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Mining Domain Knowledge [Requirements]

IEEE Software, 2015
Basic data-mining skills can be useful for processing domain documents early during requirements engineering. An example from the electronic-healthcare-records domain shows how. The Web extra at http://youtu.be/tHvi3pHEP8c is an audio podcast in which author Jane Cleland-Huang provides an audio recording of the Requirements column, in which she ...
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Knowledge representation as domain

Journal of Applied Non-Classical Logics, 1997
ABSTRACT This is a continuing attempt in a series of papers [KM 93, Mur 93, Mur 96] to show how computer-represented knowledge can be arranged as elements of an effectively represented semantic (or algebraic) domain in the sense of [GS 90]. We present a direct deductive description of the domain, which was defined semantically in [KM 93], via the Scott'
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Confidence from Self-knowledge and Domain Knowledge

2003
The GRAVA architecture supports building self-adaptive applications. An overview of the GRAVA architecture, its agent language and its reflective protocol are presented with illustrations from the aerial image interpretation domain.
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Applying Domain Knowledge

2022
Jan Rauch, Milan Šimůnek, David Chudán, Petr Máša   +3 more
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Acquisition of Domain Knowledge

2003
Linguistic knowledge in Natural Language understanding systems is commonly stratified across several levels. This is true of Information Extraction as well. Typical state-of-the-art Information Extraction systems require syntactic-semantic patterns for locating facts or events in text; domain-specific word or concept classes for semantic generalization;
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The Domain of Knowledge

1972
The principle, “The per accidens necessarily implies the per se” has been examined thus far in its chief instances as found in St. Thomas’ writings on physics and metaphysics. Yet, in order to make certain that no radically different employment of the principle by St.
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Domain knowledge

2001
Saul I. Gass, Carl M. Harris
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Knowledges and Domains

2023
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Knowledge Domains and Domain Learning

2010
L. Maggioni, P.A. Alexander
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Tracking Latent Domain Knowledge

2003
A common assumption behind measuring the importance of a phenomenon is that the more often a phenomenon is observable, the more important it is likely to be. For example, we tend to think a topic is important if we hear it a lot. In this chapter, we explore the opposite of this assumption.
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