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Knowledge-Based Systems is a peer-reviewed academic journal covering computer science, with a particular focus on knowledge-based systems. It was established in 1987 and is published 24 times per year by Elsevier. The editor-in-chief is Jie Lu (University of Technology Sydney).
International Journal of Software Engineering and Knowledge Engineering; International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems; International Journal of Wavelets, Multiresolution and Information Processing; International Journal of Web Services Research; International Journal of Wireless Information Networks
The first knowledge-based systems were primarily rule-based expert systems. These represented facts about the world as simple assertions in a flat database and used domain-specific rules to reason about these assertions, and then to add to them. One of the most famous of these early systems was Mycin, a program for medical diagnosis.
An expert system is an example of a knowledge-based system. Expert systems were the first commercial systems to use a knowledge-based architecture. In general view, an expert system includes the following components: a knowledge base, an inference engine, an explanation facility, a knowledge acquisition facility, and a user interface. [48] [49]
International Journal of Software Engineering and Knowledge Engineering International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems International Journal of Wavelets, Multiresolution and Information Processing
The following is a list of information systems journals, containing academic journals that cover information systems. The list given here contains the most influential, currently publishing journals in the field.
This list covers the journals, magazines, periodicals already published and continuing in the discipline of library and information science (LIS). It doesn't include ceased titles, predatory journals. Missing titles or information can be added to the list with relevant sources and help in updating it.
Knowledge representation goes hand in hand with automated reasoning because one of the main purposes of explicitly representing knowledge is to be able to reason about that knowledge, to make inferences, assert new knowledge, etc. Virtually all knowledge representation languages have a reasoning or inference engine as part of the system.