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Knowledge Discovery & Machine Learning Group

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

  • Data summarization techniques for learning data stored in relational databases
  • Data mining techniques for learning imbalance datasets, time series datasets and stream datasets
  • Information Retrieval techniques for structured and unstructured datasets
  • Text summarization techniques for Multi-Lingual Corpus.

 

RESEARCH PROJECTS

  • Feature Selection Methods for Relational Data Mining (2010 – Present)
  • Development of a variable-length feature construction method for summarising data stored in multiple tables using Genetic Algorithm (2010 – Present)
  • Development of Ensemble Data Mining Techniques for Imbalance Datasets (2010 – Present)
  • Development of a Genetic Based Hierarchical Agglomerative Clustering Techniques for Parallel Clustering of Bilingual Languages Based on Reduced Terms (2010 – Present)
  • Automatic Generation Of Mobile Content In Entertainment Applications Using Evolutionary Computing (2010 – Present)
  • Enhancing Document Clustering by Integrating Semantic Background Knowledge and Syntactic Features into the Bag of Words Representation (2012 – Present)
  • Enhancing Knowledge Management by Developing an Automated Document Labelling Based on Concepts Aggregation Using Hierarchical Agglomerative Clustering Technique (2012 – Present)
  • Development of a Text Analyzer for Automatic Categorization of Texts Documents Based on Interactive Visualization Approach (2012 – Present)
  • Semantic agent architecture: Embedding ontology into the agent's reasoning engine (2012 – Present)
  • Construction of an Intelligent Personalized Learning Tool (2012 – Present)
  • Development of an Intelligent Genetic-Based Data Summarisation Technique for Spatial Multi-Relational Databases (2008 – 2010)
  • Negotiating Agents for Online Auctions (2008 – 2010)
  • A Genetic Algorithm Based Term Weight Adjustment Approach for Document Clustering with Reduced Terms (2008 – 2009)
  • Hierarchical Agglomerative Clustering of Parallel Corpora of Bulgarian-English Documents (2006 – 2007)

 

RESEARCH STAFF

  • Assoc. Prof. Dr. Rayner Alfred
  • Dr. Mohd Hanafi Ahmad Hijazi
  • Mohd Norhisham Ghazali
  • Suraya Alias
  • Leau Yu Beng
  • Tan Soo Fun
  • Norhayati Daut
  • Nordaliela Mohd Rosli

 

POST GRADUATE RESEARCH STUDENTS
PhD

  • Hendra Yuni Irawan
  • Samry @ Mohd Shamrie Bin Sainin
  • Chung Seng Kheau
  • Haviluddin

MSc

  • Fourteen Masters PGR Students in total

 

Innovations (Software and Patents)

  • DARA (Dynamic Aggregation of Relational Attributes)
  • VISUALTEXT

COLLABORATION
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)

Awards

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