SmartHR: a resume query and management system based on semantic web

Yeqing Ke, Zhirou Ma, Haijiang Wu, Jie Liu, Hua Zhong, Jun Wei
2014 Proceedings of the 1st International Workshop on Crowd-based Software Development Methods and Technologies - CrowdSoft 2014  
Organizations are always confronted with the challenge of efficiently finding out suitable candidates from massive resumes. Traditional human resource management based on the information management system usually adopts SQL queries or keywords search, which cannot capture the implicit information, while the manual work is always timeconsuming. To fill this gap, this paper presents SmartHR, a resume query and management system based on semantic web. Benefiting from knowledge base, it can
more » ... ase, it can understand users' intentions more intelligently and search for suitable candidates more accurately. In this paper, we propose two key technical difficulties which SmartHR meets, including the complexity of knowledge base construction and the timeconsuming semantic search, and then give appropriate solutions respectively. Four channels are adopted to construct knowledge base, which are well illustrated. Furthermore, a variety of performance optimizations are employed and the effectiveness is evaluated on real datasets of up to millions 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.
doi:10.1145/2666539.2666573 dblp:conf/sigsoft/KeMWLZW14 fatcat:p6cyp7lfr5b2fiswlohsf76hsm