Liu Qingxiang1,Zhang Pengzhu1,Zhang Xiaoyan2(),Liu Jingfang3
1Antai College of Economics and Management, Shanghai Jiaotong University, Shanghai 200030, China 2School of Management, Shanghai University of Engineering Science, Shanghai 201620, China 3School of Management, Shanghai University, Shanghai 200444, China
[Objective] To extract talents’ knowledge structure automatically. [Methods] We built an online knowledge structure extraction system based on Web information retrieval, webpage analysis, word segmentation and semantic Web technologies. [Results] We examined the usability of the new system. For course recognition, the overall precision rate was more than 95%. For semi-structured files, the recall rate was above 95%. For some non-structured files, the reacall rate was below 90%. [Limitations] The recall rate of course recognition was restricted by the content of the dictionary. [Conclusions] The proposed method meets the requirements of constructing talents’ knowledge structure and is a useful tool for related research.
(Hong Na, Zhang Zhixiong.Practice of Creating and Reasoning Science Ontology by Protégé[J]. New Technology of Library and Information Service, 2009(7-8): 1-5.)
