Smart service

The fourth industrial revolution fundamentally changes the way businesses do business. They need to innovate to create a unique and specialized competitive advantage. Intelligent services are capable of self-discovery and self-adaptation to user needs without knowing the requirements explicitly. The adoption of intelligent services in today's businesses enables them to accelerate their digital transformation. This allows creating a huge array of user information as well as deepening the competition between organizations. Many businesses have opted for a user-driven strategy by building relationships with users to support them personally. A lot of user data is collected and stored for this purpose. Artificial Intelligence and data analytics have become mainstream in helping businesses understand users, capture and manage information about users better. This data is then used to enable systems to deliver smarter, adaptive, and personalized services based on the knowledge and context of user information.

Study topic

Intelligent services is a multidisciplinary field of study that may include some of the following topics:

  • Smart services for Business (business analytics, business intelligent, marketing intelligence, market intelligence, customer intelligence, content intelligence)
  • Smart services for Education
  • Context-aware system, personalization
  • Adaptive information system
  • Sematic web, knowledge management, user context in knowledge-intensive smart services.
  • Enabling smart services with knowledge management.
  • Internet of things, Mobile Database, Location based Services, Artificial Intelligent based on Modern Information Systems.


  • Dr. Pham Nguyen Cuong
  • Dr. Nguyen Tran Minh Thu
  • Assoc.Prof.Dr. Le Nguyen Hoai Nam
  • Dr. Vu Thi My Hang
  • Dr. Ho Le Kim Nhung
  • MSc. Tiet Gia Hong
  • MSc. Pham Minh Tu
  • MSc. Ho Thi Hoang Vy

Possible collaborative activities

  • Prof.Dr. Le Dinh Thang, Université du Québec à Trois-Rivières Québec, Canada.
  • Dr. Pham Thi Thanh Thoa, Dublin Institute of Technology-DIT, Ireland.

