Phân tích bài toán truy xuất tài liệu thủ tục hành chính công cho dịch vụ công trực tuyến

  • Dinh-Dien La Department of Information and Communications, Ha Giang Province, Viet Nam
  • Van-Hieu Nguyen Institute of Applied Science and Technology - IAST, University of Information and Communication Technology, Thai Nguyen University, Vietnam
  • Trung-Nghia Phung Institute of Applied Science and Technology - IAST, University of Information and Communication Technology, Thai Nguyen University, Vietnam
  • Khanh-Van Tran Institute of Applied Science and Technology - IAST, University of Information and Communication Technology, Thai Nguyen University, Vietnam
##plugins.pubIds.doi.readerDisplayName##: https://doi.org/10.32913/mic-ict-research-vn.v2024.n2.1297
Keywords: Truy xuất tài liệu, mô hình kết hợp, thủ tục hành chính công

Abstract

Thủ tục hành chính công là các quy trình, phương pháp thực hiện, tài liệu và yêu cầu hoặc điều kiện do các cơ quan nhà nước hoặc cá nhân có thẩm quyền quy định để giải quyết các nhiệm vụ cụ thể liên quan đến cá nhân hoặc tổ chức. Tuy nhiên, các tổ chức và công dân vẫn gặp khó khăn trong việc tiếp cận thông tin và dịch vụ hành chính công một cách dễ dàng và thuận tiện. Bài viết này nghiên cứu các kỹ thuật tiên tiến để giải quyết thách thức trong việc truy xuất tài liệu cho các dịch vụ hành chính công. Chúng tôi triển khai một quy trình truy xuất kết hợp các mô hình truy xuất truyền thống như TF-IDF và BM25 với các mô hình hiện đại như SBERT và các mô hình tinh chỉnh. Kết quả cho thấy rằng việc kết hợp các mô hình này cải thiện đáng kể hiệu suất truy xuất. Mô hình kết hợp giữa BM25 và SBERT tinh chỉnh đạt điểm F2 cao nhất, cho thấy hiệu quả vượt trội trong việc truy xuất thông tin.

Author Biographies

Dinh-Dien La, Department of Information and Communications, Ha Giang Province, Viet Nam

Dinh-Dien La is a PhD student majoring in computer science, University of Information and Communications Technology, Thai Nguyen University. He is currently Deputy Director of the Department of Information
and Communications of Ha Giang province, in charge of digital transformation. His research interests are data
science, machine learning, and deep learning in the domain of law and public administration.

Van-Hieu Nguyen, Institute of Applied Science and Technology - IAST, University of Information and Communication Technology, Thai Nguyen University, Vietnam

Van-Hieu Nguyen is pursuing an Engineering degree in Information Technology at the University of Information and Communication Technology in Thai Nguyen, Vietnam. He is involved with the Institute of Applied Science and Technology in Thai Nguyen. His research interests include machine learning, deep learning, and natural
language processing.

Trung-Nghia Phung, Institute of Applied Science and Technology - IAST, University of Information and Communication Technology, Thai Nguyen University, Vietnam

Assoc. Prof. Trung-Nghia Phung received his Engineering degree in Electronics and Telecommunications from Hanoi University of Science and Technology (HUST) in 2002. He completed his Master of Science degree in Telecommunications from Vietnam National University –Hanoi (VNUH) in 2007 and his PhD degree in Information Science from Japan Advanced Institute of Science and Technology (JAIST) in 2013. He was Dean of Faculty of Electronics and Telecommunications, Head of Academic Affairs, and he has been Rector of Thai Nguyen University of Information and Communication Technology (ICTU). He has been a Vice President of
Vietnam Club of Faculties-Institutes-Schools-Universities of ICT (FISU) and President of FISU Branch in the Northern Midlands, Mountains and Coastal Region of Vietnam. His research interests include machine learning and deep learning.

Khanh-Van Tran, Institute of Applied Science and Technology - IAST, University of Information and Communication Technology, Thai Nguyen University, Vietnam

Van-Khanh Tran received Ph.D. in Natural Language Processing from the Japan Advanced Institute of Science and Technology (JAIST). He is currently an AI Research Scientist on the NLP team at FPT Smart Cloud’s Generative AI (GenAI) Center, where he focuses on developing large language models and AI assistant ecosystems tailored for Vietnamese users. He also serves as the Deputy Head of the Institute of Applied Science and Technology. His research interests include natural language processing, large language models, and AI applications in the legal, healthcare, and finance domains.

References

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M. Ogbi and M. Aminilari, “Bm25 ranking algorithm development using matching concepts in unstructured text,” 2015. [Online]. Available: https://api.semanticscholar.org/CorpusID:9098595

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Published
2024-11-25
Issue
Tập 2024 Số 2: Các công trình nghiên cứu, phát triển và ứng dụng Công nghệ Thông tin và Truyền thông
Section
Bài viết (tiếng Việt)

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