Integration of data quality component in an ontology based knowledge management approach for e-learning system

• Main Authors: Sangodiah, A., Lim Ean Heng
• Format: Conference Proceeding
• Language: English
• Subjects: artificial intelligence; data mining; Data quality; e- learning; Electronic learning; knowledge management; text mining
• DOI: 10.1109/ICCISci.2012.6297221

At present, with the growing demand of knowledge economy, fast popularization and development of the World Wide Web, a lot of people are turning to e-learning via web. There are plenty e-learning systems nowadays and these systems provide some simple tools to manage and search a lot of teaching materials. Contrary to traditional teaching materials base which neglects to integrate semantic and concept teaching knowledge, the integration of ontology technology and knowledge management into e-learning has enabled the capturing of information and reusing it in an effective manner. Users now can easily and conveniently organize, share and reuse knowledge during e-learning. Despite a lot of research work has been revolved around ontology and knowledge management based technology in e-learning, contextual data quality issues inherent in online e-learning forums have yet to be fully explored and addressing the issues is important as to ensure only quality data is stored consistently in knowledge base in e-learning environment. This paper will highlight contextual data quality issues particularly in online e-learning forums and will propose a data quality component in e-learning environment in the context of knowledge base to address the issues. Also will be discussed are the technologies such as text mining, data mining and AI that are to incorporated into the component to accomplish its tasks. With the component in place, the contextual data quality issues can be resolved to a certain extent.