Text Data Mining for Uncovering the Influence of Religion on Ancient Greek Philosophical Thought with Optimization

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Published: Jul 30, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i6.7724
Keywords:
Text Mining, Data Mining, Feature Extraction, Gaussian Optimization, Ancient Greek

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Bian Jiang
College of State Governance, Southwest University, Chongqing, 400715, China
Shuai Kong
College of Digital Media, Sichuan University of Culture and Arts, Sichuan, China

Abstract

Text data mining can provide valuable insights into the influence of religion on the development of ancient Greek philosophical thought. This paper presented text data mining techniques to perform feature extraction and classification with Gaussian Optimization (FeCGO), to analyze the influence of religion on the development of ancient Greek philosophical thought. This paper explores the application of text data mining techniques, specifically feature extraction and classification with Gaussian Optimization (FeCGO), to analyze the influence of religion on the development of ancient Greek philosophical thought. The FeCGO examined the relevant texts, including works by ancient Greek philosophers, religious texts, myths, and historical accounts. These texts are subjected to preprocessing steps, such as tokenization, stop word removal, stemming, and normalization, to ensure the data is prepared for analysis. The proposed FeCGO method combines the Gaussian Optimization algorithm with a classification model to optimize the classification accuracy and performance. Labeled data is used to train the FeCGO model, with texts categorized based on their religious or philosophical themes. The findings contribute to a deeper understanding of the interplay between religion and philosophy in ancient Greek society. The application of text data mining techniques, specifically FeCGO, demonstrates the potential of computational methods to extract valuable insights from large-scale textual datasets.

Article Details

How to Cite
Jiang, B. ., & Kong, S. . (2023). Text Data Mining for Uncovering the Influence of Religion on Ancient Greek Philosophical Thought with Optimization. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6), 351–360. https://doi.org/10.17762/ijritcc.v11i6.7724
Issue
Vol. 11 No. 6 (2023): June (2023) Issue
Section
Articles

References

Zhang, H., & Luo, J. (2022). Interpretive Trends and the Conceptual Construction of the Daodejing’s Dao in Russian Sinology: A Historical Overview. Religions, 13(9), 825.

Robinson, J. M. (2021, March). An introduction to early Greek philosophy: The chief fragments and ancient testimony, with connecting commentary. Advanced Reasoning Forum.

Citlak, A. (2021). Psychology of religion in the theories and research of the Lvov-Warsaw School (basic achievements and developments). Archive for the Psychology of Religion, 43(1), 95-116.

Škof, L. (2021). The Food, Water, Air and Fire Doctrines in Ancient Indian and Greek Philosophies from a Comparative Perspective. Asian Studies, 9(3), 303-320.

Horujy, S. S. (2021). Russian religious philosophy: the nature of the phenomenon, its path, and its afterlife. In The Palgrave Handbook of Russian Thought (pp. 51-72). Cham: Springer International Publishing.

Sahu, S., Sarangi, H., & Mallik, P. S. (2021). A Deconstructive Analysis of Derrida’s Philosophy. Shanlax International Journal of Arts, Science and Humanities, 9, 98-107.

Shivadekar, S. ., Kataria, B. ., Hundekari, S. ., Kirti Wanjale, Balpande, V. P., & Suryawanshi, R. . (2023). Deep Learning Based Image Classification of Lungs Radiography for Detecting COVID-19 using a Deep CNN and ResNet 50. International Journal of Intelligent Systems and Applications in Engineering, 11(1s), 241–250. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/2499

Mikki, S. (2021). Homo philosophicus: Reflections on the nature and function of philosophical thought. Philosophies, 6(3), 77.

Tantlevskij, I. R., Gromova, E. V., & Gromov, D. (2021). Network Analysis of the Interaction between Different Religious and Philosophical Movements in Early Judaism. Philosophies, 6(01), 2.

Moore, B., Clark, R., Muñoz, S., Rodríguez, D., & López, L. Automated Grading Systems in Engineering Education: A Machine Learning Approach. Kuwait Journal of Machine Learning, 1(2). Retrieved from http://kuwaitjournals.com/index.php/kjml/article/view/125

De Sousa, R. (2022). What Philosophy Contributes to Emotion Science. Philosophies, 7(4), 87.

