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CSTSDEXKK0S
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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This paper attempted to assess the attitudes of students in
Advances in technology have created the potential for a new
Inclusion has become a priority on the global educational agenda,
The proposed system comes to overcome the problem of writing a C.V. Cover letter which requires some linguistic skills and a lot of experience in this domain in addition to its cost in term of time and money. The ACLGS solved the problem by developing an auto generated cover letter based on the user C.V. regardless its format. The ACLGS takes the user C.V. and the carrier announcement that contains the job requirements and the skills needed as input. The system solved the problem by building a template as a frame of slots each slot contains a required skill for the job; the system extracted the required information from the user CV and fills the slots in an automatic fashion. The ACLGS applies the Information retrieval methodologies to extract information with intelligence trends to mine the user C.V. in terms of part of speech tags and some of indicator words that the system used to recognize the proper data and required information. In addition, the system specifies a set of features for each slot in the form. The user C.V. clustered into a number of categories (e.g. Personal information, Qualifications, Experience, Skill, Rewords, and Publications). These categories are used as additional features for the extracted information and data. The system took into account the problem of sentence coherence and improves the output document through using pre-specified sentences that inserted into the output document based on the extracted information discovered from the user C.V.
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