Knowledge Extraction
Ali Zare Abarghouei; Mohammad Reza Dalvi; Zahra Dashtlaali
Abstract
The current research was conducted to apply knowledge extraction in the classification of jobs to identify the key role players using a mixed method (qualitative and sufficient data). The application of expert systems or decision support systems based on organizational data is increasing in the selection ...
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The current research was conducted to apply knowledge extraction in the classification of jobs to identify the key role players using a mixed method (qualitative and sufficient data). The application of expert systems or decision support systems based on organizational data is increasing in the selection and hiring of personnel. The data was derived from in-depth and semi-structured interviews with 17 subject experts in bank human resources, who were selected based on purposeful sampling.Data analysis was done based on the Strauss and Corbin model in the form of open, axial, and selective coding in the Atlas TI8 software. The results showed that the classification of jobs for the key role players in public and private banks includes causal conditions (requirement of talent substitution, human resource management developments, and organizational challenges), intervening conditions (organizational limitations and fear and resistance), and contextual conditions (strengthens and drivers) strategies (developmental, supportive and creating) and short-term and long-term consequences are among the components of the job classification model for the key role players in public and private banks. Next, based on the database with the CART method, the data mining of job classification was done. Regarding the performance of the model, it showed variance values of 311.92 and a risk value of 288.19. The predictions in the model explained 28.9% of the differences observed in the variable "employment status of A employees' category".
Data mining
Nasim Bakhshaei; Mohammad Reza Bagherzadeh; Yusuf Gholipourkanani; Mohammad Reza Dalvi
Abstract
This research aims to develop a data-based model for fifth-generation universities. Creating a data-driven model in a university environment is essential in education. The primary mission of higher education is to address the specific educational needs of individuals, as well as the needs of society ...
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This research aims to develop a data-based model for fifth-generation universities. Creating a data-driven model in a university environment is essential in education. The primary mission of higher education is to address the specific educational needs of individuals, as well as the needs of society and its economic development. The study was conducted in both qualitative and quantitative sections. The grounded theory is conducted based on the perspectives of the chancellors of Islamic Azad University. 21 people were selected using snowball sampling techniques. In the following, a six-category model is provided. Analysis was done using NVIVO software. The statistical population in the quantitative section consisted of all professors from Islamic Azad University nationwide. A sample size of 381 professors was selected using the Cochran sampling formula. The research tool was a questionnaire created by the researcher. Then, using the model presented and the suggested pattern fit, the performance of the model is predicted based on the K-Mean method in Weka and RapidMiner software. According to the results, the proposed model was approved by experts. The analysis of structural equations was also confirmed. According to the Waode algorithm model, the highest accuracy was 81%.
