Knowledge Extraction
Elham Samadi; Hasanali Bakhtiyar Nasrabadi; Zohreh Saadatmand
Abstract
The aim of this research is to employ neural networks in discovering functional knowledge based on the rational training of Avicenna and Kant. The methodology of this study is based on deep learning neural networks, making it an exploratory research. Given the practicality of functional knowledge, this ...
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The aim of this research is to employ neural networks in discovering functional knowledge based on the rational training of Avicenna and Kant. The methodology of this study is based on deep learning neural networks, making it an exploratory research. Given the practicality of functional knowledge, this research is applied in nature. To assess the significance of components and evaluation indicators of functional knowledge, text mining and the frequency of related symbols have been used. In order to utilize data mining techniques in this research, the WEKA software has been employed. The algorithms considered for implementation in this study are MLP, SVR, AdaBoost.R, Bagged Trees (BAGTREE), Linear Regression (LR), and Least Squares Support Vector Regression (LSSVR). According to the results obtained for functional knowledge, the LSSVR and SVR methods outperform the others, indicating their superiority. As the charts illustrate, there is significant volatility in this dataset, making prediction challenging. Furthermore, the R2 value is very close to one, indicating relatively accurate predictions by the methods. Neural networks can serve as powerful tools to aid in rational thinking, logical decision-making, and better understanding of the surrounding world, in line with the perspectives of Avicenna and Kant. These tools can assist in analyzing and interpreting complex data in these fields and strive for rationality and human excellence.
Knowledge Extraction
Elham Samadi; Hasanali Bakhtiyar Nasrabadi; Zohreh Saadatmand
Abstract
This research aims to analyze the intellectual education of Avicenna (Ibn Sina) and discover practical knowledge. The purpose of text mining in historical records is to identify relationships within existing data and extract knowledge from them. When the existing data are structured, it is easy to use ...
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This research aims to analyze the intellectual education of Avicenna (Ibn Sina) and discover practical knowledge. The purpose of text mining in historical records is to identify relationships within existing data and extract knowledge from them. When the existing data are structured, it is easy to use data mining methods to extract knowledge from them. In relation to the research topic, the method employed in this study is text mining analysis, making this research exploratory. The TF-IDF weighting method is used in this research. Considering the high dimensionality of the data, where the number of features is much greater than the number of vulnerable samples, linear Support Vector Machine (SVM) is a more suitable choice for these tests. Various implementations of this algorithm are available. In this research, LibLinear SVM, which is one of the most suitable implementations, has been used. First, the conceptual texts of Ibn Sina's thought were analyzed by understanding the contexts of existence, knowledge, man, and values. Subsequently, a list of educational requirements was deduced using concepts and categories. Finally, models for the construction of cognitive perception and an educational model were proposed. It can be said that the ideal human being, according to the teachings of Sinai, is someone who, through their scientific perspective related to their existence, knowledge, and values, can attain proper intellectual development and happiness derived from understanding the truths of the universe. This individual can acquire intellectual knowledge, enhance their power of critical thinking and reasoning, and ultimately achieve perfection.
