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Abstract

There have been many attempts to evaluate Web spaces an the basis of the information that they provide, their form or functionality, or even the importance given to each of them by the Web itself. The indicators that have been developed for this purpose fall into two groups: those based an the study of a Web space's formal characteristics, and those related to its link structure. In this study we examine most of the webometric indicators that have been proposed in the literature together with others of our own design by applying them to a set of thematically related Web spaces and analyzing the relationships between the different indicators.

Source

Journal of the American Society for Information Science and Technology. 56(2005) no.8, S.779-785

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Abstract

This study proposes a new methodology that allows for the generation of scientograms of major scientific domains, constructed on the basis of cocitation of Institute of Scientific Information categories, and pruned using PathfinderNetwork, with a layout determined by algorithms of the spring-embedder type (Kamada-Kawai), then corroborated structurally by factor analysis. We present the complete scientogram of the world for the Year 2002. It integrates the natural sciences, the social sciences, and arts and humanities. Its basic structure and the essential relationships therein are revealed, allowing us to simultaneously analyze the macrostructure, microstructure, and marrow of worldwide scientific output.

Source

Journal of the American Society for Information Science and Technology. 58(2007) no.14, S.2167-2179

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Abstract

Connectionist models or neural networksare a type of AI technique that is based an small interconnected processing nodes which yield an overall behaviour that is intelligent. They have a very broad utility. In IR, they have been used in filtering information, query expansion, relevance feedback, clustering terms or documents, the topological organization of documents, labeling groups of documents, interface design, reduction of document dimension, the classification of the terms in a brain-storming session, etc. The present work is a fairly exhaustive study and classification of the application of this type of technique to IR. For this purpose, we focus an the main publications in the area of IR and neural networks, as well as an some applications of our own design.

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Abstract

Purpose - To propose a categorization of the different conflation procedures at the two basic approaches, non-linguistic and linguistic techniques, and to justify the application of normalization methods within the framework of linguistic techniques. Design/methodology/approach - Presents a range of term conflation methods, that can be used in information retrieval. The uniterm and multiterm variants can be considered equivalent units for the purposes of automatic indexing. Stemming algorithms, segmentation rules, association measures and clustering techniques are well evaluated non-linguistic methods, and experiments with these techniques show a wide variety of results. Alternatively, the lemmatisation and the use of syntactic pattern-matching, through equivalence relations represented in finite-state transducers (FST), are emerging methods for the recognition and standardization of terms. Findings - The survey attempts to point out the positive and negative effects of the linguistic approach and its potential as a term conflation method. Originality/value - Outlines the importance of FSTs for the normalization of term variants.

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Source

Information processing and management. 39(2003) no.5, S.669-687

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Journal of the American Society for Information Science and Technology. 62(2011) no.6, S.1130-1145

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Journal of the American Society for Information Science and Technology. 64(2013) no.2, S.392-404

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Abstract

We evaluated the different genetic algorithms applied to relevance feedback that are to be found in the literature and which follow the vector space model (the most commonly used model in this type of application). They were compared with a traditional relevance feedback algorithm - the Ide dec-hi method - since this had given the best results in the study of Salton & Buckley (1990) an this subject. The experiment was performed an the Cranfield collection, and the different algorithms were evaluated using the residual collection method (one of the most suitable methods for evaluating relevance feedback techniques). The results varied greatly depending an the fitness function that was used, from no improvement in some of the genetic algorithms, to a more than 127% improvement with one algorithm, surpassing even the traditional Ide dec-hi method. One can therefore conclude that genetic algorithms show great promise as an aid to implementing a truly effective information retrieval system.

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Source

Journal of the American Society for Information Science and technology. 54(2003) no.2, S.152-160

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Journal of the Association for Information Science and Technology. 66(2015) no.5, S.1001-1016

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Journal of the Association for Information Science and Technology. 67(2016) no.1, S.178-190

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Source

Journal of the Association for Information Science and Technology. 67(2016) no.9, S.2194-2211