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  • × subject_ss:"Semantic Web"
  1. Multimedia content and the Semantic Web : methods, standards, and tools (2005) 0.06
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    Classification
    006.7 22
    Date
    7. 3.2007 19:30:22
    DDC
    006.7 22
    Footnote
    Semantic web technologies are explained, and ontology representation is emphasized. There is an excellent summary of the fundamental theory behind applying a knowledge-engineering approach to vision problems. This summary represents the concept of the semantic web and multimedia content analysis. A definition of the fuzzy knowledge representation that can be used for realization in multimedia content applications has been provided, with a comprehensive analysis. The second part of the book introduces the multimedia content analysis approaches and applications. In addition, some examples of methods applicable to multimedia content analysis are presented. Multimedia content analysis is a very diverse field and concerns many other research fields at the same time; this creates strong diversity issues, as everything from low-level features (e.g., colors, DCT coefficients, motion vectors, etc.) up to the very high and semantic level (e.g., Object, Events, Tracks, etc.) are involved. The second part includes topics on structure identification (e.g., shot detection for video sequences), and object-based video indexing. These conventional analysis methods are supplemented by results on semantic multimedia analysis, including three detailed chapters on the development and use of knowledge models for automatic multimedia analysis. Starting from object-based indexing and continuing with machine learning, these three chapters are very logically organized. Because of the diversity of this research field, including several chapters of recent research results is not sufficient to cover the state of the art of multimedia. The editors of the book should write an introductory chapter about multimedia content analysis approaches, basic problems, and technical issues and challenges, and try to survey the state of the art of the field and thus introduce the field to the reader.
    The final part of the book discusses research in multimedia content management systems and the semantic web, and presents examples and applications for semantic multimedia analysis in search and retrieval systems. These chapters describe example systems in which current projects have been implemented, and include extensive results and real demonstrations. For example, real case scenarios such as ECommerce medical applications and Web services have been introduced. Topics in natural language, speech and image processing techniques and their application for multimedia indexing, and content-based retrieval have been elaborated upon with extensive examples and deployment methods. The editors of the book themselves provide the readers with a chapter about their latest research results on knowledge-based multimedia content indexing and retrieval. Some interesting applications for multimedia content and the semantic web are introduced. Applications that have taken advantage of the metadata provided by MPEG7 in order to realize advance-access services for multimedia content have been provided. The applications discussed in the third part of the book provide useful guidance to researchers and practitioners properly planning to implement semantic multimedia analysis techniques in new research and development projects in both academia and industry. A fourth part should be added to this book: performance measurements for integrated approaches of multimedia analysis and the semantic web. Performance of the semantic approach is a very sophisticated issue and requires extensive elaboration and effort. Measuring the semantic search is an ongoing research area; several chapters concerning performance measurement and analysis would be required to adequately cover this area and introduce it to readers."
    Language
    e
  2. Fensel, D.: Ontologies : a silver bullet for knowledge management and electronic commerce (2004) 0.03
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    Classification
    004.67/8 22
    DDC
    004.67/8 22
    Language
    e
  3. Gödert, W.; Hubrich, J.; Nagelschmidt, M.: Semantic knowledge representation for information retrieval (2014) 0.02
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    Date
    23. 7.2017 13:49:22
    Language
    e
  4. Keyser, P. de: Indexing : from thesauri to the Semantic Web (2012) 0.02
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    Date
    24. 8.2016 14:03:22
    Language
    e
  5. Daconta, M.C.; Oberst, L.J.; Smith, K.T.: ¬The Semantic Web : A guide to the future of XML, Web services and knowledge management (2003) 0.02
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    Date
    22. 5.2007 10:37:38
    Language
    e
  6. Stuckenschmidt, H.; Harmelen, F. van: Information sharing on the semantic web (2005) 0.00
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    Classification
    TVU (E)
    GHBS
    TVU (E)
    Language
    e
  7. Suman, A.: From knowledge abstraction to management : using Ranganathan's faceted schema to develop conceptual frameworks for digital libraries (2014) 0.00
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  8. Hitzler, P.; Krötzsch, M.; Rudolph, S.: Foundations of Semantic Web technologies (2010) 0.00
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    Classification
    TVU (E)
    GHBS
    TVU (E)
  9. Fensel, D.: Ontologies : a silver bullet for knowledge management and electronic commerce (2001) 0.00
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  10. Willer, M.; Dunsire, G.: Bibliographic information organization in the Semantic Web (2013) 0.00
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  11. Linked data and user interaction : the road ahead (2015) 0.00
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  12. Chaudhury, S.; Mallik, A.; Ghosh, H.: Multimedia ontology : representation and applications (2016) 0.00
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  13. Semantic applications (2018) 0.00
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  14. Semantic digital libraries (2009) 0.00
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  15. Manning, C.D.; Raghavan, P.; Schütze, H.: Introduction to information retrieval (2008) 0.00
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  16. Sakr, S.; Wylot, M.; Mutharaju, R.; Le-Phuoc, D.; Fundulaki, I.: Linked data : storing, querying, and reasoning (2018) 0.00
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  17. Antoniou, G.; Harmelen, F. van: ¬A semantic Web primer (2004) 0.00
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    Footnote
    The next chapter introduces resource description framework (RDF) and RDF schema (RDFS). Unlike XML, RDF provides a foundation for expressing the semantics of dada: it is a standard dada model for machine-processable semantics. Resource description framework schema offers a number of modeling primitives for organizing RDF vocabularies in typed hierarchies. In addition to RDF and RDFS, a query language for RDF, i.e. RQL. is introduced. This chapter and the next chapter are two of the most important chapters in the book. Chapter 4 presents another language called Web Ontology Language (OWL). Because RDFS is quite primitive as a modeling language for the Web, more powerful languages are needed. A richer language. DAML+OIL, is thus proposed as a joint endeavor of the United States and Europe. OWL takes DAML+OIL as the starting point, and aims to be the standardized and broadly accepted ontology language. At the beginning of the chapter, the nontrivial relation with RDF/RDFS is discussed. Then the authors describe the various language elements of OWL in some detail. Moreover, Appendix A contains an abstract OWL syntax. which compresses OWL and makes OWL much easier to read. Chapter 5 covers both monotonic and nonmonotonic rules. Whereas the previous chapter's mainly concentrate on specializations of knowledge representation, this chapter depicts the foundation of knowledge representation and inference. Two examples are also givwn to explain monotonic and non-monotonic rules, respectively. "To get the most out of the chapter. readers had better gain a thorough understanding of predicate logic first. Chapter 6 presents several realistic application scenarios to which the Semantic Web technology can be applied. including horizontal information products at Elsevier, data integration at Audi, skill finding at Swiss Life, a think tank portal at EnerSearch, e-learning. Web services, multimedia collection indexing, online procurement, raid device interoperability. These case studies give us some real feelings about the Semantic Web.
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  18. Spinning the Semantic Web : bringing the World Wide Web to its full potential (2003) 0.00
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  19. Weller, K.: Knowledge representation in the Social Semantic Web (2010) 0.00
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    Language
    e

Languages

  • e 18
  • d 1

Types

  • m 19
  • s 5

Subjects

Classifications