Knowledge Based Systems and Their Relevance

Cite this


Knowledge base system refers to the computer technology-based productive tools of artificial intelligence that are used to impart quality, effectiveness, and knowledge-oriented approach to decision-making process (Matayong & Mahmood, 2013). In the today’s world of technology and high levels of competition in the business world, timely decision-making is a vital process in ensuring that organisations remain competitive and up to date in their activities.

Further, because of globalisation and technological advancements, competition does not just come from within, but from the international front, where technology has also facilitated the generation and sharing of an enormous amount of information, which must be relied on to inform decisions that are vital in an organisation’s competitiveness (Dimitrios, 2012). Failure of an organisation to act fast, rely on accurate information, or fail to recognise the need to react to a given market dynamics can easily drive it towards its closure (Matayong & Mahmood, 2013).

Consequently, it is very important for organisations to closely monitor changes in their areas of operations and rely on the accurate information in a timely manner to ensure that they remain competitive. Because of this unpredictable nature of the current world due to technology and globalisation, knowledge-based systems have become very important tools that allow organisations to obtain and process information in a timely and accurate manner to inform decision-making (Rah, Gul, & Wani, 2010).

Despite being a recent development in the computer age where it is deeply enshrined in the modern technology, the concept of knowledge-based systems is widely used in many organisations. Knowledge-based systems have found their application in varied areas of the modern world business and organisational management. This paper will discuss knowledge-based systems, their evolution, and relevance in the modern world. It will also highlight the current and future trends in the development and usage of the systems.


The development of knowledge-based systems can be traced to NASA and its dedication to artificial intelligence starting from the 1960s. However, the widespread use of these systems in the business environment can be traced to the recent developments have relate to the fifth-generation computer technology that is still greatly enshrined into the notion of Artificial Intelligence (AI) (Bechina & Ndlela, 2007). The emergence of computer technology, and most importantly, the internet has allowed the generation of an enormous amount of data or information that is relevant for organisations’ decision-making.

However, determining the best information out of the available information and data to inform decision-making has become even more difficult. In other words, finding information and data for an organisation that is in the process of decision-making is not the main challenge, but rather choosing the most relevant information and data out of the available facts (Kiessling, Richey, Meng, & Dabic, 2009). In the light of these new challenges, knowledge-based systems were developed by artificial intelligence researchers to aid organisations to adapt and/or use large amounts of the available information to assist in the decision-making process (Rah et al., 2010). In the period that preceded the use of knowledge-based systems, human thinking majorly guided and determined the decision-making process where processes such as data analysis and decision-making were done manually.

However, as the paper reveals, with the growing amount of the available information and data, as well as globalisation, organisations have had to collaborate with others to ensure safe and proper delivery of their products. The available data and amount of information had proved too much for the organisation to handle and process based on the numerous decisions that were made on a daily basis (Chen & Xu, 2010). The paper confirms that knowledge-based systems are very crucial in any organisation and that they have become more complex following the establishment of superior capabilities of acquiring and processing data and information to inform knowledge generation, which is vital for organisational decision-making processes.

Literature Review

This section provides important information relating to what other authors and studies have highlighted to the growing field of knowledge-based systems. Indeed, as it will be highlighted, organisational management is a highly researched area where investigators and experts try to map the best way through which an organisation can have a competitive advantage in its area. The literature review will discuss how the knowledge-based system has evolved to feature prominently as one of the key areas of competitive advantage in modern organisations.

Construction of Knowledge-based System

The knowledge-based system is an artificial intelligence structure that allows the capturing, storage, synthesis/processing, and presentation of knowledge to inform decision-making. As such, coming up with a knowledge-based system must incorporate the above capabilities and roles, without which the system cannot function. A good knowledge system has the capacity to acquire, create, package, and/or the reuse such knowledge in an organisational setting (Matayong & Mahmood, 2013). Knowledge-based systems are becoming important tools for organisational competitiveness since they provide a competitive advantage where organisations can make complex decisions within a very short time (Dimitrios, 2012).

On its own, “knowledge” is a more complex term that many organisations deploy when referring to their day-to-day achievements. Knowledge is more complex than information or data (Lau, Ning, Pun, Chin, & Ip, 2005). Indeed, the systems that support knowledge management are broader and complex when compared to those that contain data or information. As the data pyramid below shows, in the process of generating intelligence, knowledge ranks highly than data and information. It presents what an organisation wishes to know and/or do (act) in a given situation where such knowledge is needed, unlike information, which represents actionable and processed data (Matayong & Mahmood, 2013).

