Profile Identification Study: Automatic Authentication, Optimization and Real-time Processing

被引:0
|
作者
Djoudi, Lamia Atma [1 ]
Rome, Miguel [1 ]
机构
[1] Synchrone Technol, Technol Competitiveness, F-75009 Paris, France
来源
2014 INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND COMPUTATIONAL INTELLIGENCE (CSCI), VOL 2 | 2014年
关键词
Analysis; optimization; Student recruitment; curriculum; performance;
D O I
10.1109/CSCI.2014.136
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Whatever our field (research, education, industry, etc), generally we follow the same process recruitment: launch calls for tender to find candidates: PHD students, PostDoc, engineers, etc Usually, human resources service which is in charge of the first selection: application corresponds to the tender. Generally, for a large number of CVs, we must find the best candidate. Everyone wants the best candidate! Even if the service has good computer facilities, the selection process is done by a quick reading of CV by staff. This may have several disadvantages: - Have just an overview of CVs; - select the CVs based on titles, education, etc; - and we can overlook some CVs due to bad presentation of significant information. The question that arises is: Is there any software, automatic methods to find automatically the best CV that corresponds to a specific tender? Few works to date. Mainly, they concern the CVs and research methods of finer profiles and in restricted areas. During the last two years, we are working on a project where one of the main goals is to optimize and simplify the identification of the best profiles corresponding to a specific tender. We need to provide an automatic and intelligent platform. To achieve our goal, our project is brought into two parts: The first part will be presented in this paper: automatic connection and data acquisition. The second part will be presented in another paper (once we have the final results). It concerns the processing algorithm.
引用
收藏
页码:271 / 276
页数:6
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