Approaches to Propositionalization: State of the Art Review
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F04%3A00106281" target="_blank" >RIV/68407700:21230/04:00106281 - 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
Approaches to Propositionalization: State of the Art Review
Original language description
Systems aiming at discovering interesting knowledge in data, now commonly called data mining systems, are typically employed in finding patterns in a single relational table. Most of mainstream data mining tools are not applicable in the more challengingtask of finding knowledge in structured data represented by a multi-relational database. Although a family of methods known as inductive logic programming have been developed to tackle that challenge by immediate means, the idea of adapting structured data into a simpler form digestible by the wealth of AVL systems tempting to data miners. This kind of conversion is also known as most influential propositionalization. Here we provide a review of the most influential propositionalization approaches andsystems, and conduct a mutual performance comparison among a subsets of these systems.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
<a href="/en/project/1K04108" target="_blank" >1K04108: Research and implementation of methods of efficient database propositionalization</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2004
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů