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  1. Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014) 0.24 
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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
  2. Popper, K.R.: Three worlds : the Tanner lecture on human values. Deliverd at the University of Michigan, April 7, 1978 (1978) 0.19 
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    Source
    https%3A%2F%2Ftannerlectures.utah.edu%2F_documents%2Fa-to-z%2Fp%2Fpopper80.pdf&usg=AOvVaw3f4QRTEH-OEBmoYr2J_c7H
  3. Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999) 0.16 
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    Date
    17. 7.2002 19:22:06
    RSWK
    Entscheidungsunterstützungssystem / Lehrbuch
    Data-warehouse-Konzept / Lehrbuch
    Data mining / Lehrbuch
    Produktionsregelsystem / Lehrbuch
    Series
    Springer-Lehrbuch
    Subject
    Entscheidungsunterstützungssystem / Lehrbuch
    Data-warehouse-Konzept / Lehrbuch
    Data mining / Lehrbuch
    Produktionsregelsystem / Lehrbuch
  4. Shala, E.: ¬Die Autonomie des Menschen und der Maschine : gegenwärtige Definitionen von Autonomie zwischen philosophischem Hintergrund und technologischer Umsetzbarkeit (2014) 0.12 
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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. Guidi, F.; Sacerdoti Coen, C.: ¬A survey on retrieval of mathematical knowledge (2015) 0.06 
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    Abstract
    We present a short survey of the literature on indexing and retrieval of mathematical knowledge, with pointers to 72 papers and tentative taxonomies of both retrieval problems and recurring techniques.
    Date
    22. 2.2017 12:51:57
  6. Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval 0.05 
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    Abstract
    One vision of the Semantic Web is that it will be much like the Web we know today, except that documents will be enriched by annotations in machine understandable markup. These annotations will provide metadata about the documents as well as machine interpretable statements capturing some of the meaning of document content. We discuss how the information retrieval paradigm might be recast in such an environment. We suggest that retrieval can be tightly bound to inference. Doing so makes today's Web search engines useful to Semantic Web inference engines, and causes improvements in either retrieval or inference to lead directly to improvements in the other.
    Date
    12. 2.2011 17:35:22
  7. Zeilmann, K.; Beer, K.; dpa: Tablet statt Lehrbuch : wie die Digitalisierung die Unis verändert (2016) 0.04 
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    http://www.heise.de/newsticker/meldung/Tablet-statt-Lehrbuch-Wie-die-Digitalisierung-die-Unis-veraendert-3082845.html
  8. Reiner, U.: Automatische DDC-Klassifizierung von bibliografischen Titeldatensätzen (2009) 0.04 
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    Date
    22. 8.2009 12:54:24
    Theme
    Klassifikationssysteme im Online-Retrieval
  9. Sojka, P.; Liska, M.: ¬The art of mathematics retrieval (2011) 0.04 
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    Abstract
    The design and architecture of MIaS (Math Indexer and Searcher), a system for mathematics retrieval is presented, and design decisions are discussed. We argue for an approach based on Presentation MathML using a similarity of math subformulae. The system was implemented as a math-aware search engine based on the state-ofthe-art system Apache Lucene. Scalability issues were checked against more than 400,000 arXiv documents with 158 million mathematical formulae. Almost three billion MathML subformulae were indexed using a Solr-compatible Lucene.
    Content
    Vgl.: DocEng2011, September 19-22, 2011, Mountain View, California, USA Copyright 2011 ACM 978-1-4503-0863-2/11/09
    Date
    22. 2.2017 13:00:42
  10. Knorz, G.; Rein, B.: Semantische Suche in einer Hochschulontologie : Ontologie-basiertes Information-Filtering und -Retrieval mit relationalen Datenbanken (2005) 0.03 
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    Date
    11. 2.2011 18:22:25
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  11. Beppler, F.D.; Fonseca, F.T.; Pacheco, R.C.S.: Hermeneus: an architecture for an ontology-enabled information retrieval (2008) 0.03 
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    Abstract
    Ontologies improve IR systems regarding its retrieval and presentation of information, which make the task of finding information more effective, efficient, and interactive. In this paper we argue that ontologies also greatly improve the engineering of such systems. We created a framework that uses ontology to drive the process of engineering an IR system. We developed a prototype that shows how a domain specialist without knowledge in the IR field can build an IR system with interactive components. The resulting system provides support for users not only to find their information needs but also to extend their state of knowledge. This way, our approach to ontology-enabled information retrieval addresses both the engineering aspect described here and also the usability aspect described elsewhere.
