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  • × year_i:[2010 TO 2020}
  1. Verwer, K.: Freiheit und Verantwortung bei Hans Jonas (2011) 0.13 
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    Content
    Vgl.: http%3A%2F%2Fcreativechoice.org%2Fdoc%2FHansJonas.pdf&usg=AOvVaw1TM3teaYKgABL5H9yoIifA&opi=89978449.
  2. Gödert, W.; Lepsky, K.: Informationelle Kompetenz : ein humanistischer Entwurf (2019) 0.09 
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    Classification
    OKH (FH K)
    Footnote
    Rez. in: Philosophisch-ethische Rezensionen vom 09.11.2019 (Jürgen Czogalla), Unter: https://philosophisch-ethische-rezensionen.de/rezension/Goedert1.html. In: B.I.T. online 23(2020) H.3, S.345-347 (W. Sühl-Strohmenger) [Unter: https%3A%2F%2Fwww.b-i-t-online.de%2Fheft%2F2020-03-rezensionen.pdf&usg=AOvVaw0iY3f_zNcvEjeZ6inHVnOK]. In: Open Password Nr. 805 vom 14.08.2020 (H.-C. Hobohm) [Unter: https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzE0MywiOGI3NjZkZmNkZjQ1IiwwLDAsMTMxLDFd].
    GHBS
    OKH (FH K)
  3. Deisseroth, K.: Lichtschalter im Gehirn (2011) 0.08 
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    Source
    Spektrum der Wissenschaft. 2011, H.2, S.22-29
    Type
    a
  4. Ceynowa, K.: Research Library Reloaded? : Überlegungen zur Zukunft der geisteswissenschaftlichen Forschungsbibliothek (2018) 0.08 
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    Date
    1. 2.2019 12:50:22
    Type
    a
  5. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.06 
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    Abstract
    On a scientific concept hierarchy, a parent concept may have a few attributes, each of which has multiple values being a group of child concepts. We call these attributes facets: classification has a few facets such as application (e.g., face recognition), model (e.g., svm, knn), and metric (e.g., precision). In this work, we aim at building faceted concept hierarchies from scientific literature. Hierarchy construction methods heavily rely on hypernym detection, however, the faceted relations are parent-to-child links but the hypernym relation is a multi-hop, i.e., ancestor-to-descendent link with a specific facet "type-of". We use information extraction techniques to find synonyms, sibling concepts, and ancestor-descendent relations from a data science corpus. And we propose a hierarchy growth algorithm to infer the parent-child links from the three types of relationships. It resolves conflicts by maintaining the acyclic structure of a hierarchy.
    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
    Type
    a
  6. Suchenwirth, L.: Sacherschliessung in Zeiten von Corona : neue Herausforderungen und Chancen (2019) 0.06 
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    Footnote
    https%3A%2F%2Fjournals.univie.ac.at%2Findex.php%2Fvoebm%2Farticle%2Fdownload%2F5332%2F5271%2F&usg=AOvVaw2yQdFGHlmOwVls7ANCpTii.
    Location
    A
    Type
    a
  7. Zhu, W.Z.; Allen, R.B.: Document clustering using the LSI subspace signature model (2013) 0.06 
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    Abstract
    We describe the latent semantic indexing subspace signature model (LSISSM) for semantic content representation of unstructured text. Grounded on singular value decomposition, the model represents terms and documents by the distribution signatures of their statistical contribution across the top-ranking latent concept dimensions. LSISSM matches term signatures with document signatures according to their mapping coherence between latent semantic indexing (LSI) term subspace and LSI document subspace. LSISSM does feature reduction and finds a low-rank approximation of scalable and sparse term-document matrices. Experiments demonstrate that this approach significantly improves the performance of major clustering algorithms such as standard K-means and self-organizing maps compared with the vector space model and the traditional LSI model. The unique contribution ranking mechanism in LSISSM also improves the initialization of standard K-means compared with random seeding procedure, which sometimes causes low efficiency and effectiveness of clustering. A two-stage initialization strategy based on LSISSM significantly reduces the running time of standard K-means procedures.
