knowledge representation languageの例文

• Knowledge Representation languages have also lacked easy readability.
• A knowledge representation language may be sufficiently expressive to describe nuances of meaning in well understood fields.
• Daniel G . Bobrow, Terry Winograd, An Overview of KRL, A Knowledge Representation Language, Stanford Artificial Intelligence Laboratory Memo AIM 293, 1976.
• If the knowledge representation language enables to express both, then the knowledge model and the information model can be expressed in the same language ( or data structure ).
• Thus, those languages can be used as knowledge representation languages, and writing of those languages is supported by fully automatic consistency and redundancy checks, query answering, etc.
• "' Loom "'is a knowledge representation language developed by researchers in the artificial intelligence research group at the University of Southern California's Information Sciences Institute.
• Usually the knowledge representation language only allows to represent knowledge ( about kinds of things ), whereas another language or data structure is required to represent and store the information models about individual things.
• In particular, projects such as Narrative Knowledge Representation Language ( NKRL ) leveraged the use of markup languages for the representation of the narrative content of text, revamping the use of frames into the emerging scenario of media indexing and retrieval.
• Mitola's Licentiate thesis, published in August, 1999 includes the following quote " Over time, the [ Radio Knowledge Representation Language ] RKRL-empowered network can learn to distinguish a feature of the natural environment that does not match the models.
• Next come built-in inference engines and information extraction facilities, and the support of meta-ontologies such as OWL-S, Dublin Core, etc . Another important feature is the ability to import & export foreign knowledge representation languages for ontology matching.
• 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.