Quality Ranking Algorithms for Knowledge Objects in Knowledge Management Systems

Abstract

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.

Enhancing information security best practices sharing in virtual knowledge communities

“…It is concerned with identifying and learning from existing best practices to apply them in a new configuration. With the use of technology, professionals with shared interests can meet, interact and contribute virtually in an online community without geographical restrictions (Al-Rasheed and Berri, 2018; Hislop et al , 2018).…”

“…Therefore, developers should apply one of the different algorithms that are available (Al-Rasheed and Berri, 2018). Second, the portal owner needs to verify the identity of the participants who will share the best practices.…”

“…To enrich the information security best practice knowledge base, information security practitioners and experts are invited to exchange knowledge and experience. Knowledge value is increased if it is been reused and applied (Al-Rasheed and Berri, 2018).…”