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  1. Verwer, K.: Freiheit und Verantwortung bei Hans Jonas (2011) 0.22
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    Content
    Vgl.: http%3A%2F%2Fcreativechoice.org%2Fdoc%2FHansJonas.pdf&usg=AOvVaw1TM3teaYKgABL5H9yoIifA&opi=89978449.
  2. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.10
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    Content
    Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies. Vgl.: https%3A%2F%2Fwww.cs.cmu.edu%2F~cx%2Fpapers%2Fknowledge_based_text_representation.pdf&usg=AOvVaw0SaTSvhWLTh__Uz_HtOtl3.
  3. Farazi, M.: Faceted lightweight ontologies : a formalization and some experiments (2010) 0.09
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    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.
  4. Shala, E.: ¬Die Autonomie des Menschen und der Maschine : gegenwärtige Definitionen von Autonomie zwischen philosophischem Hintergrund und technologischer Umsetzbarkeit (2014) 0.09
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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.
  5. Piros, A.: Az ETO-jelzetek automatikus interpretálásának és elemzésének kérdései (2018) 0.09
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    Content
    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>
  6. Gabler, S.: Vergabe von DDC-Sachgruppen mittels eines Schlagwort-Thesaurus (2021) 0.09
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    Content
    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.
  7. Huo, W.: Automatic multi-word term extraction and its application to Web-page summarization (2012) 0.09
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    Content
    A Thesis presented to The University of Guelph In partial fulfilment of requirements for the degree of Master of Science in Computer Science. Vgl. Unter: http://www.inf.ufrgs.br%2F~ceramisch%2Fdownload_files%2Fpublications%2F2009%2Fp01.pdf.
    Date
    10. 1.2013 19:22:47
  8. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.07
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    Content
    Vgl.: http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F1627&ei=tAtYUYrBNoHKtQb3l4GYBw&usg=AFQjCNHeaxKkKU3-u54LWxMNYGXaaDLCGw&sig2=8WykXWQoDKjDSdGtAakH2Q&bvm=bv.44442042,d.Yms.
  9. Kiren, T.: ¬A clustering based indexing technique of modularized ontologies for information retrieval (2017) 0.03
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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
  10. Scherer Auberson, K.: Counteracting concept drift in natural language classifiers : proposal for an automated method (2018) 0.01
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    Content
    Diese Publikation entstand im Rahmen einer Thesis zum Master of Science FHO in Business Administration, Major Information and Data Management.
  11. Rohner, M.: Betrachtung der Data Visualization Literacy in der angestrebten Schweizer Informationsgesellschaft (2018) 0.01
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    Content
    Diese Publikation entstand im Rahmen einer Thesis zum Master of Science FHO in Business Administration, Major Information and Data Management.
  12. Martins, S. de Castro: Modelo conceitual de ecossistema semântico de informações corporativas para aplicação em objetos multimídia (2019) 0.01
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    Abstract
    Information management in corporate environments is a growing problem as companies' information assets grow and their need to use them in their operations. Several management models have been practiced with application on the most diverse fronts, practices that integrate the so-called Enterprise Content Management. This study proposes a conceptual model of semantic corporate information ecosystem, based on the Universal Document Model proposed by Dagobert Soergel. It focuses on unstructured information objects, especially multimedia, increasingly used in corporate environments, adding semantics and expanding their recovery potential in the composition and reuse of dynamic documents on demand. The proposed model considers stable elements in the organizational environment, such as actors, processes, business metadata and information objects, as well as some basic infrastructures of the corporate information environment. The main objective is to establish a conceptual model that adds semantic intelligence to information assets, leveraging pre-existing infrastructure in organizations, integrating and relating objects to other objects, actors and business processes. The approach methodology considered the state of the art of Information Organization, Representation and Retrieval, Organizational Content Management and Semantic Web technologies, in the scientific literature, as bases for the establishment of an integrative conceptual model. Therefore, the research will be qualitative and exploratory. The predicted steps of the model are: Environment, Data Type and Source Definition, Data Distillation, Metadata Enrichment, and Storage. As a result, in theoretical terms the extended model allows to process heterogeneous and unstructured data according to the established cut-outs and through the processes listed above, allowing value creation in the composition of dynamic information objects, with semantic aggregations to metadata.
  13. Noy, N.F.: Knowledge representation for intelligent information retrieval in experimental sciences (1997) 0.01
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    Abstract
    More and more information is available on-line every day. The greater the amount of on-line information, the greater the demand for tools that process and disseminate this information. Processing electronic information in the form of text and answering users' queries about that information intelligently is one of the great challenges in natural language processing and information retrieval. The research presented in this talk is centered on the latter of these two tasks: intelligent information retrieval. In order for information to be retrieved, it first needs to be formalized in a database or knowledge base. The ontology for this formalization and assumptions it is based on are crucial to successful intelligent information retrieval. We have concentrated our effort on developing an ontology for representing knowledge in the domains of experimental sciences, molecular biology in particular. We show that existing ontological models cannot be readily applied to represent this domain adequately. For example, the fundamental notion of ontology design that every "real" object is defined as an instance of a category seems incompatible with the universe where objects can change their category as a result of experimental procedures. Another important problem is representing complex structures such as DNA, mixtures, populations of molecules, etc., that are very common in molecular biology. We present extensions that need to be made to an ontology to cover these issues: the representation of transformations that change the structure and/or category of their participants, and the component relations and spatial structures of complex objects. We demonstrate examples of how the proposed representations can be used to improve the quality and completeness of answers to user queries; discuss techniques for evaluating ontologies and show a prototype of an Information Retrieval System that we developed.
  14. Schönauer, S.: Wissensmanagement im Fokus kommunikativer Prozesse (2003) 0.01
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    Abstract
    Fragestellung: "Kann man Wissen wie eine Ressource behandeln und managen?" Diese Frage stellt bzw. sollte den Ausgangspunkt jedes Wissensmanagementkonzeptes darstellen und steht aus diesem Grund im Mittelpunkt dieser Arbeit. Anders formuliert könnte man sagen: "Ist der Begriff Wissensmanagement kontradiktorisch?" Stellen Wissensmanagementkonzepte nur einen neuen Managementtrend dar, der alte, wenig erfolgreiche Konzepte (Business Process Reengeneering, TQM, Lean Management, Kaizen) mit neuen Begriffen auffüllt? Was ist Wissen und welche Faktoren begünstigen die Entstehung und den Austausch von Wissen? Welche Bedeutung hat Kommunikation für die Entstehung von Wissen? Wenn Kommunikation einen entscheidenden Faktor für die Entstehung und den Austausch von Wissen hat, inwiefern können Informations- und Kommunikationstechnologien im Kontext von Wissensmanagement genutzt werden? Das sind die zentralen Fragen, die ich mir am Anfang und im Verlauf dieser Arbeit gestellt habe. Die Fragestellungen basieren auf sozialwissenschaftlichen Überlegungen, anhand derer das ökonomische Konzept Wissensmanagement untersucht wird. Nachdem Wissen ein soziales Konstrukt ist und die Transformation der knowledge-based economy vor allem von den neuen Informations- und Kommunikationstechnologien vorangetrieben und verstärkt wurde, erschien mir die Betrachtung des Managements von Wissen anhand dieser Fragestellungen für zielführend und an der Zeit.
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    Date
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