Towards Implementation of an Information Dissemination Tool for Health Publications: Case of a Developing Country

Health related publications have been growing at a considerable rate over the years. They are archived at public or private repositories for research or decisionmaking. In developing countries there is an increase in the need for technological infrastructure and funding towards research that enables the voluminous unstructured data to be effectively identified, stored, analysed and visualized to enable prompt decision making. Analysing data in real-time will assist knowledge seekers and researchers in timely access hence quick approach to solutions. We propose a web based, low-cost and user-friendly health information dissemination tool based on machine learning algorithms that analyses full-text publications sequentially and cluster related documents for ease of access. Information retrieval aspect of the model is enhanced through use of a semi-supervised approach that optimises topic selections during search operations. As future works, we propose to scale-up the prototype for bulky data processing and apply it to big data environments.