Links of demo, website, video

Consulting on career paths and MOOC courses

Some scientific publications

  • Thi My Hang Vu, Thanh Thoa Pham Thi, Thang Le Dinh (2023). Towards a Rule Modeling Framework for Context-aware Smart Service Systems. ITM Web of Conferences , 04005.
  • Thi My Hang Vu, Thang Le Dinh, Nguyen Anh Khoa Dam, Cuong Pham-Nguyen (2023). Context-aware Knowledge-based Systems: A Literature Review. Proceedings of the 56th Hawaii International Conference on System Sciences HICSS 2023.
  • Nguyen Duy Cuong, Dinh Nguyen Hanh Dung, Pham-Nguyen Cuong, Le Dinh Thang, Le Nguyen Hoai Nam (2022). ITCareerBot: A Personalized Career Counselling Chatbot. Recent Challenges in Intelligent Information and Database Systems. ACIIDS 2022. Communications in Computer and Information Science, vol 1716.
  • Thang Le Dinh, Nguyen Anh Khoa Dam, Chan Nam Nguyen, Thi My Hang Vu, and Pham-Nguyen Cuong (2022). From Customer Data to Smart Customer Data: The Smart Data Transformation Process. International Conference on Exploring Service Science (IMT Web conference 2022- IESS 2.2)
  • Nam Nguyen Chan, Duc Loc Nguyen Vo, Cuong Pham-Nguyen, Thang Le Dinh, Nguyen Anh Khoa Dam, Thanh Thoa Pham Thi, My Hang Vu Thi. Design and deployment of a customer journey management system: the CJMA approach. MaDaIN 2021: The 2nd International Conference on Recent Advances in Machine Learning, Data Science, Intelligent Systems & Networking. December 15-15, 2021. Da Nang, Vietnam.
  • Thang Le Dinh, Thoa Pham Thi, Cuong Pham-Nguyen, Nam Le Nguyen Hoai. A Knowledge-based Model for Context-Aware Smart Service Systems. Journal of Information and Telecommunication (JIT) (2021). Taylor & Francis.
  • Pham Quynh Thi, Ho Thi Diep, Nguyen Dinh Thao, Cuong Pham-Nguyen, Thang Le Dinh, Le Nguyen Hoai Nam. Towards An Ontology-Based Knowledge Base for Job Postings. 2020 7th NAFOSTED Conference on Information and Computer Science (NICS). VNUHCM-University of Science, Vietnam. November 26-27. 2020.
  • Thang Le Dinh, Thanh Thoa Pham Thi, Cuong Pham-Nguyen, Nguyen Hoai Nam Le. Towards A Context-Aware Knowledge Model for Smart Service Systems. 2020 12th International Conference on Computational Collective Intelligence (ICCCI). 30 November - 3 December 2020. Da Nang, Vietnam. Lecture Notes in Computer Science, vol 12496. Springer, Cham.
  • Tran Hien Luong, Tran Thi Ly Ly, Pham-Nguyen Cuong, Le Dinh Thang, Tiet Gia Hong and Le Nguyen Hoai Nam (2020), Towards Chatbot-based Interactive What- and How-Question Answering Systems: the Adobot Approach. 2020 RIVF International Conference on Computing and Communication Technologies (RIVF), 2020, pp. 1-3, doi: 10.1109/RIVF48685.2020.9140742.
  • Ho Thao Hien, Pham-Nguyen Cuong, Le Nguyen Hoai Nam, Ho Le Thi Kim Nhung and Le Dinh Thang, (2018). Intelligent Assistants in Higher-Education Environments: The FIT-EBot, a Chatbot for Administrative and Learning Support. In SoICT’ 18: Ninth International Symposium on Information and Communication Technology, December 6–7, 2018, Da Nang City, Viet Nam.
  • Thu Tran Minh Nguyen, Ngoc Vu, and Binh Ly (2022), An approach to constructing a graph data repository for course recommendation based on IT career goals in the context of big data, 2022 IEEE International Conference on Big Data (IEEE BigData 2022), December 17-20, 2022 Osaka, Japan. IEEE Catalog Number: CFP22BGD-ART, ISBN: 978-1-6654-8045-1, pp. 301-308. DOI: 10.1109/BigData55660.2022.10020436
  • Thu Tran Minh Nguyen, Thinh Pham Quoc Tran (2021), A knowledge graph embedding based approach for learning path recommendation for career goals. The 13th International Conference on Computational Collective Intelligence (ICCCI 2021), 29 September – 1 October 2021, Rhodes, Greece. Lecture Notes in Computer Science, vol 12876. Springer, Cham. Print ISBN: 978-3-030-88080-4, Online ISBN: 978-3-030-88081-1, DOI:
  • Le Nguyen Hoai Nam (2021). Latent factor recommendation models for integrating explicit and implicit preferences in a multi-step decision-making process. Expert Systems with Applications, 174.
  • Le Nguyen Hoai Nam (2021). Towards comprehensive profile aggregation methods for group recommendation based on the latent factor model. Expert Systems with Applications, 185.
  • Le Nguyen Hoai Nam (2022). Profile aggregation-based group recommender systems: Moving from item preference profiles to deep profiles. IEEE Access. 10.
  • Le Nguyen Hoai Nam (2022). Incorporating textual reviews in the learning of latent factors for recommender systems. Electronic Commerce Research and Applications, 52.
  • Le Nguyen Hoai Nam (2022). Towards comprehensive approaches for the rating prediction phase in memory-based collaborative filtering recommender systems. Information Sciences, 589.
  • Le Nguyen Hoai Nam, Ho Bao Quoc (2017). The hybrid filter feature selection methods for improving high-dimensional text categorization. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 25(02), 235-265.
  • Ho Le Thi Kim Nhung, Vo Van Hai, and Roman Jasek, “Towards a Correction Factors-based Software Productivity using Ensemble approach for Early Software Development Effort Estimation”, Computer Science Online Conference, Advances in Intelligent Systems and Computing, 2022.
  • Ho Le Thi Kim Nhung, Vo Van Hai, Radek Silhavy, and Zdenka Prokopova, Petr Silhavy, "Parametric Software Effort Estimation Based On Optimizing Correction Factors and Multiple Linear Regression", IEEE Access, vol. 10, 2021.