    Date
    23. 3.2013 13:22:36
    Type
    a
  8. Hamm, S.; Schneider, K.: Automatische Erschließung von Universitätsdissertationen (2015) 0.05 
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    Source
    Dialog mit Bibliotheken. 27(2015) H.1, S.18-22
    Type
    a
  9. Köttke, K.: Kansste getrost vergessen : Wer sich auf digitale Informationssysteme verlässt, setzt kognitive Fähigkeiten frei (2019) 0.05 
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    Date
    13. 2.2019 9:22:14
    Type
    a
  10. Snow, K.; Hoffman, G.L.: What makes an effective cataloging course? : a study of the factors that promote learning (2015) 0.05 
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    Abstract
    This paper presents the results of a research study, a survey of library and information science master's degree holders who have taken a beginning cataloging course, to identify the elements of a beginning cataloging course that help students to learn cataloging concepts and skills. The results suggest that cataloging practice (the hands-on creation of bibliographic records or catalog cards), the effectiveness of the instructor, a balance of theory and practice, and placing cataloging in a real-world context contribute to effective learning. However, more research is needed to determine how, and to what the extent, each element should be incorporated into beginning cataloging courses.
    Date
    10. 9.2000 17:38:22
    Type
    a
  11. Zanibbi, R.; Yuan, B.: Keyword and image-based retrieval for mathematical expressions (2011) 0.05 
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    Abstract
    Two new methods for retrieving mathematical expressions using conventional keyword search and expression images are presented. An expression-level TF-IDF (term frequency-inverse document frequency) approach is used for keyword search, where queries and indexed expressions are represented by keywords taken from LATEX strings. TF-IDF is computed at the level of individual expressions rather than documents to increase the precision of matching. The second retrieval technique is a form of Content-Base Image Retrieval (CBIR). Expressions are segmented into connected components, and then components in the query expression and each expression in the collection are matched using contour and density features, aspect ratios, and relative positions. In an experiment using ten randomly sampled queries from a corpus of over 22,000 expressions, precision-at-k (k= 20) for the keyword-based approach was higher (keyword: µ= 84.0,s= 19.0, image-based:µ= 32.0,s= 30.7), but for a few of the queries better results were obtained using a combination of the two techniques.
    Date
    22. 2.2017 12:53:49
    Type
    a
  12. Farazi, M.: Faceted lightweight ontologies : a formalization and some experiments (2010) 0.05 
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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.
  13. Gödert, W.; Hubrich, J.; Nagelschmidt, M.: Semantic knowledge representation for information retrieval (2014) 0.05 
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    Abstract
    This book covers the basics of semantic web technologies and indexing languages, and describes their contribution to improve languages as a tool for subject queries and knowledge exploration. The book is relevant to information scientists, knowledge workers and indexers. It provides a suitable combination of theoretical foundations and practical applications.
    Classification
    BCA (FH K)
    Date
    23. 7.2017 13:49:22
    GHBS
    BCA (FH K)
  14. Piros, A.: Az ETO-jelzetek automatikus interpretálásának és elemzésének kérdései (2018) 0.05 
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    Abstract
    Converting UDC numbers manually to a complex format such as the one mentioned above is an unrealistic expectation; supporting building these representations, as far as possible automatically, is a well-founded requirement. An additional advantage of this approach is that the existing records could also be processed and converted. In my dissertation I would like to prove also that it is possible to design and implement an algorithm that is able to convert pre-coordinated UDC numbers into the introduced format by identifying all their elements and revealing their whole syntactic structure as well. In my dissertation I will discuss a feasible way of building a UDC-specific XML schema for describing the most detailed and complicated UDC numbers (containing not only the common auxiliary signs and numbers, but also the different types of special auxiliaries). The schema definition is available online at: http://piros.udc-interpreter.hu#xsd. The primary goal of my research is to prove that it is possible to support building, retrieving, and analyzing UDC numbers without compromises, by taking the whole syntactic richness of the scheme by storing the UDC numbers reserving the meaning of pre-coordination. The research has also included the implementation of a software that parses UDC classmarks attended to prove that such solution can be applied automatically without any additional effort or even retrospectively on existing collections.