Data Pyramid.
Figure 1: Data Pyramid Source: Dimitrios (2012)

Constructing a successful and an effective knowledge based system requires the availability of what is referred to as a knowledge base. A knowledge base refers to a database or a collection of information and data that the system can use to infer knowledge as guided by rules and facts that programmers or knowledge-based system engineers have input or coded into the system by (Kiessling et al., 2009). The concept behind knowledge-based systems is therefore based on the notion that the more the knowledge inputted into knowledge based systems, the more it will be able to infer such knowledge for decision-making for the organisation’s decision-making needs. This can be summarised as follows in the diagram below:

A Knowledge Based System Interface.
Figure 2: A Knowledge Based System Interface (Lau et al., 2005).

From the above figure, a knowledge base system consists of three key components that include knowledge base, inference engine, and a user interface. The knowledge base consists of commands, rules, and facts from, which all scenarios and problems that an organisation faces in relation to what the system was made to address can be found (Lau et al., 2005). The knowledge system has access to experts, as well as databases, where the necessary information and data can be obtained to add or remove the existing knowledge from the knowledge base to reflect dynamics in the field of the organisation’s operations (Dimitrios, 2012).

The inference engine refers to the component of the knowledge base system, which receives queries from the user. It uses facts and artificial reasoning to decide, which of the knowledge it receives from the knowledge base will be passed to the user depending on the situation (query) at hand (Lau et al., 2005). On the other hand, the user interface presents user-readable and understandable outputs that the operators can comprehend and use for responding to the problems they have at hand (Lau et al., 2005). The user interface also presents the platform where queries can be input into the system for problem-solving purposes.

Delving further on the knowledge base system reveals components that are important for the successful operation of the whole system. The system is the main tool that allows organisations to implement knowledge management. The components include the expert system, knowledge search, knowledge base, database management systems and databases, and data mining systems (Chen & Xu, 2010). Firstly, the expert system refers to an intelligent programming system, which solves the problems it has been fed to solve in the area of specialty. The expert system accumulates knowledge and experience over the years after being used repeatedly to solve complex problems that only expert individuals can solve (Matayong & Mahmood, 2013).

Secondly, the knowledge search refers to the search engine and agent-based knowledge hunt methods that the information base system uses to gather knowledge in response to queries that the user feeds to the system (Chen & Xu, 2010). It is worth noting that a knowledge-based system constitutes a large volume of various information prompts that have to be searched to find the relevant knowledge that is needed for a specific task. The knowledge search utilises neural networks, rough sets, and fuzzy clustering and statistics among other methods to mine knowledge (Chen & Xu, 2010).

The third important component of the knowledge-based system is the knowledge base, which constitutes three categories as discussed by Chen and Xu (2010). These categories include the external knowledge base, structured knowledge base, and the unstructured internal knowledge base. The external knowledge base stores the knowledge that has been acquired from the organisation’s network. Such knowledge is majorly in the form of data and factual contents. The well-thought-out knowledge base uses structured ways to store easily accessible knowledge. It constitutes information that has been entered by the knowledge engineers during its inception.

On the other hand, the unstructured knowledge refers to the knowledge that the system accumulates with time (Chen & Xu, 2010). Lastly, the database management systems and databases are important parts of the knowledge base system. Databases are important for storing data or information that is used to create knowledge that is consequently used to drive the effectiveness of the knowledge-based system.

The Application of Knowledge-Based Systems

According to Bechina and Ndlela (2007), the use of knowledge-based systems is greatly enshrined in modern organisations in all sectors of the economy. The complexity and competitiveness of the world’s business environment, the information that must be processed for good decision-making is enormous. Hence, a knowledge-based system offers an outright competitive advantage (Lau et al., 2005). Due to the benefit that knowledge-based systems offer to organisations, they are applied in different sectors and for various purposes as it will be discussed in the following section.

Knowledge-Based Systems and Quality Assurance

In today’s fast-paced world, there is no room for mistake. Customers demand the best service or product to appreciate the value of their money. Ensuring consistency in the quality of services and products is a key factor that organisations are keen on maintaining to remain competitive (Matayong & Mahmood, 2013). Quality assurance management systems have become a critical aspect of any organisation that seeks to attract customers and/or achieve customer loyalty at all levels. Any small mistake can easily spell doom in a company’s business by costing it thousands of dollars or even pushing it out of the market.

