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Taxonomic and Faceted Classification for Intelligent Tagging and Discovery in Net-Centric Command and Control

机译：网络中心指挥控制中智能标记和发现的分类和分面分类

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The success of Net-Centric Operations and Warfare (NCOW) depends upon the ability of net-centric environment (NCE) users both human and automated to readily discover useful information and services. Effective discovery requires, in turn, good semantic metadata tagging (i.e., indexing the functions of the services). Good tagging reflects the contextual relationships among the discoverable artifacts. It derives its value from the soundness and intuitiveness of its underlying approach to information and services classification. Unfortunately, classification soundness is mostly in the eye of the beholder, particularly for services that can be deployed for many different purposes, and not all necessarily foreseen by their initial developers. Ultimately, therefore, what is needed for more rapid and effective tagging and discovery is a services classification approach that accommodates multiple perspectives as to what constitutes a natural and intuitive characterization, plus tools that enable NCE users to take advantage of these capabilities without being overwhelmed by the sheer multiplicity of different classification perspectives. This paper presents a proposed structure for the semantic metadata that we believe will facilitate service and information discovery in the NCE, and will easily accommodate use by intelligent agents.

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