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Relational model of data over domains with similarities: an extension for similarity queries and knowledge extraction.

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F06%3A00002583" target="_blank" >RIV/61989592:15310/06:00002583 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Relational model of data over domains with similarities: an extension for similarity queries and knowledge extraction.

  • Original language 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 theyform 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 compar

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BD - Information theory

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2006

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    The 2006 IEEE International Conference Information Reuse and Integration

  • ISBN

    0-7803-9788-6

  • ISSN

  • e-ISSN

  • Number of pages

    1500

  • Pages from-to

  • Publisher name

    IEEE Computer Society Press

  • Place of publication

    New York

  • Event location

  • Event date

  • Type of event by nationality

  • UT code for WoS article