Deductive information retrieval based on classifications

Järvelin, Kalervo; Niemi, Timo

doi:10.1002/(sici)1097-4571(199312)44:10<557::aid-asi2>3.0.co;2-m

Cited by 4 publications

(2 citation statements)

References 17 publications

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“…. The main menu for impact factor analysis which are returned as a set [23]. The two sets of article numbers are finally intersected by the operation set_intersection.…”

Section: Generalised Impact Factorsmentioning

confidence: 99%

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A user‐oriented interface for generalised informetric analysis based on applying advanced data modelling techniques

Järvelin

Ingwersen²,

Niemi³

2000

Journal of Documentation

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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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“…. The main menu for impact factor analysis which are returned as a set [23]. The two sets of article numbers are finally intersected by the operation set_intersection.…”

Section: Generalised Impact Factorsmentioning

confidence: 99%

“…references) of article art_5 are denoted by im_successors(art_5, [CITES]) = {art_3, …}. These notations correspond to the operations of our query language for transitive processing [16,23] which will be used below. The query language also has an acyclicity checking tool for the binary relations.…”

Section: Introductionmentioning

confidence: 99%