Quality Ranking Algorithms for Knowledge Objects in Knowledge Management Systems
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 1
Abstract
The emergence of web-based Knowledge Management Systems (KMS) has raised several concerns about the quality of Knowledge Objects (KO), which are the building blocks of knowledge expertise. Web-based KMSs offer large knowledge repositories with millions of resources added by experts or uploaded by users, and their content must be assessed for accuracy and relevance. To improve the efficiency of ranking KOs, two models are proposed for KO evaluation. Both models are based on user interactions and exploit user reputation as an important factor in quality estimation. For the purpose of evaluating the performance of the two proposed models, the algorithms were implemented and incorporated in a KMS. The results of the experiment indicate that the two models are comparable in accuracy, and that the algorithms can be integrated in the search engine of a KMS to estimate the quality of KOs and accordingly rank the results of user searches.
Authors and Affiliations
Amal Al-Rasheed, Jawad Berri
Keywords
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- EP ID EP261474
- DOI 10.14569/IJACSA.2018.090117
- Views 108
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