[Paper Review] Web-Based Expert System for Civil Service Regulations: RCSES

Mofreh A. Hogo, Khaled M. Fouad+1 more|arXiv (Cornell University)|Jan 12, 2010

Business Process Modeling and Analysis17 references3 citations

TL;DR

This paper presents RCSES, a novel web-based expert system for civil service regulations in Saudi Arabia, leveraging XML-based rule representation and ontology modeling to encode 17 key regulations. The system enables dynamic knowledge management, inference, and validation through an interactive interface, demonstrating high usability, performance, and accuracy in real-world testing with domain experts and technical users.

ABSTRACT

Internet and expert systems have offered new ways of sharing and distributing knowledge, but there is a lack of researches in the area of web based expert systems. This paper introduces a development of a web-based expert system for the regulations of civil service in the Kingdom of Saudi Arabia named as RCSES. It is the first time to develop such system (application of civil service regulations) as well the development of it using web based approach. The proposed system considers 17 regulations of the civil service system. The different phases of developing the RCSES system are presented, as knowledge acquiring and selection, ontology and knowledge representations using XML format. XML Rule-based knowledge sources and the inference mechanisms were implemented using ASP.net technique. An interactive tool for entering the ontology and knowledge base, and the inferencing was built. It gives the ability to use, modify, update, and extend the existing knowledge base in an easy way. The knowledge was validated by experts in the domain of civil service regulations, and the proposed RCSES was tested, verified, and validated by different technical users and the developers staff. The RCSES system is compared with other related web based expert systems, that comparison proved the goodness, usability, and high performance of RCSES.

Motivation & Objective

• To develop a centralized, accessible, and maintainable system for civil service regulations in Saudi Arabia.
• To bridge the gap in research on web-based expert systems for public sector regulations.
• To enable non-technical users to query, update, and extend knowledge about civil service rules through an intuitive interface.
• To validate the system’s accuracy and usability with domain experts and technical users.
• To demonstrate the system’s performance and scalability compared to existing web-based expert systems.

Proposed method

• Knowledge acquisition and selection were conducted through collaboration with civil service domain experts.
• An ontology was developed to model regulatory concepts and relationships using XML-based representation.
• Rule-based knowledge sources were encoded in XML format to support structured inference.
• An inference engine was implemented using HTTP-based web services to process user queries.
• An interactive web interface was built to allow users to input data, view results, and modify the knowledge base dynamically.
• The system was tested and validated through iterative feedback from developers and domain experts.

Experimental results

Research questions

• RQ1 How can a web-based expert system effectively model and deliver civil service regulations in a scalable and maintainable way?
• RQ2 To what extent can XML-based rule representation and ontology modeling improve the accuracy and usability of regulatory knowledge systems?
• RQ3 Can a web-based interface enable non-technical users to effectively query and update complex regulatory knowledge?
• RQ4 How does the performance and usability of RCSES compare to other existing web-based expert systems?
• RQ5 What is the impact of expert validation on the reliability and correctness of the system’s outputs?

Key findings

• RCSES successfully encoded 17 civil service regulations using a structured XML-based ontology and rule system.
• The system demonstrated high usability and performance in testing with technical users and developers.
• Domain experts confirmed the accuracy and completeness of the knowledge base after validation.
• The interactive interface enabled easy modification, extension, and querying of the knowledge base without requiring technical expertise.
• Comparative analysis confirmed RCSES outperformed other similar systems in usability and response efficiency.
• The system proved scalable and maintainable, supporting dynamic updates and long-term knowledge evolution.