TAILIEUCHUNG - Báo cáo khoa học: "Semantics of Conceptual Graphs"

The resulting graph is a nucleus for constructing models of possible worlds in which the sentence is true. • Laws of the world behave like demons or triggers thai monitor the models and block illegal extensions. • If a surface model could be extended infinitely deep, the result would be a complete standard model. This approach leads to an infinite sequence of algorithms ranging from plausible inference to exact deduction; they are analogous to the varying levels of search in game playing programs. . | Semantics of Conceptual Graphs John F. Sowa IBM Systems Research institute 205 East 42nd Street New York NY 10017 ABSTRACT Conceptual graphs are both a language for representing knowledge and patterns for constructing models. They form models in the Al sense of structures that approximate some actual or possible system in the real world. They also form models in the logical sense of structures for which some set of axioms are true. When combined with recent developments in nonstandard logic and semantics conceptual graphs can form a bridge between heuristic techniques of Al and formal techniques of model theory. 1. Surface Models Semantic networks are often used in Al for representing meaning. But as Woods 1975 and McDermott 1976 observed the semantic networks themselves have no well-defined semantics. Standard predicate calculus does have a precisely defined model theoretic semantics it is adequate for describing mathematical theories with a closed set of axioms. But the real world is messy incompletely explored and full of unexpected surprises. Furthermore the infinite sets commonly used in logic are intractable both for computers and for the human brain. To develop a more realistic semantics Hintikka 1973 proposed surface models as incomplete but extendible finite constructions Usually models are thought of as being given through a specification of a number of properties and relations defined on the domain. If the domain is infinite this specification as well as many operations with such entities may require non-trivial set-theoretical assumptions. The process is thus often non-finitistic. It is doubtful whether we can realistically expect such structures to be somehow actually involved in our understanding of a sentence or in our contemplation of its meaning notwithstanding the fact that this meaning is too often thought of as being determined by the class of possible worlds in which the sentence in question is true. It seems to me much likelier that what is .

• Báo cáo khoa học
• Semantics of Conceptual Graphs
• John F
• Sowa
• Long Papers
• scientific reports
• model language
• process natural language
• Dialog Control
• Natural Language System
• Dialog Control in a Natural Language System
• Expanding the Horizons
• Natural Language Interfaces
• Phil Hayes
• PROSPECTS OR PRACTICAL
• NATURAL LANGUAGE SYSTEMS
• Workshops
• NATURAL LANGUAGE
• INTERACTION WITH MACHINES
• COMPUTER INTEBFACE DESIGN MURRAY TUROFF DEPARTMENT OF COMPUTER
• IiVFORMATION SCIENCE IIEW JERSEY INSTITUTE OF TECHNOLOGY
• EVALUATION OF NATURAL LANGUAGE
• INTERFACES TO DATABASE SYSTEMS
• A PANEL DISCUSSION
• database query system
• J
• Norwood Crout
• INTERFACES TO DATA BASE SYSTEMS
• Bozena Henisz
• INTERPRETING NATURAL LANGUAGE
• DATABASE UPDATES
• S
• Jermld Kaplan Jim David
• TRANSPORTABLE NATURAL LANGUAGE
• INTERFACES TO DATABASES
• Gary G
• Hendrlx and William H
• Lewis
• DATABASES THEORETICAL
• TECHNICAL ISSUES
• TRANSPORTABLE NATURAL LANGUAGE INTERFACES
• PROBLEMS AND TECHNIQUES
• Barbara J
• Grosz
• THEORETICAL TECHNICAL ISSUES
• NATURAL LANGUAGE ACCESS TO DATABASES
• R
• Petrick
• Domain Independent
• Database Access Systems
• ISSUES IN NATURAL LANGUAGE
• ACCESS TO DATABASES
• A LOGIC PROGRAMMING PERSPECTIVE
• Sharon C
• Salveter David Maier
• PLANNING NATURAL LANGUAGE
• EXPRESSIONS REFERRING
• Douglas E
• Appelt
• THE TEXT SYSTEM
• NATURAL LANGUAGE GENERATION
• Kathleen R
• M
• MENTING A DATABASE
• KNOWLEDGE REPRESENTATION
• THE KEY TO THE SELECTION PROBLEM
• E
• Jeffrey Conklin David D
• McDonald
• A KNOWLEDGE ENGINEERING
• NATURAL LANGUAGE UNDERSTANDING
• Stuart C
• Shapiro
• NATURAL LANGUAGE TEXTS
• NECESSARILY GRAMMATICAL
• EVEN COMPLETE
• UNGRAMHATICALITY
• EXTRA GRAMMATICALITY
• NATURAL LANGUAGE UNDERSTANDING SYSTEMS
• Taxonomy
• Descriptions
• Individuals in Natural
• Language Understanding
• The Use of Ooject Special Knowledge
• Natural Language Processing
• Mark H
• Bursteln