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
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DOI - Digital Object Identifier
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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
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
BD - Information theory
OECD FORD branch
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Result continuities
Project
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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
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e-ISSN
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Number of pages
1500
Pages from-to
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Publisher name
IEEE Computer Society Press
Place of publication
New York
Event location
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Event date
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Type of event by nationality
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UT code for WoS article
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