    Date
    28.11.2016 12:43:22
  12. Zanibbi, R.; Yuan, B.: Keyword and image-based retrieval for mathematical expressions (2011) 0.03 
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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
  13. Henrich, A.: Information Retrieval : Grundlagen, Modelle und Anwendungen (2008) 0.03 
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    Date
    22. 8.2015 21:23:08
  14. Van Dijck, P.: Introduction to XFML (2003) 0.03 
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    Source
    http://www.xml.com/lpt/a/2003/01/22/xfml.html
    Theme
    Klassifikationssysteme im Online-Retrieval
  15. Priss, U.: Faceted knowledge representation (1999) 0.03 
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    Abstract
    Faceted Knowledge Representation provides a formalism for implementing knowledge systems. The basic notions of faceted knowledge representation are "unit", "relation", "facet" and "interpretation". Units are atomic elements and can be abstract elements or refer to external objects in an application. Relations are sequences or matrices of 0 and 1's (binary matrices). Facets are relational structures that combine units and relations. Each facet represents an aspect or viewpoint of a knowledge system. Interpretations are mappings that can be used to translate between different representations. This paper introduces the basic notions of faceted knowledge representation. The formalism is applied here to an abstract modeling of a faceted thesaurus as used in information retrieval.
    Date
    22. 1.2016 17:30:31
  16. Information retrieval research : Proceedings of the 19th Annual BCS-IRSG Colloquium on IR Research, Aberdeen, Scotland, 8-9 April 1997 (1997) 0.02 
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    LCSH
    Information storage and retrieval systems / Research / Congresses
    Information retrieval / Research / Congresses
    RSWK
    Information retrieval / Kongress / Aberdeen <1997>
    Subject
    Information storage and retrieval systems / Research / Congresses
    Information retrieval / Research / Congresses
    Information retrieval / Kongress / Aberdeen <1997>
  17. Place, E.: Internationale Zusammenarbeit bei Internet Subject Gateways (1999) 0.02 
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    Date
    22. 6.2002 19:35:09
    Theme
    Klassifikationssysteme im Online-Retrieval
  18. Priss, U.: Description logic and faceted knowledge representation (1999) 0.02 
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    Abstract
    The term "facet" was introduced into the field of library classification systems by Ranganathan in the 1930's [Ranganathan, 1962]. A facet is a viewpoint or aspect. In contrast to traditional classification systems, faceted systems are modular in that a domain is analyzed in terms of baseline facets which are then synthesized. In this paper, the term "facet" is used in a broader meaning. Facets can describe different aspects on the same level of abstraction or the same aspect on different levels of abstraction. The notion of facets is related to database views, multicontexts and conceptual scaling in formal concept analysis [Ganter and Wille, 1999], polymorphism in object-oriented design, aspect-oriented programming, views and contexts in description logic and semantic networks. This paper presents a definition of facets in terms of faceted knowledge representation that incorporates the traditional narrower notion of facets and potentially facilitates translation between different knowledge representation formalisms. A goal of this approach is a modular, machine-aided knowledge base design mechanism. A possible application is faceted thesaurus construction for information retrieval and data mining. Reasoning complexity depends on the size of the modules (facets). A more general analysis of complexity will be left for future research.
    Date
    22. 1.2016 17:30:31
  19. Kottmann, N.; Studer, T.: Improving semantic query answering (2006) 0.02 
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    Abstract
    The retrieval problem is one of the main reasoning tasks for knowledge base systems. Given a knowledge base K and a concept C, the retrieval problem consists of finding all individuals a for which K logically entails C(a). We present an approach to answer retrieval queries over (a restriction of) OWL ontologies. Our solution is based on reducing the retrieval problem to a problem of evaluating an SQL query over a database constructed from the original knowledge base. We provide complete answers to retrieval problems. Still, our system performs very well as is shown by a standard benchmark.
  20. Gödert, W.: ¬An ontology-based model for indexing and retrieval (2013) 0.02 
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    Abstract
    Starting from an unsolved problem of information retrieval this paper presents an ontology-based model for indexing and retrieval. The model combines the methods and experiences of cognitive-to-interpret indexing languages with the strengths and possibilities of formal knowledge representation. The core component of the model uses inferences along the paths of typed relations between the entities of a knowledge representation for enabling the determination of hit quantities in the context of retrieval processes. The entities are arranged in aspect-oriented facets to ensure a consistent hierarchical structure. The possible consequences for indexing and retrieval are discussed.

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