1. What are the contributions in "Ernest: a semantic network system for pattern understanding" ?
Aktract-This paper gives a detailed account of a system environment for the treatment of general problems of image and speech understanding.
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ERNEST: a semantic network system for pattern understanding
TL;DR: The authors give a detailed account of a system environment for treating general problems of image and speech understanding by providing a framework for representing declarative and procedural knowledge based on a suitable definition of a semantic network.
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Abstract: The authors give a detailed account of a system environment for treating general problems of image and speech understanding. A framework for representing declarative and procedural knowledge based on a suitable definition of a semantic network is provided. The syntax and semantics of the network are clearly defined. The pragmatics of the network in its use for pattern understanding are defined by several rules which are problem-independent. This allows one to formulate problem-independent control algorithms. Complete software environments are available to handle the described structures. The general applicability of the network system is demonstrated by short descriptions of three applications from different task domains. >
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Citations
Mathematical Theory of Computation
John J. McCarthy
- 01 Aug 1991
TL;DR: The goals of this project were the development of logical formalisms for reasoning about programs that use abstractions and reflection, and the application of these theoretical results to selected software problems.
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Patent
Information extraction from a database
Sergey Brin
- 14 Sep 2012
TL;DR: In this article, techniques for extracting information from a database such as the Web are described. But they do not address the problem of identifying a pattern in which the tuples of information were stored.
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A new representation of knowledge concerning human anatomy and function.
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TL;DR: By integrating concepts of computer graphics and artificial intelligence, novel ways of representing medical knowledge become possible and allow unprecedented possibilities ranging from three-dimensional interactive atlases to systems for surgery rehearsal.
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SAR Sea-Ice Image Analysis Based on Iterative Region Growing Using Semantics
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TL;DR: The algorithm is a general-segmentation approach named iterative region growing using semantics, which is dedicated to the problem of classifying the operational SAR sea-ice imagery provided by the Canadian Ice Service (CIS).
Control and explanation in a signal understanding environment
TL;DR: A problem-independent control algorithm for the interpretation of sensor signals is presented which provides both data-driven and model-driven control structures which can easily be combined to perform any mixed strategy.
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