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Knowledge Discovery and Machine Learning (KDML)

RESEARCH AREAS

1. Relational Data Mining

2. Mining imbalance datasets, time series datasets and stream datasets

3. Cross Language Information Retrieval (CLIR)

4. Information Retrieval for structured and unstructured datasets

 

EXCELLENCE

1. KDML is one of the research groups dealing with machine learning techniques for knowledge discovery purposes in Malaysia.

2. KDML excels in the field of relational data summarization for datasets stored in relational databases (e.g., medical, bioinformatics, finance and scientific datasets)

 

MISSION

The main mission of KDML, as a research group, is conducting research in the area of:

1. Data summarization techniques for learning data stored in relational databases

2. Data mining techniques for learning imbalance datasets, time series datasets and stream datasets

3. Information Retrieval techniques for structured and unstructured datasets

4. Text summarization techniques for Multi-Lingual Corpus

 

CURRENT RESEARCH PROJECTS

  1. Feature Selection Methods for Relational Data Mining (2010 – Present)
  2. Development of a variable-length feature construction method for summarising data stored in multiple tables using Genetic Algorithm (2010 – Present)
  3. Development of Ensemble Data Mining Techniques for Imbalance Datasets (2010 – Present)
  4. Development of a Genetic Based Hierarchical Agglomerative Clustering Techniques for Parallel Clustering of Bilingual Languages Based on Reduced Terms (2010 – Present)
  5. Automatic Generation Of Mobile Content In Entertainment Applications Using Evolutionary Computing (2010 – Present)
  6. Enhancing Document Clustering by Integrating Semantic Background Knowledge and Syntactic Features into the Bag of Words Representation (2012 – Present)
  7. Enhancing Knowledge Management by Developing an Automated Document Labelling Based on Concepts Aggregation Using Hierarchical Agglomerative Clustering Technique (2012 – Present)
  8. Development of a Text Analyzer for Automatic Categorization of Texts Documents Based on Interactive Visualization Approach (2012 – Present)
  9. Semantic agent architecture: Embedding ontology into the agent's reasoning engine (2012 – Present)
  10. Construction of an Intelligent Personalized Learning Tool (2012 – Present)

 

PAST RESEARCH PROJECTS

  1. Development of an Intelligent Genetic-Based Data Summarisation Technique for Spatial Multi-Relational Databases (2008 – 2010)
  2. Negotiating Agents for Online Auctions (2008 – 2010)
  3. A Genetic Algorithm Based Term Weight Adjustment Approach for Document Clustering with Reduced Terms (2008 – 2009)
  4. Hierarchical Agglomerative Clustering of Parallel Corpora of Bulgarian-English Documents (2006 – 2007)

 

RESEARCH STAFF

SENIOR RESEARCHERS

  1. Assoc. Prof. Dr. Rayner Alfred
  2. Dr. Mohd Hanafi Ahmad Hijazi
  3. Mohd Norhisham Ghazali
  4. Suraya Alias
  5. Leau Yu Beng
  6. Tan Soo Fun
  7. Norhayati Daut
  8. Nordaliela Mohd Rosli

 

RESEARCHERS

PHD

  1. Hendra Yuni Irawan
  2. Chung Seng Kheau
  3. Haviluddin

MSc

  1. Marwan Abdul Jabbar Ali Al-Selwi
  2. Leow Ching Leong
  3. Surayaini Basri
  4. Florence Sia
  5. Afriza Sara Linimin
  6. Helena Binti Appolonius
  7. Natasha Joseph
  8. Kow Weng Onn
  9. Lan Jun Keong
  10. Ann Benjamin
  11. Syra Mokunjil
  12. Santana Rajan A/L Perumale
  13. Irwansah Bin Amran
  14. Nurulalam Yaakub

 

ACHIEVEMENTS

PUBLICATIONS

For KDML publications go here.

INNOVATIONS

  1. DARA (Dynamic Aggregation of Relational Attributes)
  2. VISUALTEXT

AWARDS

  1. GOLD AWARD in SIIF 2010, Seoul, Korea (BioDARA: A Toolkit to Extract Bio-Medical Information and Structuring Based on Data Summarization)
  2. GOLD AWARD in ITEX 2010, KLCC, Kuala Lumpur, Malaysia (BioDARA: A Toolkit to Extract Bio-Medical Information and Structuring Based on Data Summarization)
  3. BRONSE AWARD in SIIF 2010, Seoul, Korea (DARA: A Data Summarization Approach to Mining Patterns in a Biodiversity Database)
  4. BRONSE AWARD in PECIPTA 2011, KLCC, Kuala Lumpur, Malaysia (BioDARA: A  Toolkit to Extract Bio-Medical Information and Structuring Based on Data Summarization)
  5. BRONSE AWARD in PECIPTA 2009, KLCC, Kuala Lumpur, Malaysia (DARA: A Data Summarization Approach to Mining Patterns in a Biodiversity Database)

 

COLLABORATIONS

Academic Partners

  • Artificial Intelligence Research Group, University of York, United Kingdom.
  • Academy of Science, Sofia, Bulgaria.

Industry Partners

  • WWF (Malaysia)
  • Borneo Conservation Trust (BCT), Sabah, Malaysia
  • IBM (Malaysia)

 

CONTACT

Rayner Alfred (PhD)
School of Engineering and Information Technology
Universiti Malaysia Sabah,
Jalan UMS,
88400, Kota Kinabalu, Sabah, Malaysia

Tel: +6088-320000 ext:3040
Fax: +6088320348
Email:This email address is being protected from spambots. You need JavaScript enabled to view it.,This email address is being protected from spambots. You need JavaScript enabled to view it.

http://ums.academia.edu/RaynerAlfred