Knowledge Representation Techniques Pdf

Knowledge representation techniques pdf

Defining ontologies that are static and incapable of evolving on the fly would be very limiting for Internet-based systems. Cyc was an attempt to build a huge encyclopedic knowledge base that would contain not just expert knowledge but common sense knowledge. Computer architecture Embedded system Real-time computing Dependability. It was not long before the frame communities and the rule-based researchers realized that there was synergy between their approaches.

Knowledge representation and reasoning

After CycL, a number of ontology languages have been developed. Logic machines in fiction and List of fictional computers.

Discrete mathematics Probability Statistics Mathematical software Information theory Mathematical analysis Numerical analysis. The system would begin with a goal. The classifier technology provides the ability to deal with the dynamic environment of the Internet.

Each of these offers a way to see some part of the world. Basic principles of common sense physics, causality, intentions, etc. From Wikipedia, the free encyclopedia. Frames were originally used on systems geared toward human interaction, e. The knowledge recorded in Cyc included common sense models of time, causality, physics, intentions, and many others.

Knowledge representation techniques pdf

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In Ronald Brachman and Hector J. Artificial Intelligence Review. This was a driving motivation behind rule-based expert systems. The commitment made selecting one or another ontology can produce a sharply different view of the task at hand. Integrated systems were developed that combined Frames and Rules.

There is no more powerful formalism than that used by mathematicians to define general propositions about the world. This capability is ideal for the ever-changing and evolving information space of the Internet. There is a long history of work attempting to build ontologies for a variety of task domains, e.

First order logic can be intimidating even for many software developers. Another area of knowledge representation research was the problem of common sense reasoning.

Knowledge representation techniques pdf

Concurrent computing Parallel computing Distributed computing Multithreading Multiprocessing. The Semantic Web seeks to add a layer of semantics meaning on top of the current Internet. It is an abstract description of a category describing things in the world, problems, and potential solutions.

The language they defined was known as CycL. Virtually all knowledge representation languages have a reasoning or inference engine as part of the system. As knowledge-based technology scaled up, the need for larger knowledge bases and for modular knowledge bases that could communicate and integrate with each other became apparent.

Knowledge representation makes complex software easier to define and maintain than procedural code and can be used in expert systems. The automatic classification gives developers technology to provide order on a constantly evolving network of knowledge.

Cyc established its own Frame language and had large numbers of analysts document various areas of common sense reasoning in that language. Ontologies can of course be written down in a wide variety of languages and notations e. Frame languages and automatic classification play a big part in the vision for the future Semantic Web. Rather than indexing web sites and pages via keywords, the Semantic Web creates large ontologies of concepts.

Redirected from Knowledge representation. Searching for a concept will be more effective than traditional text only searches. So for example, not just medical diagnosis as a whole topic, but medical diagnosis of certain kinds of diseases. These systems featured data structures for planning and decomposition. Classifiers focus on the subsumption relations in a knowledge base rather than rules.

Supervised learning Unsupervised learning Reinforcement learning Multi-task learning Cross-validation. Frames were good for representing the real world, described as classes, subclasses, slots data values with various constraints on possible values. Ontology engineering and Ontology language.

In this way the classifier can function as an inference engine, sketching pdf free deducing new facts from an existing knowledge base. The justification for knowledge representation is that conventional procedural code is not the best formalism to use to solve complex problems. Representation and Inference in the Cyc Project. Consider the difference that arises in selecting the lumped element view of a circuit rather than the electrodynamic view of the same device. Information Sciences Institute.

In other projects Wikimedia Commons. Rules were good for representing and utilizing complex logic such as the process to make a medical diagnosis. Lawrence Erlbaum Associates, Inc. For example, talking to experts in terms of business rules rather than code lessens the semantic gap between users and developers and makes development of complex systems more practical.

In addition to expert systems, other researchers developed the concept of frame-based languages in the mids. This reasoner is called the classifier.

Knowledge representation Scientific modeling Programming paradigms Automated reasoning. Currently one of the most active areas of knowledge representation research are projects associated with the Semantic Web. Wikimedia Commons has media related to Knowledge representation.

At the same time as this was occurring, there was another strain of research which was less commercially focused and was driven by mathematical logic and automated theorem proving. As a second example, medical diagnosis viewed in terms of rules e.