Conceptual Framework of Kxpert:Knowledge-Based Information Retrieval for Expert Profiling

Abstract

With the constant demand for expertise within organisation, especially in boosting the credibility of experts in the organisation, it is a need to bring forth a simple yet effective knowledge-based expert profiling based on information retrieved from credential publication sites. A number of frameworks from previous authors are analysed to propose one sound framework for a case university, to improve its existing research expert database, to make it more efficient in the information retrieval process and knowledge repository technique. Knowledge expertise mapping is proposed to be part of the whole mechanism for the conceptual framework called kXpert in this paper. The choice of credential knowledge sources is highlighted due to the updated information made available on the sites that are based on the published works of the internal experts. Very rare that this information is referred to on daily basis when there is a need to find expertise, thinking that the existing database has it all. The proposed conceptual framework presented in this paper is the work to be completed in the next phase, and can be customised for other organisations, industries and purposes.

Agent-mediated Knowledge Recovery: The Case of Turnover-induced Knowledge Loss in a Knowledge-intensive Institution

“…Turnover-induced knowledge loss has been reported in previous research, especially in organisations managing software development projects (Rigby et al, 2016;Nassif & Robillard, 2017) and in knowledge-intensive institutions (Ismail & Suhaimi, 2021;Ismail, 2016). Before one could understand the knowledge loss and knowledge recovery, it is important to realise that knowledge continuity is highly significant for an organisation.…”

“…Technically, it is found that intelligent software agents could be useful for knowledge recovery and mitigating knowledge loss (Ismail & Suhaimi, 2021;Ismail, 2016). This technical domain has expanded into the concept of Agent of Things (AoT), derived from the popular domain of Internet of Things (IoT), but focusing on the intelligent software developed within the environment where the software agent sits.…”

“…The agents, i.e., Connect, Identify, Decide, and Method, together orchestrate a workflow that ensures consistent and accurate knowledge recovery and preservation, thereby addressing the risks associated with knowledge loss during employee turnover. The developed CIDM model seeks to fill the gap recognized by Rigby et al (2016); Nassif and Robillard (2017); Ismail and Suhaimi (2021) concerning the lack of practical, technological applications of knowledge management theories. The model leverages NLP capabilities and rule-based process flow, offering a solution for structured retention and recovery of tacit and explicit knowledge in organizations.…”