Bahodirovna, A. M. (2022). Semantic Field of ‘Spirituality’: Lexical Analysis and Psychological, Philosophical Features. European Journal of Life Safety and Stability (2660-9630), 14, 124-31.

Jackson, J. C., Watts, J., List, J. M., Puryear, C., Drabble, R., & Lindquist, K. A. (2022). From text to thought: How analyzing language can advance psychological science. Perspectives on Psychological Science, 17(3), 805-826.

Shanthi, D. N. ., & J, S. . (2021). Machine Learning Architecture in Soft Sensor for Manufacturing Control and Monitoring System Based on Data Classification. Research Journal of Computer Systems and Engineering, 2(2), 01:05. Retrieved from https://technicaljournals.org/RJCSE/index.php/journal/article/view/24

Muratovna, Y. U., & Kazakbaevich, S. N. (2021). HERMENEUTICS AS A SCIENCE OF CORRECT UNDERSTANDING AND INTERPRETATION OF THE MEANING OF PHILOSOPHICAL TEXTS. Emergent: Journal of Educational Discoveries and Lifelong Learning (EJEDL), 2(04), 70-73.

Prof. Nikhil Surkar. (2015). Design and Analysis of Optimized Fin-FETs. International Journal of New Practices in Management and Engineering, 4(04), 01 - 06. Retrieved from http://ijnpme.org/index.php/IJNPME/article/view/39

Mitcham, C. (2022). Thinking through technology: The path between engineering and philosophy. University of Chicago Press.

Samadov, A. R. (2021). Philosophical Analysis of the synthesis of Morality and Aesthetics in Spiritual Life. CENTRAL ASIAN JOURNAL OF SOCIAL SCIENCES AND HISTORY, 2(3), 1-7.

Mickiewicz, F. (2021). Theologization of Greek Terms and Concepts in the Septuagint and New Testament. Verbum Vitae, 39(3), 751-769.

Romero-Silva, R., & De Leeuw, S. (2021). Learning from the past to shape the future: a comprehensive text mining analysis of OR/MS reviews. Omega, 100, 102388.

Jadhav, A., Kaur, M., & Akter, F. (2022). Evolution of software development effort and cost estimation techniques: five decades study using automated text mining approach. Mathematical Problems in Engineering, 2022, 1-17.

Hassani, A., Iranmanesh, A., & Mansouri, N. (2021). Text mining using nonnegative matrix factorization and latent semantic analysis. Neural Computing and Applications, 33, 13745-13766.

Li, Y., Jiang, D., Lian, R., Wu, X., Tan, C., Xu, Y., & Su, Z. (2021). Heterogeneous latent topic discovery for semantic text mining. IEEE Transactions on Knowledge and Data Engineering, 35(1), 533-544.

Bezdan, T., Stoean, C., Naamany, A. A., Bacanin, N., Rashid, T. A., Zivkovic, M., & Venkatachalam, K. (2021). Hybrid fruit-fly optimization algorithm with k-means for text document clustering. Mathematics, 9(16), 1929.

Gharehchopogh, F. S., & Khalifelu, Z. A. (2011, October). Analysis and evaluation of unstructured data: text mining versus natural language processing. In 2011 5th International Conference on Application of Information and Communication Technologies (AICT) (pp. 1-4). IEEE.

Widiastuti, N. I. (2019, November). Convolution neural network for text mining and natural language processing. In IOP Conference Series: Materials Science and Engineering (Vol. 662, No. 5, p. 052010). IOP Publishing.

Dreisbach, C., Koleck, T. A., Bourne, P. E., & Bakken, S. (2019). A systematic review of natural language processing and text mining of symptoms from electronic patient-authored text data. International journal of medical informatics, 125, 37-46.

Wu, C., Li, X., Guo, Y., Wang, J., Ren, Z., Wang, M., & Yang, Z. (2022). Natural language processing for smart construction: Current status and future directions. Automation in Construction, 134, 104059.