Search (3 results, page 1 of 1)

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Abstract

Search statements in this revision process can be viewed as a 'move' in the overall search strategy. Very little is known about how end users develop and revise their search strategies. A study was conducted to analyse the moves made in 244 data base searches conducted by 26 medical students at the University of North Carolina at Chapel Hill. Students search INQUIRER, a data base of facts and concepts in microbiology. The searches were conducted during a 3-week period in spring 1990 and were recorded by the INQUIRER system. Each search statement was categorised, using Fidel's online searching moves (S. Online review 9(1985) S.61-74) and Bates' search tactics (s. JASIS 30(1979) S.205-214). Further analyses indicated that the most common moves were Browse/Specity, Select Exhaust, Intersect, and Vary, and that selection of moves varied by student and by problem. Analysis of search tactics (combinations of moves) identified 5 common search approaches. The results of this study have implcations for future research on search behaviours, for thedesign of system interfaces and data base structures, and for the training of end users

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Abstract

Attempts to automate classification have focused on mimicking the intellectual processes whereby human classifiers assign entities to mutually exclusive groups that exhibit or more shared characteristics. A more viable approach might be to construct an adaptive retrieval system that produces groupings of related entities by generating dynamic categories based on document content and on the system's emergent structure as it adapts to modifications in the database and to observed patterns of access. Presents a theoretical model for adaptive information networks using relevance feedback and genetic algorithms to generate emergent structure

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Abstract

In information science, classification systems are conventionally viewed as tools for representing knowledge in the universe of ideas, the human mind, or one or more sets of documents. In this view, developing and maintaining relationships and structures in classification schemes must primarily consider two abstract ingredients: i) a set of concepts for one or more domains; and ii) a (set of) unambiguous structure(s) to articulate the relationships that persist between the various concepts that comprise the classificatory structure. We contend that design decisions pertaining to the structure of a classification system consist of far more than simply creating links between the elements in a particular set of concepts. Ultimately, a simplistic tool view of classifications implies that the construction is little more than a technical task in a very narrow sense: that classificatory concepts are viewed as standard representations of what are assumed to be the central and/or important topics in the knowledge domain(s), and that there is i) an unambiguous Platonic ideal or universal consensus that determines how the links will be generated within a classificatory structure; or, conversely, ii) that there are no general structures and relationships available at all, but that only diverse individual knowledge structures exist, which cannot be reconciled into a general organization of knowledge