Knowledge Sharing Portal Evaluation: An Extended Analysis of Knowledge Seekers’ and Experts’ Feedback

Knowledge Sharing Portal Evaluation: An Extended Analysis of Knowledge Seekers’ and Experts’ Feedback

D. Venkata Subramanian (Department of Computer Science and Engineering, B.S. Abdur Rahman University, Chennai, India), Angelina Geetha (Department of Computer Science and Engineering, B.S. Abdur Rahman University, Chennai, India) and Senthil Raja (Virtusa (India) Private Limited, Chennai, India)
DOI: 10.4018/jwltt.2012040105
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Abstract

A knowledge management (KM) system plays a crucial role in every industry as well as in higher learning institutions. The purpose of this case study is to better understand the relationships between the knowledge seekers and expert’s feedback when evaluating, knowledge portals. One of the primary goals of this case study is to analyze the data collected from the database technology professionals (knowledge seekers), who access a series of database technology articles in the knowledge sharing portal to enhance their skills. This study also analyzes the data from the database technology experts, for validation, and performs the correlation between the evaluation results of knowledge providers and seekers. In addition, this paper tries to identify the correlation between the feedback data collected from knowledge seekers and providers. This study also describes an evaluation methodology involving both knowledge seekers and providers, with an emphasis on the key evaluation factors and supporting factors, as an effective approach to evaluate the knowledge sharing portal.
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Km System Technology Framework

Knowledge management (KM) system is a collective term that is used to describe the creation of knowledge repositories, respective interface components, improvement of knowledge access and sharing as well as communication through collaboration, enhancing the knowledge environment and managing knowledge as an asset for an organization. A KM system could be Document based, Ontology/Taxonomy based, AI technologies based or based on network maps or based on more organic approach using social computing tools. A KMS is an integrated multifunctional system that can support all major knowledge management and processing activities such as, Capturing, Organizing, Classifying, Understanding, Debugging, Editing, Finding, Retrieving, Disseminating, Transferring and Sharing knowledge. Considering the fundamental capabilities of KMS described by Jennex (2011) and typical KMS infrastructure topology, Subramanian and Geetha (2011) found a suitable KMS framework, which is mentioned in the Figure 1. This framework represents all the components which make up the KMS for industries as well as higher learning institutions and in particular focused on the needed quality factors to develop a measurement model based which are helpful for measuring the effectiveness of KMS. Some of the commonly used components which make up the KMS are described in the below sections.

Figure 1.

KMS technology framework

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