROJECT: Health Association Rule Mining (HARM project 2006), £9,000 UK Sterling My main areas of research interest include, but not limited to the following: · Data Engineering · Performance of Data Mining Algorithms · Intelligent Information Retrieval · Fuzzy Logic (as applied to Data Mining) · Persvasive Computing (Peer to peer systems) |
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Publications· M. Sulaiman Khan, Muyeba, M and Coenen, F. 2008. "A Weighted utility Framework for Mining Association Rules", to appear in 2nd UKSim european Symposium on Computer Modelling and Simulation (EMS2008), Liverpool, UK.
· M. Sulaiman Khann, Muyeba, M and Coenen, F. 2008. "Weighted Association Rule Mining from Binary and Fuzzy Data", to appear in 8th Industrial Conference on Data Mining (ICDM08), LeipZig, Germany.
· M. Sulaiman Khan, Muyeba, M and Coenen, F. 2008. "Mining Fuzzy Association Rules from Composite Items", to appear in IFIP International Conference on Artificial Intelligence (IFIP-AI 2008), Milano, Italy.
· M. Sulaiman Khan, Muyeba, M and Coenen, F. 2008. "Fuzzy Weighted Association Rule Mining with Weighted Support and Confidence Framework", to appear in Algorithms for Large-Scale Information Processing in Knowledge Discovery (ALSIP 2008), Osaka, Japan.
· M. Sulaiman Khan, Muyeba, M and Coenen, F. 2008. A Framework for Mining Fuzzy Association Rules from Composite Items, to appear in Algorithms for Large-Scale Information Processing in Knowledge Discovery (ALSIP 2008), Osaka, Japan.
· Khan, M. S.; Muyeba, M and Coenen, F. 2007.On Extraction of Nutritional Patterns (NPS) Using Fuzzy Association Rule Mining, To appear in Proceedings of International Conference on Health Informatics (HEALTHINFO 2008),Madeira, Portugal, IEEE/EMB Sponsored,Indexed by DBLP, INSPEC, ISI
· Khan, M. S.; Muyeba, M and Tjortjis, C. and Coenen, F. 2007.An Effective Fuzzy Healthy Association Rule Mining Algorithm (FHARM), To appear in UKCI 2007, the 7th Annual Workshop on Computational Intelligence (FUZZ-IEEE co-located), London, UK · Muyeba, M; Khan, M. S.; Malik, Z. and Tjortjis, C. 2006.Towards Healthy Association Rule Mining (HARM): A Fuzzy Quantitative Approach, Lecture Notes in Computer Science (LNCS), Springer, IDEAL, Volume 4224, pp 1014-1022. · Khan, M. S.; Muyeba, M. 2006.Query Coordination for Distributed Data Sharing in P2P Networks, Lecture Notes in Computer Science(LNCS), Springer, VLDB 2006 (DBISP2P), Volume 4125, pp. 376-384. · Muyeba, M; Khan, M. S. and Gong, Z. 2006.On Clustering Attribute-Oriented Induction, Research and Development in Intelligent Systems XXIII 2006, Springer-Verlag, Bramer, M.; et al (Eds.), pp 403-407 |
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