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IEEE Journals & Magazines
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This paper discusses the creation and use of unique identifiers for intellectual property. General concepts applicable to unique identifiers are defined and discussed [identifier, digital object, dumb and intelligent identifiers, readability, affordance or computability, multiple identification, resolution, metadata, persistence, granularity, derivatives (e.g., versions, formats, manifestations, and copies), check digits, and intermediate objects]. Requirements for unique identifiers are reviewed. Capacity issues for an identifier scheme and business issues (cost, antitrust considerations, and intellectual property rights) are explored. Technical and administrative issues of identifiers are discussed, with particular reference to the uses of identifiers, which necessitates intelligence within a system of unique identifiers (scope, protocol independence, multiple roles, fungibility, persistence, standards, and emerging structural metadata approaches). Two brief illustrations of failure in unique identifiers are given. The role of unique identifiers on the Internet is discussed with explanation of the architecture of uniform resource addressing, specifying the resource from a uniform resource name (URN), names and addresses, URN implementations, and a future digital object infrastructure. Brief examples of unique information identifier systems in music, text, and digital objects in general are discussed. Recommendations are made for actions to assist in the development of future identifiers
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IEEE Conference Publications
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In this paper we present an empirical study of relationships between three source code lexicons: the identifier, comment, and literal lexicons. We conjecture that shared and unique properties of these lexicons for the given subject system can inform the configuration of a source code retrieval technique for a particular software understanding activity or software evolution task. Thus, we seek to discover these lexicon properties, and so we investigate five lexicon measures that consider term frequency, term density, and term provenance.
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