Search (69 results, page 1 of 4)

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INDEX

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Date

4. 2.2015 9:22:39

Footnote

Vgl.: http://publiscologne.fh-koeln.de/frontdoor/index/index/id/334/docId/334.

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Science Citation Index

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Footnote

[Magisterarbeit zur Informationswissenschaft]; enthält neben einer theoretischen Einführung eine ausführliche Beschreibung des Systems INDEX 3.1

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INDEX

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INDEX

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Abstract

While classifications are heavily used to categorize web content, the evolution of the web foresees a more formal structure - ontology - which can serve this purpose. Ontologies are core artifacts of the Semantic Web which enable machines to use inference rules to conduct automated reasoning on data. Lightweight ontologies bridge the gap between classifications and ontologies. A lightweight ontology (LO) is an ontology representing a backbone taxonomy where the concept of the child node is more specific than the concept of the parent node. Formal lightweight ontologies can be generated from their informal ones. The key applications of formal lightweight ontologies are document classification, semantic search, and data integration. However, these applications suffer from the following problems: the disambiguation accuracy of the state of the art NLP tools used in generating formal lightweight ontologies from their informal ones; the lack of background knowledge needed for the formal lightweight ontologies; and the limitation of ontology reuse. In this dissertation, we propose a novel solution to these problems in formal lightweight ontologies; namely, faceted lightweight ontology (FLO). FLO is a lightweight ontology in which terms, present in each node label, and their concepts, are available in the background knowledge (BK), which is organized as a set of facets. A facet can be defined as a distinctive property of the groups of concepts that can help in differentiating one group from another. Background knowledge can be defined as a subset of a knowledge base, such as WordNet, and often represents a specific domain.

Content

PhD Dissertation at International Doctorate School in Information and Communication Technology. Vgl.: https%3A%2F%2Fcore.ac.uk%2Fdownload%2Fpdf%2F150083013.pdf&usg=AOvVaw2n-qisNagpyT0lli_6QbAQ.

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Content

Vgl.: http%3A%2F%2Fcreativechoice.org%2Fdoc%2FHansJonas.pdf&usg=AOvVaw1TM3teaYKgABL5H9yoIifA&opi=89978449.

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Content

Inhalt: 1. Aufgabe - 2. Ermittlung von Mehrwortgruppen - 2.1 Definition - 3. Kennzeichnung der Mehrwortgruppen - 4. Grundformen - 5. Term- und Dokumenthäufigkeit --- Termgewichtung - 6. Steuerungsinstrument Schwellenwert - 7. Invertierter Index. Vgl. unter: http://www.grin.com/de/e-book/104966/automatische-indexierung.

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Content

Vgl.: http://publiscologne.th-koeln.de/frontdoor/index/index/docId/234

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Abstract

Indexing plays a vital role in Information Retrieval. With the availability of huge volume of information, it has become necessary to index the information in such a way to make easier for the end users to find the information they want efficiently and accurately. Keyword-based indexing uses words as indexing terms. It is not capable of capturing the implicit relation among terms or the semantics of the words in the document. To eliminate this limitation, ontology-based indexing came into existence, which allows semantic based indexing to solve complex and indirect user queries. Ontologies are used for document indexing which allows semantic based information retrieval. Existing ontologies or the ones constructed from scratch are used presently for indexing. Constructing ontologies from scratch is a labor-intensive task and requires extensive domain knowledge whereas use of an existing ontology may leave some important concepts in documents un-annotated. Using multiple ontologies can overcome the problem of missing out concepts to a great extent, but it is difficult to manage (changes in ontologies over time by their developers) multiple ontologies and ontology heterogeneity also arises due to ontologies constructed by different ontology developers. One possible solution to managing multiple ontologies and build from scratch is to use modular ontologies for indexing.

Date

20. 1.2015 18:30:22

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Theme

Preserved Context Index System (PRECIS)

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Content

Masterarbeit an der Hochschule Hannover, Fakultät III - Medien, Information und Design. Trägerin des VFI-Förderpreises 2015, Vgl.: urn:nbn:de:bsz:960-opus4-5280. http://serwiss.bib.hs-hannover.de/frontdoor/index/index/docId/528. Vgl. auch: Knoll, A. (geb. Lamparter): Kompetenzprofil von Information Professionals in Unternehmen. In: Young information professionals. 1(2016) S.1-11.

