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  1. Dobrev, P.; Kalaydjiev, O.; Angelova, G.: From conceptual structures to semantic interoperability of content (2007) 0.07 
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    Series
    Lecture notes in computer science: Lecture notes in artificial intelligence ; 4604
    Source
    Conceptual structures: knowledge architectures for smart applications: 15th International Conference on Conceptual Structures, ICCS 2007, Sheffield, UK, July 22 - 27, 2007 ; proceedings. Eds.: U. Priss u.a
  2. Gendt, M. van; Isaac, I.; Meij, L. van der; Schlobach, S.: Semantic Web techniques for multiple views on heterogeneous collections : a case study (2006) 0.07 
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    Series
    Lecture notes in computer science; vol.4172
    Source
    Research and advanced technology for digital libraries : 10th European conference, proceedings / ECDL 2006, Alicante, Spain, September 17 - 22, 2006
  3. 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.
  4. Developments in applied artificial intelligence : proceedings / 16th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2003, Loughborough, UK, June 23 - 26, 2003 (2003) 0.03 
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    Series
    Lecture notes in computer science ; Vol. 2718 : Lecture notes in artificial intelligence
  5. Reasoning Web : Semantic Interoperability on the Web, 13th International Summer School 2017, London, UK, July 7-11, 2017, Tutorial Lectures (2017) 0.03 
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    Abstract
    This volume contains the lecture notes of the 13th Reasoning Web Summer School, RW 2017, held in London, UK, in July 2017. In 2017, the theme of the school was "Semantic Interoperability on the Web", which encompasses subjects such as data integration, open data management, reasoning over linked data, database to ontology mapping, query answering over ontologies, hybrid reasoning with rules and ontologies, and ontology-based dynamic systems. The papers of this volume focus on these topics and also address foundational reasoning techniques used in answer set programming and ontologies.
    Series
    Lecture Notes in Computer Scienc;10370 )(Information Systems and Applications, incl. Internet/Web, and HCI
  6. Green, R.; Panzer, M.: ¬The ontological character of classes in the Dewey Decimal Classification 0.03 
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    Abstract
    Classes in the Dewey Decimal Classification (DDC) system function as neighborhoods around focal topics in captions and notes. Topical neighborhoods are generated through specialization and instantiation, complex topic synthesis, index terms and mapped headings, hierarchical force, rules for choosing between numbers, development of the DDC over time, and use of the system in classifying resources. Implications of representation using a formal knowledge representation language are explored.
  7. Assem, M. van; Menken, M.R.; Schreiber, G.; Wielemaker, J.; Wielinga, B.: ¬A method for converting thesauri to RDF/OWL (2004) 0.03 
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    Series
    Lecture notes in computer science; no.3298
  8. Lukasiewicz, T.: Uncertainty reasoning for the Semantic Web (2017) 0.03 
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    Lecture Notes in Computer Scienc;10370) (Information Systems and Applications, incl. Internet/Web, and HCI
  9. 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.
  10. 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.
  11. Widhalm, R.; Mueck, T.A.: Merging topics in well-formed XML topic maps (2003) 0.02 
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    Series
    Lecture notes in computer science; vol. 2870
  12. Bloehdorn, S.; Cimiano, P.; Duke, A.; Haase, P.; Heizmann, J.; Thurlow, I.; Völker, J.: Ontology-based question answering for digital libraries (2007) 0.02 
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    Lecture notes in computer science ; vol. 4675
  13. Drexel, G.: Knowledge engineering for intelligent information retrieval (2001) 0.02 
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    Lecture notes in computer science; vol.2004
  14. Halpin, H.; Hayes, P.J.; McCusker, J.P.; McGuinness, D.L.; Thompson, H.S.: When owl:sameAs isn't the same : an analysis of identity in linked data (2010) 0.02 
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    Lecture notes in computer science; 6496
  15. Vallet, D.; Fernández, M.; Castells, P.: ¬An ontology-based information retrieval model (2005) 0.02 
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    Lecture Notes in Computer Science ; 3532
  16. SKOS Simple Knowledge Organization System Primer (2009) 0.02 
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    Abstract
    SKOS (Simple Knowledge Organisation System) provides a model for expressing the basic structure and content of concept schemes such as thesauri, classification schemes, subject heading lists, taxonomies, folksonomies, and other types of controlled vocabulary. As an application of the Resource Description Framework (RDF) SKOS allows concepts to be documented, linked and merged with other data, while still being composed, integrated and published on the World Wide Web. This document is an implementors guide for those who would like to represent their concept scheme using SKOS. In basic SKOS, conceptual resources (concepts) can be identified using URIs, labelled with strings in one or more natural languages, documented with various types of notes, semantically related to each other in informal hierarchies and association networks, and aggregated into distinct concept schemes. In advanced SKOS, conceptual resources can be mapped to conceptual resources in other schemes and grouped into labelled or ordered collections. Concept labels can also be related to each other. Finally, the SKOS vocabulary itself can be extended to suit the needs of particular communities of practice.
  17. ¬The Semantic Web : research and applications ; second European Semantic WebConference, ESWC 2005, Heraklion, Crete, Greece, May 29 - June 1, 2005 ; proceedings (2005) 0.02 
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    Lecture Notes in Computer Science ; 3532
  18. Tzitzikas, Y.; Spyratos, N.; Constantopoulos, P.; Analyti, A.: Extended faceted ontologies (2002) 0.02 
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    Lecture notes in computer science; vol. 2348
  19. Frisch, A.M.; Allen, J.F.: Knowledge retrieval as limited inference (1982) 0.02 
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    Lecture notes in computer science; vol 138
  20. ISO 25964 Thesauri and interoperability with other vocabularies (2008) 0.02 
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    Abstract
    T.2: The ability to identify and locate relevant information among vast collections and other resources is a major and pressing challenge today. Several different types of vocabulary are in use for this purpose. Some of the most widely used vocabularies were designed a hundred years ago and have been evolving steadily. A different generation of vocabularies is now emerging, designed to exploit the electronic media more effectively. A good understanding of the previous generation is still essential for effective access to collections indexed with them. An important object of ISO 25964 as a whole is to support data exchange and other forms of interoperability in circumstances in which more than one structured vocabulary is applied within one retrieval system or network. Sometimes one vocabulary has to be mapped to another, and it is important to understand both the potential and the limitations of such mappings. In other systems, a thesaurus is mapped to a classification scheme, or an ontology to a thesaurus. Comprehensive interoperability needs to cover the whole range of vocabulary types, whether young or old. Concepts in different vocabularies are related only in that they have the same or similar meaning. However, the meaning can be found in a number of different aspects within each particular type of structured vocabulary: - within terms or captions selected in different languages; - in the notation assigned indicating a place within a larger hierarchy; - in the definition, scope notes, history notes and other notes that explain the significance of that concept; and - in explicit relationships to other concepts or entities within the same vocabulary. In order to create mappings from one structured vocabulary to another it is first necessary to understand, within the context of each different type of structured vocabulary, the significance and relative importance of each of the different elements in defining the meaning of that particular concept. ISO 25964-1 describes the key characteristics of thesauri along with additional advice on best practice. ISO 25964-2 focuses on other types of vocabulary and does not attempt to cover all aspects of good practice. It concentrates on those aspects which need to be understood if one of the vocabularies is to work effectively alongside one or more of the others. Recognizing that a new standard cannot be applied to some existing vocabularies, this part of ISO 25964 provides informative description alongside the recommendations, the aim of which is to enable users and system developers to interpret and implement the existing vocabularies effectively. The remainder of ISO 25964-2 deals with the principles and practicalities of establishing mappings between vocabularies.

Authors

Years

Languages

  • e 70
  • d 13

Types

  • a 61
  • el 20
  • m 7
  • s 5
  • x 5
  • n 3
  • r 1
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