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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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Abstract

We report data fusion experiments carried out on the four best-performing retrieval models from TREC 5. Three were conceptually/algorithmically very different from one another; one was algorithmically similar to one of the former. The objective of the test was to observe the performance of the 11 logical data fusion combinations compared to the performance of the four individual models and their intermediate fusions when following the principle of polyrepresentation. This principle is based on cognitive IR perspective (Ingwersen & Järvelin, 2005) and implies that each retrieval model is regarded as a representation of a unique interpretation of information retrieval (IR). It predicts that only fusions of very different, but equally good, IR models may outperform each constituent as well as their intermediate fusions. Two kinds of experiments were carried out. One tested restricted fusions, which entails that only the inner disjoint overlap documents between fused models are ranked. The second set of experiments was based on traditional data fusion methods. The experiments involved the 30 TREC 5 topics that contain more than 44 relevant documents. In all tests, the Borda and CombSUM scoring methods were used. Performance was measured by precision and recall, with document cutoff values (DCVs) at 100 and 15 documents, respectively. Results show that restricted fusions made of two, three, or four cognitively/algorithmically very different retrieval models perform significantly better than do the individual models at DCV100. At DCV15, however, the results of polyrepresentative fusion were less predictable. The traditional fusion method based on polyrepresentation principles demonstrates a clear picture of performance at both DCV levels and verifies the polyrepresentation predictions for data fusion in IR. Data fusion improves retrieval performance over their constituent IR models only if the models all are quite conceptually/algorithmically dissimilar and equally and well performing, in that order of importance.

Date

22. 3.2009 18:48:28

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Abstract

Because of the increasing presence of scientific publications an the Web, combined with the existing difficulties in easily verifying and retrieving these publications, research an techniques and methods for retrieval of scientific Web publications is called for. In this article, we report an the initial steps taken toward the construction of a test collection of scientific Web publications within the subject domain of plant biology. The steps reported are those of data gathering and data analysis aiming at identifying characteristics of scientific Web publications. The data used in this article were generated based an specifically selected domain topics that are searched for in three publicly accessible search engines (Google, AlITheWeb, and AItaVista). A sample of the retrieved hits was analyzed with regard to how various publication attributes correlated with the scientific quality of the content and whether this information could be employed to harvest, filter, and rank Web publications. The attributes analyzed were inlinks, outlinks, bibliographic references, file format, language, search engine overlap, structural position (according to site structure), and the occurrence of various types of metadata. As could be expected, the ranked output differs between the three search engines. Apparently, this is caused by differences in ranking algorithms rather than the databases themselves. In fact, because scientific Web content in this subject domain receives few inlinks, both AItaVista and AlITheWeb retrieved a higher degree of accessible scientific content than Google. Because of the search engine cutoffs of accessible URLs, the feasibility of using search engine output for Web content analysis is also discussed.

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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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Source

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

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Abstract

This paper provides an over-view of 2, complementary approaches to the design and implementation of information retrieval systems. The first approach focuses on the algorithms and data structures that are needed to maximise the effectiveness and the efficiency of the searches that can be carried out on text databases, while the second adopts a cognitive approach that focuses on the role of the user and of the knowledge sources involved in information retrieval. The paper argues for an holistic view of information retrieval that is capable of encompassing both of these approaches

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Abstract

Reports investigations into the feasibility and reliability of calculating impact factors for web sites, called Web Impact Factors (Web-IF). analyzes a selection of 7 small and medium scale national and 4 large web domains as well as 6 institutional web sites over a series of snapshots taken of the web during a month. Describes the data isolation and calculation methods and discusses the tests. The results thus far demonstrate that Web-IFs are calculable with high confidence for national and sector domains whilst institutional Web-IFs should be approached with caution

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Abstract

Investigates the possibilities and limitations of online citation analysis. The Dialog online processing tools RANK, MAP and TARGET are used to perform analysis of citations to and from isolated sets of documents as well as to carry out diachrone journal analysis. Discusses the implications of this analysis on the journal impact factors of ISI journals. Suggests that by the combined application of RANK and TARGET, a hitherto overlooked possibility of the online analysis of bibliographic coupling and mapping of scientific fields has been revealed

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Source

Information processing and management. 44(2008) no.5, S.1673-1683