Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management System
This study proposes a system for analyzing non-face-to-face counseling data using text-mining techniques to assess psychological states and automatically classify them into predefined categories. The system addresses the challenge of understanding internal issues that may be difficult to express in...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-11-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/22/10747 |
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| author | Woncheol Park Seungmin Oh Seonghyun Park |
| author_facet | Woncheol Park Seungmin Oh Seonghyun Park |
| author_sort | Woncheol Park |
| collection | DOAJ |
| description | This study proposes a system for analyzing non-face-to-face counseling data using text-mining techniques to assess psychological states and automatically classify them into predefined categories. The system addresses the challenge of understanding internal issues that may be difficult to express in traditional face-to-face counseling. To solve this problem, a counseling management system based on text mining was developed. In the experiment, we combined TF-IDF and Word Embedding techniques to process and classify client counseling data into five major categories: school, friends, personality, appearance, and family. The classification performance achieved high accuracy and F1-Score, demonstrating the system’s effectiveness in understanding and categorizing clients’ emotions and psychological states. This system offers a structured approach to analyzing counseling data, providing counselors with a foundation for recommending personalized counseling treatments. The findings of this study suggest that in-depth analysis and classification of counseling data can enhance the quality of counseling, even in non-face-to-face environments, offering more efficient and tailored solutions. |
| format | Article |
| id | doaj-art-a9db3238eecb44a3818708c40e784ca0 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-a9db3238eecb44a3818708c40e784ca02025-08-20T02:26:59ZengMDPI AGApplied Sciences2076-34172024-11-0114221074710.3390/app142210747Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management SystemWoncheol Park0Seungmin Oh1Seonghyun Park2Department of Computer Engineering, Kongju National University, Cheonan 31080, Republic of KoreaDepartment of Computer Engineering, Kongju National University, Cheonan 31080, Republic of KoreaDepartment of Computer Engineering, Kongju National University, Cheonan 31080, Republic of KoreaThis study proposes a system for analyzing non-face-to-face counseling data using text-mining techniques to assess psychological states and automatically classify them into predefined categories. The system addresses the challenge of understanding internal issues that may be difficult to express in traditional face-to-face counseling. To solve this problem, a counseling management system based on text mining was developed. In the experiment, we combined TF-IDF and Word Embedding techniques to process and classify client counseling data into five major categories: school, friends, personality, appearance, and family. The classification performance achieved high accuracy and F1-Score, demonstrating the system’s effectiveness in understanding and categorizing clients’ emotions and psychological states. This system offers a structured approach to analyzing counseling data, providing counselors with a foundation for recommending personalized counseling treatments. The findings of this study suggest that in-depth analysis and classification of counseling data can enhance the quality of counseling, even in non-face-to-face environments, offering more efficient and tailored solutions.https://www.mdpi.com/2076-3417/14/22/10747non-face-to-face counselingcounseling datatext miningTF-IDF (Term Frequency–Inverse Document Frequency)Word Embedding |
| spellingShingle | Woncheol Park Seungmin Oh Seonghyun Park Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management System Applied Sciences non-face-to-face counseling counseling data text mining TF-IDF (Term Frequency–Inverse Document Frequency) Word Embedding |
| title | Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management System |
| title_full | Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management System |
| title_fullStr | Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management System |
| title_full_unstemmed | Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management System |
| title_short | Text-Mining-Based Non-Face-to-Face Counseling Data Classification and Management System |
| title_sort | text mining based non face to face counseling data classification and management system |
| topic | non-face-to-face counseling counseling data text mining TF-IDF (Term Frequency–Inverse Document Frequency) Word Embedding |
| url | https://www.mdpi.com/2076-3417/14/22/10747 |
| work_keys_str_mv | AT woncheolpark textminingbasednonfacetofacecounselingdataclassificationandmanagementsystem AT seungminoh textminingbasednonfacetofacecounselingdataclassificationandmanagementsystem AT seonghyunpark textminingbasednonfacetofacecounselingdataclassificationandmanagementsystem |