According to Matayong and Mahmood (2013), the increased global competition has pushed organisations to embrace shorter product lifecycles. Further, consumers’ demand for lower costs, greater performance, product varieties, and advancements in microelectronics has pushed products and manufacturing systems to become more complex to adapt to the market dynamics (Matayong & Mahmood, 2013). Such changes in the fast-paced world mean that organisations are facing a greater challenge of guaranteeing quality services and products while at the same time ensuring that they meet the rapidly changing customer demands (Lau et al., 2005).

One of the key approaches that organisations are highly advised to use is the combination of knowledge-based systems with the manufacturing or production systems. The strategy addresses complex processes and problems as they arise to guarantee seamless production and delivery of services (Dimitrios, 2012). As Matayong and Mahmood (2013) confirm, knowledge-based systems are important, especially in addressing problems that arise from the use of optimisation techniques. The knowledge-based systems allow the production processes to be easier since the organisation can manage its quality assurance information system (QAIS). The process of making important decisions that go towards quality assurance and production of eminent products and services requires fast and accurate decision-making.

The process must be considerate of all factors and functions that influence quality (Matayong & Mahmood, 2013). In this case, a computer-based decision support system forms a very critical part of the production processes. However, ensuring that the decision support system (DSS) is effective requires a solid and a complete knowledge and information base that combines all functions that relate to production and quality (Matayong & Mahmood, 2013).

The application of knowledge-based system in the production and manufacturing processes is a great addition to the problem-solving and decision-making systems that ensure smooth running and production optimisation to keep at pace with the demand for the modern and fast moving world of business (Matayong & Mahmood, 2013). Knowledge-based systems are used as problem processing systems where they provide information from a knowledge base that is used to generate and provide useful solutions and information to address the problems at hand in real-time or as fast as possible to ensure continuity of the production processes (Matayong & Mahmood, 2013).

The implementation of a knowledge-based system in the quality assurance information system lifts the burden from line mangers and specialists from addressing routine issues of production to more complex matters and problems in the production chain (Dimitrios, 2012). The use of the knowledge-based system allows non-expert and non-technical specialists to make accurate and critical decisions in ensuring successful production (Kiessling et al., 2009). At the end, it is evident that the use of knowledge-based system is a very critical part of ensuring smooth production and manufacturing processes, which give organisations a competitive advantage. Such organisations can then respond to the increasing customer demands for quality of products and services.

Knowledge-Based System and Healthcare Services

Healthcare is a critical sector that is directly concerned with the wellbeing of human beings. The sensitivity of healthcare services means that health care service providers have to make critical decisions where any mistake can lead to the escalation of situations into matters of life and death (Dimitrios, 2012). The provision of health care services has evolved significantly over the years because of technology and the increased research and development agendas, which have led to the emergence of new and advanced healthcare technologies and procedures that can address the previously difficult health care demands with ease (Dimitrios, 2012).

The sensitivity that surrounds healthcare services means that care providers have to make important decisions that adhere to the clinical and medical guidelines and evidence-based rules that emanate from medical science (Dimitrios, 2012). However, the magnitude of the decisions that the practitioners have to make, especially in emergencies makes it very challenging for practitioners to make the right decisions all the time (Dimitrios, 2012). In other words, choosing the decision that one has to go with from a myriad of evidence-based options that are available for each medical situation is a major challenge.

The situation can be costly to the service provider, as well as the service seeker or patient (Dimitrios, 2012). To avoid or minimise the challenges that are evident in the healthcare sector, knowledge-based systems become very crucial tools for guiding the decision-making process (Kiessling et al., 2009). They lead to better healthcare outcomes. The use of knowledge-based systems in healthcare allows doctors and nurses to interpret large-scale patient data using knowledge and evidence-based methods, which are vital for fast diagnosis and treatment decisions (Dimitrios, 2012). For example, the knowledge-based systems store and process information that relates to patients’ medical history. Besides examining real-time data from diverse diagnosis devices, the systems compare the common characteristics and trends in medical record databases to ensure fast decision-making.

The effectiveness of knowledge-based systems in a healthcare service provision setting requires the availability of adequate and relevant information that can easily aid in clinical decision-making (Dimitrios, 2012). Such knowledge must be transformed into actionable intelligence within a timely and accurate manner that can be interpreted well by different functional workgroups that are mandated with handling the case in point (Matayong & Mahmood, 2013). The following diagram represents the knowledge cycle in a health care service provision setting.

