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Indexing and Retrieval of Non-Text Information

Bag om Indexing and Retrieval of Non-Text Information

The scope of this volume will encompass a collection of research papers related to indexing and retrieval of online non-text information. In recent years, the Internet has seen an exponential increase in the number of documents placed online that are not in textual format. These documents appear in a variety of contexts, such as user-generated content sharing websites, social networking websites etc. and formats, including photographs, videos, recorded music, data visualizations etc. The prevalence of these contexts and data formats presents a particularly challenging task to information indexing and retrieval research due to many difficulties, such as assigning suitable semantic metadata, processing and extracting non-textual content automatically, and designing retrieval systems that "speak in the native language" of non-text documents.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783110260571
  • Indbinding:
  • Hardback
  • Sideantal:
  • 440
  • Udgivet:
  • 15. oktober 2012
  • Størrelse:
  • 160x30x236 mm.
  • Vægt:
  • 805 g.
  • 2-3 uger.
  • 16. december 2024
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Forlænget returret til d. 31. januar 2025

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Beskrivelse af Indexing and Retrieval of Non-Text Information

The scope of this volume will encompass a collection of research papers related to indexing and retrieval of online non-text information. In recent years, the Internet has seen an exponential increase in the number of documents placed online that are not in textual format. These documents appear in a variety of contexts, such as user-generated content sharing websites, social networking websites etc. and formats, including photographs, videos, recorded music, data visualizations etc. The prevalence of these contexts and data formats presents a particularly challenging task to information indexing and retrieval research due to many difficulties, such as assigning suitable semantic metadata, processing and extracting non-textual content automatically, and designing retrieval systems that "speak in the native language" of non-text documents.

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