Integrating Knowledge Requirements into Topic Map for Online-Education

Abstract:

Topic Map, which described as The GPS of information universe, traditionally focused on building knowledge structure and associating them with information resources. In online-education environment, it has been used to address the issues about people disoriented in huge amounts of learning resources, to support learners browse the semantic relationship between knowledge topics and find the learning content effectively and instructors externalize their implicit knowledge both on conceptual and information level. However, as the explosion of knowledge information, people are suffering the disorientation of knowledge topics. Specially, learners are puzzled about what knowledge are valuable and need to learn, and knowledge providers dont know how to update outdated knowledge hierarchy or develop new knowledge product for changing requirements. To address this problem, we extend Topic map by adding a top level, named knowledge requirement level (KRL). This level KRL can be used to guide learners to concentrate on the required knowledge topics, and drive knowledge providers to redevelop or refactor outdated knowledge hierarchy. In order to obtaining social knowledge topic requirement for KRL, we have developed an information extraction tool, named WIE, to extract knowledge requirement information from job-list Webpages for supporting users extract data for different piece of a given structure-fixed Webpages.

• Periodical: Advanced Materials Research (Volumes 791-793)
• Pages: 1721-1725
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.791-793.1721
• Online since: September 2013
• Authors: An Qiong Tang, We Nan Tan, Tong Wang, Lin Shan Cui, Shan Tang
• Keywords: Information Extraction, Knowledge Integration, Topic Map

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