TAILIEUCHUNG - Báo cáo khoa học: "SEHANTICS OF TEHPORAL QUERIES AND TEHPORAL DATA"

This paper analyzes the requirements for adding a temporal reasoning component to a natural language database query system, and proposes a computational model that satisfies those requirements. A prelimInary implementation in Prolog is used to generate examples of the model's capabi Iltles. I. Introduction A major area of weakness in natural language (NL) interfaces is the lack of ability to understar~ and answer queries involving time. | SEMANTICS OF TEMPORAL QUERIES AND TEMPORAL DATA Carole D. Hafner College of Computer Science Northeastern University Boston MA 02115 Abstract This paper analyzes the requirements for adding a temporal reasoning component to a natural language database query system and proposes a computational model that satisfies those requirements. A preliminary implementation in Prolog is used to generate examples of the model s capabilities. I. Introduction A major area of weakness In natural language NL interfaces is the lack of ability to understand and answer queries involving time. Although there is growing recognition of the importance of temporal semantics among database theoreticians see for example Codd 61 Anderson 21 Clifford and Warren 41 Snodgrass 151 existing database management systems offer little or no support for the manipulation of time data. Furthermore as we will see In the next Section there is no consensus among researchers about how such capabilities should work. Thus the developer of a NL interface who wants to support time-related queries cannot look to an underlying DBMS for help. Currently available NL systems such as Intellect 81 have not attempted to support temporal queries except in a trivial sense. In Intellect users can ask to retrieve date attributes . When was Smith hired or enter restrictions based on the value of a date attribute . List the employees hired after Jan I 1984 but more complex questions such as How long has It been since Smith received a raise or What projects did Jones work on last January are not understood. This is a serious practical limitation since the Intended users of NL systems are executives and other professionals who will require more sophisticated temporal capabilities. This report describes a model of temporal reasoning that Is designed to be incorporated Into a NL query system. We assume that a syntactic component could be developed to translate explicit temporal references in English . two years ago into .

• Báo cáo khoa học
• SEHANTICS OF TEHPORAL QUERIES
• TEHPORAL DATA
• Carole O
• Hafner
• 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
• Long Papers
• 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