Data Mining
With the proliferation of data, the field of Data Mining has gained rapid popularity. Data Mining focuses on the discovery of patterns in large datasets by making use of statistical and machine learning techniques.
Our current focus involves leveraging machine learning techniques to facilitate efficient and effective delivery of services in the health and educational domains---two areas that are of significance in the so-called developing world.
Project Members
Data Mining Publications
Kambunji, Martin, Emmanuel Phiri, Castridah Nachibinga, and Ernest Sinyangwe. 2023. “Automatic Summarisation Of Zambian Legislative Documents”. Lusaka, Zambia: University of Zambia. |
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Chanda, Chilufya, Chileshe Kamfwa, and Chuulu Mainda. 2023. “The Zambia National Electronic Theses And Dissertations Pre-Processing Pipeline Portal”. Lusaka, Zambia: University of Zambia. |
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Chipangila, Bertha, Eric Liswaniso, Andrew Mawila, Philomena Mwanza, Daisy Nawila, Robert M'sendo, Mayumbo Nyirenda, and Lighton Phiri. 2023. “Controlled Vocabularies In Digital Libraries: Challenges And Solutions For Increased Discoverability Of Digital Objects”. International Journal On Digital Libraries, 17. doi:10.1007/s00799-023-00374-1. |
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Chalwe, Christabel, Chisanga Chanda, Lweendo Muzyamba, and Joe Mwape. 2023. “Wikimotivate: A Facebook Plugin For Motivating Content Creation And Contribution On Wikipedia”. Lusaka: University of Zambia. |
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Chisale, Adrian, and Lighton Phiri. 2023. “Towards Metadata Completeness In National Etd Portals For Improved Discoverability”. In 26Th International Symposium On Electronic Theses And Dissertations. Gujarat, Indian: INFLIBNET Centre. http://ir.inflibnet.ac.in/handle/1944/2446. |
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