A Framework for Acquiring Temporal-Abstraction Knowledge

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Citation: Yuval Shahar and Manfred Aben and Mark A. Musen. (1993) A Framework for Acquiring Temporal-Abstraction Knowledge. In , January,1993.

Publication techreport ( Edit )
type Technical Report
bibtype techreport
Bibtex basics
author Yuval Shahar and Manfred Aben and Mark A. Musen
title A Framework for Acquiring Temporal-Abstraction Knowledge
number KSL-93-02
institution Knowledge Systems, AI Laboratory
year 1993
month January
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abstract We formally describe a framework that we suggested previously for abstracting time-stamped data and sharing the domain-specific knowledge needed for this task. The temporal-abstraction (TA) task is an important part of general tasks such as pattern recognition over time and planning (e.g., forming and revising therapy plans for patients). The TA task is decomposed by the suggested TA method into several subtasks achieved by three basic TA mechanisms: point temporal abstraction, for abstracting values of several temporally coexistent parameter values into a value of another parameter; temporal inference, for inferring domain-specific sound logical conclusions for a single temporal interval or two meeting intervals; and temporal interpolation, for bridging nonmeeting temporal intervals. The TA method has also been implemented as a system, RESUME. We then show how this framework can be formally specified as inferences in the KADS knowledge-modeling methodology, thus proposing a platform for modeling and sharing domain-independent TA inference knowledge. Making explicit the knowledge required for TA and formalizing the semantics of the mechanisms involved supports the acquisition of that knowledge by automatically generated tools and emphasizes the advantages of a modular, task-specific but domain-independent architecture for designing knowledge-based systems.

KSL Technical Report ID: KSL-93-02
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Abstract We formally describe a framework that we s … We formally describe a framework that we suggested previously for abstracting time-stamped data and sharing the domain-specific knowledge needed for this task. The temporal-abstraction (TA) task is an important part of general tasks such as pattern recognition over time and planning (e.g., forming and revising therapy plans for patients). The TA task is decomposed by the suggested TA method into several subtasks achieved by three basic TA mechanisms: point temporal abstraction, for abstracting values of several temporally coexistent parameter values into a value of another parameter; temporal inference, for inferring domain-specific sound logical conclusions for a single temporal interval or two meeting intervals; and temporal interpolation, for bridging nonmeeting temporal intervals. The TA method has also been implemented as a system, RESUME. We then show how this framework can be formally specified as inferences in the KADS knowledge-modeling methodology, thus proposing a platform for modeling and sharing domain-independent TA inference knowledge. Making explicit the knowledge required for TA and formalizing the semantics of the mechanisms involved supports the acquisition of that knowledge by automatically generated tools and emphasizes the advantages of a modular, task-specific but domain-independent architecture for designing knowledge-based systems. ure for designing knowledge-based systems.
Author Yuval Shahar and Manfred Aben and Mark A. Musen  +
Bibtype techreport  +
Has author Yuval Shahar and Manfred Aben and Mark A. Musen  +
Has identifier KSL-93-02  +
Has publishing details January,1993  +
Has title A Framework for Acquiring Temporal-Abstraction Knowledge  +
Has year 1993  +
Institution Knowledge Systems, AI Laboratory  +
Ksl tr id KSL-93-02  +
Month January  +
Number KSL-93-02  +
Process note NO  +
Title A Framework for Acquiring Temporal-Abstraction Knowledge  +
Year 1993  +
Retrieved from "http://tw.rpi.edu/wiki/A_Framework_for_Acquiring_Temporal-Abstraction_Knowledge"
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