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Penemuan Pengetahuan dan Pembelajaran Mesin

BIDANG PENYELIDIKAN

1. Perlombongan data Relational

2. Melombong set data tidak seimbang, time series dan stream

3. Dapatan semula maklumat bersilang bahasa (CLIR)

4. Dapatan semula maklumat untuk set data berstruktur dan tidak berstruktur

KECEMERLANGAN

1. KDML adalah sebuah kumpulan penyelidikan menggunakan teknik machine learning untuk penemuan pengetahuan di Malaysia.

2. KDML cemerlang di dalam bidang peringkasan data relational untuk data yang disimpan di dalam pangakaln data (contohnya data perubatan, bioinformatik, kewangan dan saintifik).

MISI

Misi utama adalah untuk menjalankan penyelidikan dalam bidang:

1. Teknik peringkasan data untuk pembelajaran data yang disimpan di dalam pangkalan data relational.

2. Teknik perlombongan data untuk pembelajaran set data tidak seimbang, time series dan stream.

3. Dapatan semula maklumat untuk data berstruktur dan tidak berstruktur.

4. Teknik peringkasan teks untuk Multi-Lingual Corpus.

 

PROJEK PENYELIDIKAN TERKINI

  1.  
  2. Enhancing Document Clustering by Integrating Semantic Background Knowledge and Syntactic Features into the Bag of Words Representation (2012 – Present)
  3. Enhancing Knowledge Management by Developing an Automated Document Labelling Based on Concepts Aggregation Using Hierarchical Agglomerative Clustering Technique (2012 – Present)
  4. Development of a Text Analyzer for Automatic Categorization of Texts Documents Based on Interactive Visualization Approach (2012 – Present)
  5. Semantic agent architecture: Embedding ontology into the agent's reasoning engine (2012 – Present)
  6. Construction of an Intelligent Personalized Learning Tool (2012 – Present)

PAST RESEARCH PROJECTS

  1. Feature Selection Methods for Relational Data Mining (Tamat)
  2. Development of a variable-length feature construction method for summarising data stored in multiple tables using Genetic Algorithm (Tamat)
  3. Development of Ensemble Data Mining Techniques for Imbalance Datasets (Tamat)
  4. Development of a Genetic Based Hierarchical Agglomerative Clustering Techniques for Parallel Clustering of Bilingual Languages Based on Reduced Terms (Tamat)
  5. Automatic Generation Of Mobile Content In Entertainment Applications Using Evolutionary Computing (Tamat)
  6. Development of an Intelligent Genetic-Based Data Summarisation Technique for Spatial Multi-Relational Databases (2008 – 2010)
  7. Negotiating Agents for Online Auctions (2008 – 2010)
  8. A Genetic Algorithm Based Term Weight Adjustment Approach for Document Clustering with Reduced Terms (2008 – 2009)
  9. Hierarchical Agglomerative Clustering of Parallel Corpora of Bulgarian-English Documents (2006 – 2007)

STAF PENYELIDIK

PENYELIDIK KANAN

  1. Prof. Madya 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

 

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

PENCAPAIAN

PENERBITAN

Senarai penerbitan KDML.

INOVASI

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

ANUGERAH

  1. GOLD AWARD in SIIF 2010, Seoul, Korea (BioDARA: Toolkit to Extract Bio-Medical Information and Structuring Based on Data Summarization)
  2. GOLD AWARD in ITEX 2010, KLCC, Kuala Lumpur, Malaysia (BioDARA: 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)

 

KOLABORASI

Rakan Akademik

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

Rakan Industri

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

 

HUBUNGI

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
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http://ums.academia.edu/RaynerAlfred