On-line consistent ranking on e-recruitment: seeking the truth behind a well-formed CV

被引:53
作者
Faliagka, Evanthia [1 ]
Iliadis, Lazaros [2 ]
Karydis, Ioannis [3 ]
Rigou, Maria [1 ]
Sioutas, Spyros [3 ]
Tsakalidis, Athanasios [1 ]
Tzimas, Giannis [4 ]
机构
[1] Univ Patras, Comp Engn & Informat Dept, Patras, Greece
[2] Democritus Univ Thrace, Forestry & Management Environm Dept, Komotini, Greece
[3] Ionian Univ, Dept Informat, Corfu, Greece
[4] Technol Educ Inst Messolonghi, Dept Appl Informat Management & Econ, Mesolongion, Greece
关键词
E-recruitment; Personality mining; Recommendation systems; Data mining; MANAGEMENT;
D O I
10.1007/s10462-013-9414-y
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this work we present a novel approach for evaluating job applicants in online recruitment systems, using machine learning algorithms to solve the candidate ranking problem and performing semantic matching techniques. An application of our approach is implemented in the form of a prototype system, whose functionality is showcased and evaluated in a real-world recruitment scenario. The proposed system extracts a set of objective criteria from the applicants' LinkedIn profile, and compares them semantically to the job's prerequisites. It also infers their personality characteristics using linguistic analysis on their blog posts. Our system was found to perform consistently compared to human recruiters, thus it can be trusted for the automation of applicant ranking and personality mining.
引用
收藏
页码:515 / 528
页数:14
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