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Abstract

Nach der Veröffentlichung einer deutschen Übersetzung der Dewey Decimal Classification 22 im Oktober 2005 und ihrer Nutzung zur Inhaltserschließung in der Deutschen Nationalbibliographie seit Januar 2006 stellt sich aus Sicht der deutschen kunsthistorischen Spezialbibliotheken die Frage nach einer möglichen Verwendung der DDC und ihrer generellen Eignung zur Inhalterschließung kunsthistorischer Publikationen. Diese Frage wird vor dem Hintergrund der bestehenden bibliothekarischen Strukturen für die Kunstgeschichte sowie mit Blick auf die inhaltlichen Besonderheiten, die Forschungsmethodik und die publizistischen Traditionen dieses Faches erörtert.

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Abstract

Unser Projekt soll eine Kreuzkonkordanz zwischen den Universalklassifikationen wie der "Regensburger Verbundsklassifikation (RVK)" und der "Basisklassifikation (BK)" sowie den Fachklassifikationen "Mathematics Subject Classification (MSC2010)" und "Physics and Astronomy Classification Scheme (PACS2010)" in den Fachgebieten Mathematik und Physik herstellen. Fazit: "Die klassifikatorische Übereinstmmung zwischen Regensburger Verbundklassifikation und Physics and Astronomy Classification Scheme war in einzelnen Fachbereichen (z. B. Kernphysik) recht gut. Doch andere Fachbereiche (z.B. Polymerphysik, Mineralogie) stimmten sehr wenig überein. Insgesamt konnten wir 890 einfache Verbindungen erstellen. Mehrfachverbindungen wurden aus technischen Gründen nicht mitgezählt. Das Projekt war insgesamt sehr umfangreich, daher konnte es im Rahmen der zwanzig Projekttage nicht erschöpfend behandelt werden. Eine Weiterentwicklung, insbesondere hinsichtlich des kollektiven Zuganges in Form eines Webformulars und der automatischen Klassifizierung erscheint jedoch sinnvoll."

Pages

22 S

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Content

Vgl.: https://publiscologne.th-koeln.de/frontdoor/index/index/searchtype/authorsearch/author/Julia+Walz/docId/1169/start/0/rows/10.

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Content

Bachelorarbeit, Hannover: Hochschule Hannover; Fakultät III: Medien, Information und Design, im Studiengang Informationsmanagement, 2015. Vgl.: http://serwiss.bib.hs-hannover.de/frontdoor/index/index/docId/673.

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Abstract

In this thesis we propose three new word association measures for multi-word term extraction. We combine these association measures with LocalMaxs algorithm in our extraction model and compare the results of different multi-word term extraction methods. Our approach is language and domain independent and requires no training data. It can be applied to such tasks as text summarization, information retrieval, and document classification. We further explore the potential of using multi-word terms as an effective representation for general web-page summarization. We extract multi-word terms from human written summaries in a large collection of web-pages, and generate the summaries by aligning document words with these multi-word terms. Our system applies machine translation technology to learn the aligning process from a training set and focuses on selecting high quality multi-word terms from human written summaries to generate suitable results for web-page summarization.

Date

10. 1.2013 19:22:47

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Footnote

Vgl. unter: https://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=2&cad=rja&uact=8&ved=2ahUKEwizweHljdbcAhVS16QKHXcFD9QQFjABegQICRAB&url=https%3A%2F%2Fwww.researchgate.net%2Fpublication%2F271200105_Die_Autonomie_des_Menschen_und_der_Maschine_-_gegenwartige_Definitionen_von_Autonomie_zwischen_philosophischem_Hintergrund_und_technologischer_Umsetzbarkeit_Redigierte_Version_der_Magisterarbeit_Karls&usg=AOvVaw06orrdJmFF2xbCCp_hL26q.

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Vgl. auch: New automatic interpreter for complex UDC numbers. Unter: <https%3A%2F%2Fudcc.org%2Ffiles%2FAttilaPiros_EC_36-37_2014-2015.pdf&usg=AOvVaw3kc9CwDDCWP7aArpfjrs5b>

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Master thesis Master of Science (Library and Information Studies) (MSc), Universität Wien. Advisor: Christoph Steiner. Vgl.: https://www.researchgate.net/publication/371680244_Vergabe_von_DDC-Sachgruppen_mittels_eines_Schlagwort-Thesaurus. DOI: 10.25365/thesis.70030. Vgl. dazu die Präsentation unter: https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=web&cd=&ved=0CAIQw7AJahcKEwjwoZzzytz_AhUAAAAAHQAAAAAQAg&url=https%3A%2F%2Fwiki.dnb.de%2Fdownload%2Fattachments%2F252121510%2FDA3%2520Workshop-Gabler.pdf%3Fversion%3D1%26modificationDate%3D1671093170000%26api%3Dv2&psig=AOvVaw0szwENK1or3HevgvIDOfjx&ust=1687719410889597&opi=89978449.