Path: Top -> Journal -> Jurnal Internasional -> King Saud University -> 2020 -> Volume 32, Issue 5, June
Automatic CV processing for scientific research using data mining algorithm
Oleh : Mohamed El Mohadab, Belaid Bouikhalene, Said Safi, King Saud University
Dibuat : 2021-08-04, dengan 0 file
Keyword : Scientific research, Natural language processing, Data mining, Decision aid, CV processing
Url : http://www.sciencedirect.com/science/article/pii/S1319157818302921
Sumber pengambilan dokumen : Web
To manage and measure the performance of scientific research at the university, managers or policymakers need synthetic indicators that are cleverly grouped in several indicators which aim to offer to the leaders the necessary tools, so as to improve scientific research. The governance of information system has posed a serious challenge for the leadership of universities especially through the use of decision aid. In order to improve the information system, especially scientific research, a study of automatizing curriculum vitae for researchers of different disciplines belonging to various research laboratories is discussed in this paper. The use of natural language processing with data mining classifier Decision Tree is presented in order to predict the field of work of each researcher. The choice of Decision Tree classifier among One Rule classifier and Naive Bayes classifier is not arbitrary; it is chosen by comparing performance metrics- such as Precision, Recall, F-measure, Correctly Classify Instance, Incorrectly Classify Instance, Kappa Statistic, Root Mean Squad Error, Relative Absolute Error, and Root Relative Squad Error.
Deskripsi Alternatif :To manage and measure the performance of scientific research at the university, managers or policymakers need synthetic indicators that are cleverly grouped in several indicators which aim to offer to the leaders the necessary tools, so as to improve scientific research. The governance of information system has posed a serious challenge for the leadership of universities especially through the use of decision aid. In order to improve the information system, especially scientific research, a study of automatizing curriculum vitae for researchers of different disciplines belonging to various research laboratories is discussed in this paper. The use of natural language processing with data mining classifier Decision Tree is presented in order to predict the field of work of each researcher. The choice of Decision Tree classifier among One Rule classifier and Naive Bayes classifier is not arbitrary; it is chosen by comparing performance metrics- such as Precision, Recall, F-measure, Correctly Classify Instance, Incorrectly Classify Instance, Kappa Statistic, Root Mean Squad Error, Relative Absolute Error, and Root Relative Squad Error.
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