Information Retrieval Framework for Digital Resource Objects
Universiti Sains Malaysia, Malaysia, Wafa’ Za’al Alma’aitah · International Journal of Advanced Trends in Computer Science and Engineering · 2019
Basically, digital resource objects (DRO) suffer from two fundamental issues, namely lack of quality of metadata content and difficulty in accessing metadata content.These lead to decrease in the performance of the DRO retrieval.With a view to increase the performance of the DRO retrieval, many components of information retrieval have been enhanced such as document expansion (DE), retrieval model such as Dirichlet smoothing (DS) model, and query expansion (QE).Most of these studies have shown that employing IR components (DE, QE or DS) independently to enhance the DROs retrieval has helped to increase the performance of the retrieval.It is assumed that IR components can enhance the performance of the DRO retrieval.Based on this assumption, an information retrieval framework (IRF) for DROs is presented in this paper.The proposed IRF is to address the retrieval problems in DROs and provide an environment for retrieving information from DROs with the highest possible performance.The principle task of IRF is to make all components of IR (DE, DS, and QE) work together to achieve the greatest benefit in improving the retrieval performance.Several experiments were conducted on CHiC2013 which is a collection on cultural heritage.The results show a considerable enhancement over other IR approaches that use the DE method, DS model and QE method independently.