Search (7 results, page 1 of 1)

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Source

Encyclopedia of library and information science. Vol.56, [=Suppl.19]

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Source

Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates

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Source

International forum on information and documentation. 14(1989), S.17-22

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Abstract

The paper presents the principles underlying the cognitive framework for Information Retrieval (IR). It introduces the concept of polyrepresentation applied simultaneously to the user's cognitive space and the information space of IR systems. The concept seeks to represent the current user's information need, problem state, and domain work task or interest in a structure of causality. Further, it suggests to apply different methods of representation and a variety of IR techniques of 'different cognitive and functional origin' simultaneously to each information object in the information space. The cognitive differences between such representations imply that by applying 'cognitive retrieval overlaps' of information objects, originating from different interpretations of such objects over time and by type, the degree of uncertainty inherent in IR is decreased and the intellectual access possibilities are increased. One consequence of the framework is its capability to elucidate the seemingly dubious assumptions underlying the predominant algorithmic retrieval models, such as, the vector space and probabilistic models

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Abstract

The objective of this paper is to amalgamate theories of text retrieval from various research traditions into a cognitive theory for information retrieval interaction. Set in a cognitive framework, the paper outlines the concept of polyrepresentation applied to both the user's cognitive space and the information space of IR systems. The concept seeks to represent the current user's information need, problem state, and domain work task or interest in a structure of causality. Further, it implies that we should apply different methods of representation and a variety of IR techniques of different cognitive and functional origin simultaneously to each semantic full-text entity in the information space. The cognitive differences imply that by applying cognitive overlaps of information objects, originating from different interprestations of such objects through time and by type, the degree of uncertainty inherent in IR is decreased. ... The lack of consistency among authors, indexers, evaluators or users is of an identical cognitive nature. It is unavoidable, and indeed favourable to IR. In particular, for full-text retrieval, alternative semantic entities, including Salton 'et al.'s' 'passage retrieval', are proposed to replace the traditional document record as the basic retrieval entity. These empirically observed phenomena of inconsistency and of semantic entities and values associated with data interpretation support strongly a cognitive approach to IR and the logical use of olypresentation, cognitive overlaps, and both data fusion and data diffusion

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Abstract

This article presents a novel user-oriented interface for generalised informetric analysis and demonstrates how informetric calculations can easily and declaratively be specified through advanced data modelling techniques. The interface is declarative and at a high level. Therefore it is easy to use, flexible and extensible. It enables end users to perform basic informetric ad hoc calculations easily and often with much less effort than in contemporary online retrieval systems. It also provides several fruitful generalisations of typical informetric measurements like impact factors. These are based on substituting traditional foci of analysis, for instance journals, by other object types, such as authors, organisations or countries. In the interface, bibliographic data are modelled as complex objects (non-first normal form relations) and terminological and citation networks involving transitive relationships are modelled as binary relations for deductive processing. The interface is flexible, because it makes it easy to switch focus between various object types for informetric calculations, e.g. from authors to institutions. Moreover, it is demonstrated that all informetric data can easily be broken down by criteria that foster advanced analysis, e.g. by years or content-bearing attributes. Such modelling allows flexible data aggregation along many dimensions. These salient features emerge from the query interface's general data restructuring and aggregation capabilities combined with transitive processing capabilities. The features are illustrated by means of sample queries and results in the article.

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Date

22. 3.2009 18:48:28