Search (3 results, page 1 of 1)

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Abstract

In this paper we analyze a major part of the research output of the Networked Knowledge Organization Systems (NKOS) community in the period 2000 to 2015 from a network analytical perspective. We fo- cus on the paper output presented at the European NKOS workshops in the last 15 years. Our open dataset, the "NKOS bibliography", includes 14 workshop agendas (ECDL 2000-2010, TPDL 2011-2015) and 4 special issues on NKOS (2001, 2004, 2006 and 2015) which cover 171 papers with 218 distinct authors in total. A focus of the analysis is the visualization of co-authorship networks in this interdisciplinary eld. We used standard network analytic measures like degree and betweenness centrality to de- scribe the co-authorship distribution in our NKOS dataset. We can see in our dataset that 15% (with degree=0) of authors had no co-authorship with others and 53% of them had a maximum of 3 cooperations with other authors. 32% had at least 4 co-authors for all of their papers. The NKOS co-author network in the "NKOS bibliography" is a typical co- authorship network with one relatively large component, many smaller components and many isolated co-authorships or triples.

Type

a

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Abstract

Users of web search engines are known to mostly focus on the top ranked results of the search engine result page. While many studies support this well known information seeking pattern only few studies concentrate on the question what users are missing by neglecting lower ranked results. To learn more about the relevance distributions in the so-called long tail we conducted a relevance assessment study with the Million Short long-tail web search engine. While we see a clear difference in the content between the head and the tail of the search engine result list we see no statistical significant differences in the binary relevance judgments and weak significant differences when using graded relevance. The tail contains different but still valuable results. We argue that the long tail can be a rich source for the diversification of web search engine result lists but it needs more evaluation to clearly describe the differences.

Type

a

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Abstract

Im August 2009 wurde SKOS "Simple Knowledge Organization System" als neuer Standard für web-basierte kontrollierte Vokabulare durch das W3C veröffentlicht1. SKOS dient als Datenmodell, um kontrollierte Vokabulare über das Web anzubieten sowie technisch und semantisch interoperabel zu machen. Perspektivisch kann die heterogene Landschaft der Erschließungsvokabulare über SKOS vereinheitlicht und vor allem die Inhalte der klassischen Datenbanken (Bereich Fachinformation) für Anwendungen des Semantic Web, beispielsweise als Linked Open Data2 (LOD), zugänglich und stär-ker miteinander vernetzt werden. Vokabulare im SKOS-Format können dabei eine relevante Funktion einnehmen, indem sie als standardisiertes Brückenvokabular dienen und semantische Verlinkung zwischen erschlossenen, veröffentlichten Daten herstellen. Die folgende Fallstudie skizziert ein Szenario mit drei thematisch verwandten Thesauri, die ins SKOS-Format übertragen und inhaltlich über Crosskonkordanzen aus dem Projekt KoMoHe verbunden werden. Die Mapping Properties von SKOS bieten dazu standardisierte Relationen, die denen der Crosskonkordanzen entsprechen. Die beteiligten Thesauri der Fallstudie sind a) TheSoz (Thesaurus Sozialwissenschaften, GESIS), b) STW (Standard-Thesaurus Wirtschaft, ZBW) und c) IBLK-Thesaurus (SWP).