# (Ijcsis) International Journal Of Computer Science And Information Security, Vol. 6, No. 3, 2009 Web-Based Expert System For Civil Service Regulations:Rcses

Mofreh A. Hogo* Electrical engineering Technology Dept., 
Higher Institution of Technology Benha, Benha University, Egypt. 

Fouad Mousa Business management Dept, Faculty of commerce, Assuit university 
*the corresponding author, Khaled Fouad Central Lab. for Agricultural Expert Systems (CLAES) 
 
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.** 
Keywords- Knowledge base;Ontology; RCSES; and Civil regulation. 

I. INTRODUCTION 
An expert system is a computer program that simulate the problem-solving behavior of a human, it is composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes the knowledge base), and the end user interface (accepting inputs, generating outputs). The path that leads to the development of expert systems is different from that of conventional programming techniques. The concepts for expert system development come from the subject domain of artificial intelligence (AI), and require a departure from conventional computing practices and programming techniques. Expert systems (ES) emerged as a branch of artificial intelligence (AI), from the effort of researchers to develop computer programs that could reason as humans [1]. 

Many organizations have leveraged this technology to increase productivity and profits through better business decisions the work in [2-5] are one of most commercially successful branches of AI [6]. Although there have been reports of ES 
failures [7] and [8], surveys [9] and [10] show that many companies have remained enthusiastic proponents of the technology and continue to develop important and successful applications. Internet technology can change the way that an ES is developed and distributed. For the first time, knowledge on any subject can directly be delivered to users through a web based ES. Grove [11] provided some examples of web-based expert systems in industry, medicine, science and government and claimed that "there are now a large number of expert systems available on the Internet." He argued that there are several factors that make the Internet, by contrast to standalone platforms, an ideal base for KBS (knowledge based system) delivery. These factors include: The Internet is readily accessible, web-browsers provide a common multimedia interface, several Internet-compatible tools for KBS 
development are available, Internet-based applications are inherently portable, and emerging protocols support cooperation among KBS. He also identified several problems in the development of web-based KBS: Keeping up with rapid technological change to servers, interface components, inference engines, and various protocols; and reducing the potential delivery bottleneck caused by communication loads and a limited infrastructure Adams [12] pointed out that "there are numerous examples of expert systems on the web, but many of these systems are small, non-critical systems." The most successful example is probably the web-based legal expert system reported by Bodine [13], who remarked that "Law firms are collecting hundreds of thousands of dollars in subscription fees from clients who use their question-andanswer advisory services based on the web.". Contrary to Grove and Adams, Huntington [14] stated that "there are not many ES on the web" due to the fact that the Internet was not created with applications such as expert systems in mind. As a result, the manner in which the web and web browsers interface made it difficult to perform the actions required by ES. Athappilly [15] reported a "dynamic web-based knowledge system for prototype development for extended enterprise." He suggested that the use of emerging Internet 