Discrete mathematics
Prolog and natural-language analysis
Prolog and natural-language analysis
Representations of commonsense knowledge
Representations of commonsense knowledge
Artificial intelligence (2nd ed.): structures and strategies for complex problem-solving
Artificial intelligence (2nd ed.): structures and strategies for complex problem-solving
What Are Ontologies, and Why Do We Need Them?
IEEE Intelligent Systems
Ontology development as undergraduate research
Journal of Computing Sciences in Colleges
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Ontologies are used to create knowledge base systems and vocabularies that are effective in representing a particular field or domain. This research explores ways of managing combinatorial explosion in ontologies. The test domain for the research will be the Caspor system. Computer Algebra Story Problem ORiginator is a set of prolog programs used for random generation of algebra word problems. Caspor was developed at Xavier University of Louisiana to help beginning problem solvers enhance their algebra problem solving skills. Caspor uses an ontology to represent information about contexts of word problems; for example, vehicles, rates, and distances. Presently, the Caspor ontology is represented by means of prolog unit clauses together with predicates that supply the information to the rest of the system. We are exploring the suitability of a third-party ontology description language (ODL) to use for this purpose as an alternative. Two such ODLs are Back and Classic. Back (Berlin Advanced Computational Knowledge representation system) is a KL-One based knowledge representation system that was developed at Technical University. Classic is a knowledge representation system based on description logic. Classic has a framework that allows users to represent descriptions, concepts, roles, individuals, and rules. It also provides most features that are available in a semantic network.