Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Nekvapil, Viktor | |
| dc.contributor.editor | Steinberger, Josef | |
| dc.contributor.editor | Zíma, Martin | |
| dc.contributor.editor | Fiala, Dalibor | |
| dc.contributor.editor | Dostal, Martin | |
| dc.contributor.editor | Nykl, Michal | |
| dc.date.accessioned | 2017-10-09T12:19:33Z | |
| dc.date.available | 2017-10-09T12:19:33Z | |
| dc.date.issued | 2017 | |
| dc.identifier.citation | STEINBERGER, Josef ed.; ZÍMA, Martin ed.; FIALA, Dalibor ed.; DOSTAL, Martin ed.; NYKL, Michal ed. Data a znalosti 2017: sborník konference, Plzeň, Hotel Angelo 5. - 6. října 2017. 1. vyd. Plzeň: Západočeská univerzita v Plzni, 2017, s. 198-203. ISBN 978-80-261-0720-0. | cs |
| dc.identifier.isbn | 978-80-261-0720-0 | |
| dc.identifier.uri | https://www.zcu.cz/export/sites/zcu/pracoviste/vyd/online/DataAZnalosti2017.pdf | |
| dc.identifier.uri | http://hdl.handle.net/11025/26363 | |
| dc.format | 6 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en | en |
| dc.publisher | Západočeská univerzita v Plzni | cs |
| dc.rights | © Západočeská univerzita v Plzni | cs |
| dc.subject | důvěryhodné znalosti | cs |
| dc.subject | hodnocení | cs |
| dc.subject | data mining | cs |
| dc.title | Applying trusted knowledge in evaluation phase of data mining | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | conferenceObject | en |
| dc.rights.access | openAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | New concept of Trusted Knowledge (TK) is introduced. Trusted Knowledge are data from trusted organizations such as ministries, statistical of-fices and so on which can replace domain expert in the evaluation phase of the data mining task. The approach called “A/TK-formulas” enables to filter out re-sulting patterns which are consequences of Trusted Knowledge and thus ena-bles user to concentrate on interesting ones. Conversely, user can request to show only resulting patterns which are consequences of TK to see which of them are in line with TK. The third option enables to request patterns which are in contradiction to the TK. Further new features of Trusted Knowledge frame-work are introduced in this paper – Trusted Knowledge for mining histograms and Trusted Knowledge hints. | en |
| dc.subject.translated | trusted knowledge | en |
| dc.subject.translated | evaluation | en |
| dc.subject.translated | data mining | en |
| dc.type.status | Peer-reviewed | en |
| Vyskytuje se v kolekcích: | Data a znalosti 2017 Data a znalosti 2017 | |
Soubory připojené k záznamu:
| Soubor | Popis | Velikost | Formát | |
|---|---|---|---|---|
| Nekvapil.pdf | Plný text | 654,92 kB | Adobe PDF | Zobrazit/otevřít |
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