Knowledge Cycle for Healthcare Setting.
Figure 3: Knowledge Cycle for Healthcare Setting. Source: (Dimitrios, 2012)

In summary, knowledge-based systems can help in ensuring quality provision of healthcare services by assisting in the decision-making processes at both the patient and the population level (Dimitrios, 2012). For instance, knowledge-based systems can be used in diagnosis by regularly interpreting and monitoring patient data. Secondly, they can be used to help in the management of chronic diseases by establishing benchmarks and alerts for timely responses (Dimitrios, 2012). Thirdly, knowledge-based systems can be used to help public health surveillance by storing and interpreting large amounts of data, which can help in identification of pandemic diseases or chronic disease surveillance (Dimitrios, 2012). Lastly, using data that has been stored for a client, the knowledge-based systems can help in clinical decision-making processes such as preventing drug-to-drug interactions. Such decision support is critical.

In some cases, since doctors and nurses may be unaware of prescriptions reactivity, they may endanger a patient’s health (Matayong & Mahmood, 2013). A knowledge-based system, with its vast amount of data that relates to health care, can notify a doctor or any other practitioner early in advance concerning the possibility of drug-to-drug reaction, hence leading to better decision-making. Concisely, knowledge-based systems are important in healthcare management since they allow a room for better and faster diagnosis and treatment of patients and hence better outcomes for health care services.

Knowledge-Based Systems and Procurement Decision-making

In the business world, purchasing and selling are two important strategic aspects of a successful business. In this case, buyers and suppliers are very critical stakeholders for the success or failure of any business at all levels (Kiessling et al., 2009). With the emergence of technology and globalisation, the strategic actions that relate to the buying decision or purchasing management have become vital and indeed key parts of an organisation’s competitive advantage (Lau et al., 2005). Organisations must make critical and strategic purchasing decisions upon which they can peg their success in the market.

In making strategic decisions that relate to purchasing, the decision-making process is a difficult one, especially when considering the myriad of variables that the choice makers in an organisation have to consider before coming up with the strategic decisions that relate to purchasing (Matayong & Mahmood, 2013). To ensure that the purchasing decisions are the strategic, organisations are increasingly adopting knowledge-based systems to guide this rigorous process. As opposed to the previous purchasing decision where the focus was only on getting the best price for supplies, the present-day purchasing decisions must incorporate other important factors such as quality and delivery time (Lau et al., 2005).

These variables are increasingly making it more difficult for human beings, without the aid of expert systems, to make timely decisions that can support an organisation’s goals of quality and punctuality in the delivery of services and goods. Other important variables include delivery reliability, cost capability, technical capability, and financial stability of the supplier, which must be considered if a business is keen on ensuring success in its areas of operation (Lau et al., 2005).

To maintain a solid control and management of an organisation’s purchasing function, knowledge-based systems play an important role in ensuring fast and accurate purchasing decisions relating to the purchasing decision process. A knowledge-based system stores a vast amount of information and facts that relate to the various suppliers, as well as their characteristics such as distribution consistency, cost competence, procedural aptitude, and commercial steadiness, which are all important in determining their cost effectiveness in an organisation (Lau et al., 2005). For example, a supplier who provides poor quality supplies within a short time may not offer the required competitive advantage when compared with another supplier who offers quality supplies but within a longer time lead (Dimitrios, 2012).

In another example, a supplier who cannot keep up with the demand for the supplies that are needed by an organisation may leave the organisation with a bad reputation for not being able to deliver services within the customer-specified timeframes (Lau et al., 2005). Such a bad reputation may lead to losses for the company. Therefore, it is important for an organisation to put in place an elaborate knowledge-based system to ensure that all purchasing decisions can be made accurately and appropriately to support the organisation’s punctual delivery of services and goods to customers without compromising their quality and cost (Kiessling et al., 2009).

The customer is a very powerful stakeholder in an organisation since he or she is the one through whom an organisation thrives. In this case, with the availability of substitute goods or service providers, the customer has increasingly become very powerful in the determination of the kind of services or goods that organisations choose to provide (Lau et al., 2005). Further, customer demands have become more varied and difficult to meet, yet the quality demands have increased drastically (Lau et al., 2005). To meet the customer-specific demands for the final product or service, organisations must make explicit and unique procurement decisions in ensuring that the customer receives the right product or service (Lau et al., 2005). The organisations that meet the unequivocal customer demands are more likely to attract customer loyalty while those that cannot meet these demands find themselves struggling to survive in the competition process (Dimitrios, 2012).

