About: Relational model of data over domains with similarities: an extension for similarity queries and knowledge extraction.     Goto   Sponge   NotDistinct   Permalink

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Description
  • We present an extension of Codd's relational model of data. Our extension is motivated by similarity-based querying. It consists in equipping each domain of attribute values with a similarity relation and in modifying the classical relational model in order to account for issues generated by adding similarities. As a counterpart to data tables over a set of domains of Codd's model, we introduce ranked data tables over domains with similarities. We present a relational algebra, and tuple and domain calculi for our model and prove their equivalence. An interesting point is that our relational algebra contains operations like \mathrm{top}_k (k best results matching a query). Then, we study functional dependencies extended by similarities, argue that they form a new type of data dependency not captured by the classical model, prove a completeness result w.r.t. Armstrong-like rules, describe non-redundant bases and provide an algorithm for computing the bases. In addition to that, we compare our
  • We present an extension of Codd's relational model of data. Our extension is motivated by similarity-based querying. It consists in equipping each domain of attribute values with a similarity relation and in modifying the classical relational model in order to account for issues generated by adding similarities. As a counterpart to data tables over a set of domains of Codd's model, we introduce ranked data tables over domains with similarities. We present a relational algebra, and tuple and domain calculi for our model and prove their equivalence. An interesting point is that our relational algebra contains operations like \mathrm{top}_k (k best results matching a query). Then, we study functional dependencies extended by similarities, argue that they form a new type of data dependency not captured by the classical model, prove a completeness result w.r.t. Armstrong-like rules, describe non-redundant bases and provide an algorithm for computing the bases. In addition to that, we compare our (en)
Title
  • Relational model of data over domains with similarities: an extension for similarity queries and knowledge extraction.
  • Relational model of data over domains with similarities: an extension for similarity queries and knowledge extraction. (en)
skos:prefLabel
  • Relational model of data over domains with similarities: an extension for similarity queries and knowledge extraction.
  • Relational model of data over domains with similarities: an extension for similarity queries and knowledge extraction. (en)
skos:notation
  • RIV/61989592:15310/06:00002583!RIV10-MSM-15310___
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • Z(MSM6198959214)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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http://linked.open...iv/duvernostUdaju
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  • 497063
http://linked.open...ai/riv/idVysledku
  • RIV/61989592:15310/06:00002583
http://linked.open...riv/jazykVysledku
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  • Relational model; domains with similarities; similarity queries; knowledge extraction. (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [FC224D309BF8]
http://linked.open...i/riv/mistoVydani
  • New York
http://linked.open...i/riv/nazevZdroje
  • The 2006 IEEE International Conference Information Reuse and Integration
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Bělohlávek, Radim
  • Vychodil, Vilém
http://linked.open...n/vavai/riv/zamer
number of pages
http://purl.org/ne...btex#hasPublisher
  • IEEE Computer Society Press
https://schema.org/isbn
  • 0-7803-9788-6
http://localhost/t...ganizacniJednotka
  • 15310
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