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  1. 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) 0.04
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  2. Resource Description Framework (RDF) (2004) 0.03
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    Abstract
    The Resource Description Framework (RDF) integrates a variety of applications from library catalogs and world-wide directories to syndication and aggregation of news, software, and content to personal collections of music, photos, and events using XML as an interchange syntax. The RDF specifications provide a lightweight ontology system to support the exchange of knowledge on the Web. The W3C Semantic Web Activity Statement explains W3C's plans for RDF, including the RDF Core WG, Web Ontology and the RDF Interest Group.
  3. Stojanovic, N.: Ontology-based Information Retrieval : methods and tools for cooperative query answering (2005) 0.03
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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.
  4. Xiong, C.: Knowledge based text representations for information retrieval (2016) 0.03
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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.
  5. Mengle, S.S.R.; Goharian, N.: Detecting relationships among categories using text classification (2010) 0.02
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    Abstract
    Discovering relationships among concepts and categories is crucial in various information systems. The authors' objective was to discover such relationships among document categories. Traditionally, such relationships are represented in the form of a concept hierarchy, grouping some categories under the same parent category. Although the nature of hierarchy supports the identification of categories that may share the same parent, not all of these categories have a relationship with each other - other than sharing the same parent. However, some non-sibling relationships exist that although are related to each other are not identified as such. The authors identify and build a relationship network (relationship-net) with categories as the vertices and relationships as the edges of this network. They demonstrate that using a relationship-net, some nonobvious category relationships are detected. Their approach capitalizes on the misclassification information generated during the process of text classification to identify potential relationships among categories and automatically generate relationship-nets. Their results demonstrate a statistically significant improvement over the current approach by up to 73% on 20 News groups 20NG, up to 68% on 17 categories in the Open Directories Project (ODP17), and more than twice on ODP46 and Special Interest Group on Information Retrieval (SIGIR) data sets. Their results also indicate that using misclassification information stemming from passage classification as opposed to document classification statistically significantly improves the results on 20NG (8%), ODP17 (5%), ODP46 (73%), and SIGIR (117%) with respect to F1 measure. By assigning weights to relationships and by performing feature selection, results are further optimized.
  6. Schmitz-Esser, W.: Language of general communication and concept compatibility (1996) 0.02
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    Pages
    S.11-22
  7. Tudhope, D.; Hodge, G.: Terminology registries (2007) 0.02
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    Date
    26.12.2011 13:22:07
  8. Kiryakov, A.; Popov, B.; Terziev, I.; Manov, D.; Ognyanoff, D.: Semantic annotation, indexing, and retrieval (2004) 0.02
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    Abstract
    The Semantic Web realization depends on the availability of a critical mass of metadata for the web content, associated with the respective formal knowledge about the world. We claim that the Semantic Web, at its current stage of development, is in a state of a critical need of metadata generation and usage schemata that are specific, well-defined and easy to understand. This paper introduces our vision for a holistic architecture for semantic annotation, indexing, and retrieval of documents with regard to extensive semantic repositories. A system (called KIM), implementing this concept, is presented in brief and it is used for the purposes of evaluation and demonstration. A particular schema for semantic annotation with respect to real-world entities is proposed. The underlying philosophy is that a practical semantic annotation is impossible without some particular knowledge modelling commitments. Our understanding is that a system for such semantic annotation should be based upon a simple model of real-world entity classes, complemented with extensive instance knowledge. To ensure the efficiency, ease of sharing, and reusability of the metadata, we introduce an upper-level ontology (of about 250 classes and 100 properties), which starts with some basic philosophical distinctions and then goes down to the most common entity types (people, companies, cities, etc.). Thus it encodes many of the domain-independent commonsense concepts and allows straightforward domain-specific extensions. On the basis of the ontology, a large-scale knowledge base of entity descriptions is bootstrapped, and further extended and maintained. Currently, the knowledge bases usually scales between 105 and 106 descriptions. Finally, this paper presents a semantically enhanced information extraction system, which provides automatic semantic annotation with references to classes in the ontology and to instances. The system has been running over a continuously growing document collection (currently about 0.5 million news articles), so it has been under constant testing and evaluation for some time now. On the basis of these semantic annotations, we perform semantic based indexing and retrieval where users can mix traditional information retrieval (IR) queries and ontology-based ones. We argue that such large-scale, fully automatic methods are essential for the transformation of the current largely textual web into a Semantic Web.
  9. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.01
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    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
  10. Synak, M.; Dabrowski, M.; Kruk, S.R.: Semantic Web and ontologies (2009) 0.01
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    Date
    31. 7.2010 16:58:22
  11. OWL Web Ontology Language Test Cases (2004) 0.01
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    Date
    14. 8.2011 13:33:22
  12. Giunchiglia, F.; Villafiorita, A.; Walsh, T.: Theories of abstraction (1997) 0.01
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    Date
    1.10.2018 14:13:22
  13. Jacobs, I.: From chaos, order: W3C standard helps organize knowledge : SKOS Connects Diverse Knowledge Organization Systems to Linked Data (2009) 0.01
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    Abstract
    18 August 2009 -- Today W3C announces a new standard that builds a bridge between the world of knowledge organization systems - including thesauri, classifications, subject headings, taxonomies, and folksonomies - and the linked data community, bringing benefits to both. Libraries, museums, newspapers, government portals, enterprises, social networking applications, and other communities that manage large collections of books, historical artifacts, news reports, business glossaries, blog entries, and other items can now use Simple Knowledge Organization System (SKOS) to leverage the power of linked data. As different communities with expertise and established vocabularies use SKOS to integrate them into the Semantic Web, they increase the value of the information for everyone.
  14. Priss, U.: Faceted information representation (2000) 0.01
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    Date
    22. 1.2016 17:47:06
  15. Deokattey, S.; Neelameghan, A.; Kumar, V.: ¬A method for developing a domain ontology : a case study for a multidisciplinary subject (2010) 0.01
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    Date
    22. 7.2010 19:41:16
  16. Mayfield, J.; Finin, T.: Information retrieval on the Semantic Web : integrating inference and retrieval 0.01
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    Date
    12. 2.2011 17:35:22
  17. Madalli, D.P.; Balaji, B.P.; Sarangi, A.K.: Music domain analysis for building faceted ontological representation (2014) 0.01
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    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  18. Priss, U.: Faceted knowledge representation (1999) 0.01
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    Date
    22. 1.2016 17:30:31
  19. Definition of the CIDOC Conceptual Reference Model (2003) 0.01
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    Date
    6. 8.2010 14:22:28
  20. Gendt, M. van; Isaac, I.; Meij, L. van der; Schlobach, S.: Semantic Web techniques for multiple views on heterogeneous collections : a case study (2006) 0.01
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    Source
    Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006

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