    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>
  15. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.05 
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    Content
    One of a series of three publications influenced by the travelling exhibit Places & Spaces: Mapping Science, curated by the Cyberinfrastructure for Network Science Center at Indiana University. - Additional materials can be found at http://http://scimaps.org/atlas2. Erweitert durch: Börner, Katy. Atlas of Science: Visualizing What We Know.
    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
  16. Deokattey, S.; Sharma, S.B.K.; Kumar, G.R.; Bhanumurthy, K.: Knowledge organization research : an overview (2015) 0.05 
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    Abstract
    The object of this literature review is to provide a historical perspective of R and D work in the area of Knowledge Organization (KO). This overview/summarization will provide information on major areas of KO. Journal articles published in core areas of KO: (Classification, Indexing, Thesauri and Taxonomies, Internet and Subject approach to information in the electronic era and Ontologies will be predominantly covered in this literature review. Coverage in this overview may not be completely exhaustive, but it succinctly showcases major developments in the area of KO. This review is a good source of additional reading material on KO apart from prescribed reading material on KO
    Date
    22. 6.2015 16:13:38
  17. Hjoerland, B.: Theories of knowledge organization - theories of knowledge (2017) 0.05 
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    Pages
    S.22-36
    Source
    Theorie, Semantik und Organisation von Wissen: Proceedings der 13. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und dem 13. Internationalen Symposium der Informationswissenschaft der Higher Education Association for Information Science (HI) Potsdam (19.-20.03.2013): 'Theory, Information and Organization of Knowledge' / Proceedings der 14. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und Natural Language & Information Systems (NLDB) Passau (16.06.2015): 'Lexical Resources for Knowledge Organization' / Proceedings des Workshops der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) auf der SEMANTICS Leipzig (1.09.2014): 'Knowledge Organization and Semantic Web' / Proceedings des Workshops der Polnischen und Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) Cottbus (29.-30.09.2011): 'Economics of Knowledge Production and Organization'. Hrsg. von W. Babik, H.P. Ohly u. K. Weber
    Type
    a
  18. Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014) 0.05 
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    Source
    http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja
  19. Golub, K.; Tudhope, D.; Zeng, M.L.; Zumer, M.: Terminology registries for knowledge organization systems : functionality, use, and attributes (2014) 0.04 
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    Abstract
    Terminology registries (TRs) are a crucial element of the infrastructure required for resource discovery services, digital libraries, Linked Data, and semantic interoperability generally. They can make the content of knowledge organization systems (KOS) available both for human and machine access. The paper describes the attributes and functionality for a TR, based on a review of published literature, existing TRs, and a survey of experts. A domain model based on user tasks is constructed and a set of core metadata elements for use in TRs is proposed. Ideally, the TR should allow searching as well as browsing for a KOS, matching a user's search while also providing information about existing terminology services, accessible to both humans and machines. The issues surrounding metadata for KOS are also discussed, together with the rationale for different aspects and the importance of a core set of KOS metadata for future machine-based access; a possible core set of metadata elements is proposed. This is dealt with in terms of practical experience and in relation to the Dublin Core Application Profile.
    Date
    22. 8.2014 17:12:54
    Type
    a
  20. Petric, K.; Petric, T.; Krisper, M.; Rajkovic, V.: User profiling on a pilot digital library with the final result of a new adaptive knowledge management solution (2011) 0.04 
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    Abstract
    In this article, several procedures (e.g., measurements, information retrieval analyses, power law, association rules, hierarchical clustering) are introduced which were made on a pilot digital library. Information retrievals of web users from 01/01/2003 to 01/01/2006 on the internal search engine of the pilot digital library have been analyzed. With the power law method of data processing, a constant information retrieval pattern has been established, stable over a longer period of time. After this, the data have been analyzed. On the basis of the accomplished measurements and analyses, a series of mental models of web users for global (educational) purposes have been developed (e.g., the metamodel of thought hierarchy of web users, the segmentation model of web users), and the users were profiled in four different groups (adventurers, observers, applicable, and know-alls). The article concludes with the construction of a new knowledge management solution called multidimensional rank thesaurus.
    Date
    13. 7.2011 14:47:22
    Type
    a

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