Development of an Internet-Based Information/Data Resource Platform during the COVID-19 Pandemic Using Hierarchical Clustering

Abstract

There is a heavy usage of Internet-based information resource platform due to COVID-19 pandemic. If it can present the search results as a list of group of related terms and context, that would be ideal. An additional enhancement would be to display information in the search results in a classified manner. Therefore, the research is proposing an effective and efficient information retrieval system. The methodology adopted follows conventional Information Retrieval (IR) system design except that Cosine similarity and hierarchical clustering were introduced for search result ranking. The Average Precision of the proposed system was compared with that of flat clustering such as K-means. The result of the evaluation shows that hierarchical clustering improved in precision, being10% better than flat clustering result retrieval result. This led to greater usability, user experience, and efficiency of the system.