Therefore, the knowledge-based system is an important tool that allows procurement personnel to make unique decisions that relate to the procurement of inputs to meet varied customer demands without negotiating quality for the customer and profits for the organisation (Lau et al., 2005). Concisely, the knowledge-based system supports the purchasing decision-making process by ensuring that different variables that are relevant to the organisation and the customer are made in a timely manner to guarantee quality and apt delivery of the final product or service while at the same time giving the best value for the organisation in terms of customer satisfaction and profitability.

Knowledge-Based System in Institutions of Learning

Learning institutions provide knowledge to students, as well as other interested parties. They are an authority in their own right, yet they have been slow to adapt new knowledge in teaching and delivery of the relevant content to students (Rah et al., 2010). However, with the availability of knowledge and information in the internet and/or through other technologies, these institutions no longer hold the monopoly to new knowledge since it is easily accessible via the internet. In addition, the institutions are more on the spotlight for failing to provide relevant knowledge and skills that are needed in the fast-paced world. The situation has led to unprepared and under-skilled graduates whose incompetence has forced organisations to spend many resources to re-train them (Dimitrios, 2012).

The above trend is likely to change with the adoption of knowledge-based systems, which can help trainers and students to access relevant information that can help them to provide or acquire the right knowledge and skills that are needed in the current world (Dimitrios, 2012). For instance, the use of knowledge-based systems in libraries allows institutions of learning to manage vast amounts of information and data that students require in their learning (Rah et al., 2010). Further, it allows students to access the correct and relevant information that is needed to address different problems that they seek to solve in their learning process. In complex courses such as engineering and medicine among others, providing knowledge-based systems can allow tutors and students to access important information and tutorials that guide in the process of teaching and learning (Matayong & Mahmood, 2013).

In the teaching process, teachers are also exposed to various teaching approaches, which they can use to deliver new knowledge to students (Bechina & Ndlela, 2007). However, choosing the specific pedagogy becomes a daunting challenge, which can be greatly supported through knowledge base (Kiessling et al., 2009). In this case, the knowledge-based system stores and provides important insights into the approaches that tutors can use to approach the teaching of respective disciplines. With such aid, teachers ensure that they can use the approaches that are best suited to deliver the best outcomes for the students (Rah et al., 2010). While knowledge-based systems that focus on learning institutions have evolved slowly due to the varied disciplines and knowledge depths in the education sector, their role cannot be underestimated. With time, it is evident that knowledge-based system will become critical parts of any quality education provision.

The Future Trends of Knowledge-Based Systems

As technology advances and globalisation increases, knowledge-based systems will develop to adapt to these changes (Chen & Xu, 2010). In the past and even the present, organisations have operated as standalones. They have separate supply chains, management, and other aspects that make them unique in the business segments (Matayong & Mahmood, 2013). However, with the increasing interdependence of organisations, it will become important for knowledge-based systems to include and incorporate these increasing levels of collaboration between organisations in various stages of production.

For example, more and more organisations are increasingly becoming involved in the production of supplies where they closely monitor the activities of the suppliers to ensure quality and timeliness of supplies (Chen & Xu, 2010). In such a case, organisations will have to incorporate knowledge-based systems that can guarantee the monitoring and control of production process starting from the production of the supplies.

The use of online knowledge-based systems is also another emerging trend that will redefine the future of the use and application of knowledge-based systems (Rah et al., 2010). The sharing of knowledge through these systems may bring unforeseen problems that relate to trust and accuracy of the knowledge that is contained therein. Virtual organisations are also an emerging phenomenon, which poses new challenges into how organisations will share knowledge or information that is critical for successful delivery of services and products (Rah et al., 2010). Regardless of the above challenges and issues, advancements in technology will lead to more adoption of knowledge-based technologies in more fields in the globalised future world.

Main Theoretical and Application Contents of the Project

Knowledge-based systems have attracted a lot of attention in terms of their application in real-life and in theoretical studies that seek to explain complex challenges that such systems pose in today’s world. In terms of application, this project has exposed important areas where the knowledge-based systems have been applied, their evolution, and the expected trends. It is evident that the knowledge-based systems have come in at the right time when competition has increased drastically because of technological developments and globalisation where the world has become a small village (Matayong & Mahmood, 2013).

As organisations seek to remain competitive and at pace with global trends and customer needs, it is evident that knowledge-based systems form an important segment of the change where they fill the gaps in knowledge and skills that are needed in real time for decision making in critical business processes and activities (Kiessling et al., 2009). As discussed in the literature review, the scope of the areas that knowledge-based systems are applied is very wide. The future trends show that this scope will increase to cover even virtual organisations.

