SmartHR: a resume query and management system based on semantic web
Yeqing Ke, Zhirou Ma, Haijiang Wu, Jie Liu, Hua Zhong, Jun Fang Wei · 2014
Organizations are always confronted with the challenge of eciently nding out suitable candidates from massive re- sumes. Traditional human resource management based on the information management system usually adopts SQL queries or keywords search, which cannot capture the im- plicit information, while the manual work is always time- consuming. To ll this gap, this paper presents SmartHR, a resume query and management system based on seman- tic web. Beneting from knowledge base, it can understand users' intentions more intelligently and search for suitable candidates more accurately. In this paper, we propose two key technical diculties which SmartHR meets, including the complexity of knowledge base construction and the time- consuming semantic search, and then give appropriate solu- tions respectively. Four channels are adopted to construct knowledge base, which are well illustrated. Furthermore, a variety of performance optimizations are employed and the eectiveness is evaluated on real datasets of up to million- s of triples and the results show a great improvement. As a representative application in semantic web, our practice in SmartHR provides useful experience and conclusions for developers.