Scalable Performance of FCbO Algorithm on Museum Data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F16%3A33160379" target="_blank" >RIV/61989592:15310/16:33160379 - isvavai.cz</a>
Result on the web
<a href="http://ceur-ws.org/Vol-1624/paper28.pdf" target="_blank" >http://ceur-ws.org/Vol-1624/paper28.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Scalable Performance of FCbO Algorithm on Museum Data
Original language description
Formal Concept Analysis - known as a technique for data analysis and visualisation - can also be applied as a means of creating interaction approaches that allow for knowledge discovery within collections of content. These interaction approaches rely on performant algorithms that can generate conceptual neighbourhoods based on a single formal concept, or incrementally compute and update a set of formal concepts given changes to a formal context. Using case studies based on content from museum collections, this paper describes the scalability limitations of existing interaction approaches and presents an implementation and evaluation of the FCbO update algorithm as a means of updating formal concepts from large and dynamically changing museum datasets.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
IN - Informatics
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
CEUR Workshop Proceedings
ISBN
978-5-600-01454-1
ISSN
1613-0073
e-ISSN
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Number of pages
14
Pages from-to
363-376
Publisher name
CEUR-WS
Place of publication
Moskva
Event location
Moskva
Event date
Jul 18, 2016
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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