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)