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Indexing and Retrieval of Non-Text Information

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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  • Språk:
  • Engelska
  • ISBN:
  • 9783110260571
  • Format:
  • Inbunden
  • Sidor:
  • 440
  • Utgiven:
  • 15. oktober 2012
  • Mått:
  • 160x30x236 mm.
  • Vikt:
  • 805 g.
Leveranstid: 2-4 veckor
Förväntad leverans: 18. december 2024

Beskrivning av 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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