Despite the growing application of knowledge-based studies, theoretical studies will be needed to identify and project the impacts and influences of the increasing use of knowledge-based systems in the modern and future business environment (Dimitrios, 2012). Theoretical applications of knowledge-based systems allow researchers to dream big in terms of the areas where knowledge-based systems can be applied, as well as helping in projecting the various problems that may arise in their application (Dimitrios, 2012). In addition, coming up with possible solutions for various problems that are projected for the knowledge-based systems allows the business world to be ready for any eventualities. In this case, the project has provided important insights that will be key factors for consideration in the future knowledge-based systems where the internet will be a major part of these systems. The systems will present new challenges in terms of ethical considerations during the process of sharing information among other factors that must be considered for their effectiveness.


Knowledge-based systems are very critical segments that define business competitiveness in the highly competitive modern world. Knowledge-based systems provide organisations with a platform where they can easily access and manage knowledge that is critical for decision-making. Due to competition and globalisation, decisions have to be made while considering not only the varied amounts of data and information volumes that are at the disposal of the decision makers but also the set timeframe to meet the ever-changing business environment and customer demands. As discussed in the paper, the effectiveness of a knowledge-based system is highly dependent on the amount of knowledge that has been input into the system by the experts. To ensure that such systems are even more effective, it is important to ensure that they can record and keep new knowledge to warrant adaptability and hence relevance of the knowledge in the end.

The application of knowledge-based systems touches on many areas of the world of business and the public sector such as quality assurance, education, healthcare, and procurement among others. These sectors clearly show that knowledge-based systems can be adapted to all areas of business and hence the likely trend in the future of knowledge-based systems where the world is expected to become more competitive. Technology will most likely influence how the future knowledge-based systems will be applied. Of these technologies, the increasing use and application of internet will be a critical factor that will influence the conception and application of knowledge-based systems.

Appendices: Value of the Project

The Relationship between the Project Contents and the Title of the Project

The project discusses the key aspects that relate to knowledge-based systems, its evolution, and how it has become enshrined into the modern world of business. The contents of the project relate well with the title of the project, “Knowledge-Based System”, which has been well covered in the paper, despite it being a broad topic.

Insight and Scientific Value of the Project

The project has offered important insights into the use and application of knowledge based systems. Knowledge-based systems are of significant scientific value since the makes important revelations that relate to the future trends of knowledge dissemination techniques and their applications in the future businesses and organisations.

Reference List

Bechina, A., & Ndlela, M. (2007). Success Factors in Implementing Knowldge Based Systems. Journal of Knowledge Management, 7(2), 211-218. Web.

Chen, Z., & Xu, X. (2010). Study on Construction of Knowledge System Based on Enhancing Core Competencies of Industrial Clusters. International Journal of Business and Management, 5(3), 217-222. Web.

Dimitrios, K. (2012). Knowledge Based Management in the Health System. Review of International Comparative Management, 13(2), 284-293. Web.

Kiessling, T., Richey, R., Meng, J., & Dabic, M. (2009). Exploring Knowledge Management to Organisational Performance Outcomes in a Transitional Economy. Journal of World Business, 44(1), 421-433. Web.

Lau, H., Ning, A., Pun, K., Chin, K., & Ip, W. (2005). A Knowledge-Base System to Support Procurement Decision. Journal of Knowledge Management, 9(1), 87-100. Web.

Matayong, S., & Mahmood, A. (2013). The Review of Approaches to Knowledge Management System Studies. Journal of Knowledge Management, 17(3), 472-490. Web.

Rah, J., Gul, S., & Wani, Z. (2010). University Libraries: Step Towards a Web Based Knowledge Management System. Journal of Information and Knowledge Management Systems, 40(1), 24-38. Web.

Cite this paper

Select style


Premium Papers. (2023, January 14). Knowledge Based Systems and Their Relevance. Retrieved from


Premium Papers. (2023, January 14). Knowledge Based Systems and Their Relevance.

Work Cited

"Knowledge Based Systems and Their Relevance." Premium Papers, 14 Jan. 2023,


Premium Papers. (2023) 'Knowledge Based Systems and Their Relevance'. 14 January.


Premium Papers. 2023. "Knowledge Based Systems and Their Relevance." January 14, 2023.

1. Premium Papers. "Knowledge Based Systems and Their Relevance." January 14, 2023.


Premium Papers. "Knowledge Based Systems and Their Relevance." January 14, 2023.