Abstract
Nowadays the number of people searching work is increasing and the number of university graduates is also getting larger. Companies searching for a perfect job candidate for a person working in the informatics domain may be lost between different resumes with different formats and big quantity. Selecting the best curriculum vitae (CV) is a considered a big step to help any company decide whether a job seeker is suitable or not. The criteria that should be taken into consideration is divided between a block of private information and another block of professional data. The blocks are based on age, education, participating in real projects, availability of published papers or research activities, possessing modern programming languages and technologies and so on. Selecting the perfect candidate needs an estimation based on a choice function similar to the utility function which weighs the different criteria and helps in evaluating them numerically. But since we may be dealing with some fuzzy or uncertain information we proposed the use of modified Boyer Moore algorithm and RELIEF method to reach the target.
Highlights
When searching for some information in a text, the goal is to reach some specific business resolution
The curriculum vitae (CV) is read by the application; it is divided into semantic blocks
A utility function will be used as a future step to complete the whole system's implementation
Summary
When searching for some information in a text, the goal is to reach some specific business resolution. Searching CV’s for a particular data is one of the problems that online recruiters and many big companies are facing It is not an easy job for such companies to mine through data of different types and. Previous studies had suggested a system to search for specific information even if it is not precisely stated in the resume. The suggestion is based on the existence of some mistakes in the resume when writing incorrect words without noticing the errors. Another reason for this suggestion is to combine different variations of the same word since they have the same meaning and explaining the same idea
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