| Attributes | Values |
|---|
| rdf:type
| |
| Description
| - V této práci předkládáme rámec pro interakitvní, iteraticní a intuitivní dolování víceúrovňových asociačních, charakterizačních a klasifikačních pravidel nad daty organizovánými ve víceúrovňových konceptuálních hierarchiích. Tento rámec se nazývá OLAM SE (Self Explaining On-Line Analytical Mining) a je předpokládán jako rozšíření OLAPu nebo jako alternatica k Hanovu OLAMu. OLAM zpracovává data uložená ve struktuře datových kostek, která je založena na dané konceptuální hierarchii. OLAM SE určuje hodnotu minimální podpory z uživatelem definované hodnoty pokrytí dat za použití principu kódování entropie. Stejně tak určuje maximální prahovou hodnotu k zamezení zkoumání znalosti, která je zřejmá a potencionálně nezajímavá. Hlavní část dat je tudíž popsána pomocí frekventovaných vzorů. Prezentace výsledků je inspirována notací UML diagamů. Zahrnuje uzly grafu, kterými jsou frekventované množiny dat reprezentov (cs)
- In this paper, we propose a framework for interactive, iterative, and intuitive mining of multilevel association, characterization and classification rules on data organized in multi-level conceptual hierarchies. This framework is called OLAM SE (Self Explaining On-Line Analytical Mining) and it is proposed as an extension of OLAP or as an alternative to Han's OLAM. OLAM processes data stored in data cubes structure of which is based on a given conceptual hierarchy. OLAM SE determines minimum support value from user defined cover value of data with usage of entropy coding principle. It also automatically determines the maximum threshold to avoid explaining knowledge that is obvious and so potentially uninteresting. Major part of data is thus described by frequent patterns. The presentation of results is inspired by UML diagram notation. It contains a graph nodes of which are frequent data sets represented as packages including sub packages - data classes or items. Edges represent relations or patterns
- In this paper, we propose a framework for interactive, iterative, and intuitive mining of multilevel association, characterization and classification rules on data organized in multi-level conceptual hierarchies. This framework is called OLAM SE (Self Explaining On-Line Analytical Mining) and it is proposed as an extension of OLAP or as an alternative to Han's OLAM. OLAM processes data stored in data cubes structure of which is based on a given conceptual hierarchy. OLAM SE determines minimum support value from user defined cover value of data with usage of entropy coding principle. It also automatically determines the maximum threshold to avoid explaining knowledge that is obvious and so potentially uninteresting. Major part of data is thus described by frequent patterns. The presentation of results is inspired by UML diagram notation. It contains a graph nodes of which are frequent data sets represented as packages including sub packages - data classes or items. Edges represent relations or patterns (en)
|
| Title
| - Interactive Mining on Hierarchical Data
- Interaktivní dolování dat nad hierarchickými daty (cs)
- Interactive Mining on Hierarchical Data (en)
|
| skos:prefLabel
| - Interactive Mining on Hierarchical Data
- Interaktivní dolování dat nad hierarchickými daty (cs)
- Interactive Mining on Hierarchical Data (en)
|
| skos:notation
| - RIV/00216305:26230/07:PU73631!RIV08-MSM-26230___
|
| http://linked.open.../vavai/riv/strany
| |
| http://linked.open...avai/riv/aktivita
| |
| http://linked.open...avai/riv/aktivity
| |
| http://linked.open...vai/riv/dodaniDat
| |
| http://linked.open...aciTvurceVysledku
| |
| http://linked.open.../riv/druhVysledku
| |
| http://linked.open...iv/duvernostUdaju
| |
| http://linked.open...titaPredkladatele
| |
| http://linked.open...dnocenehoVysledku
| |
| http://linked.open...ai/riv/idVysledku
| - RIV/00216305:26230/07:PU73631
|
| http://linked.open...riv/jazykVysledku
| |
| http://linked.open.../riv/klicovaSlova
| - interactive, intuitive, on-line, data mining, OLAP, data warehouse, association, characterization, classification, nonna&,iuml,ve Bayessian classification, uml notation based presentation (en)
|
| http://linked.open.../riv/klicoveSlovo
| |
| http://linked.open...ontrolniKodProRIV
| |
| http://linked.open...v/mistoKonaniAkce
| |
| http://linked.open...i/riv/mistoVydani
| |
| http://linked.open...i/riv/nazevZdroje
| - Proceedings of the 13th Conference STUDENT EEICT 2007 Volume 4
|
| http://linked.open...in/vavai/riv/obor
| |
| http://linked.open...ichTvurcuVysledku
| |
| http://linked.open...cetTvurcuVysledku
| |
| http://linked.open...UplatneniVysledku
| |
| http://linked.open...iv/tvurceVysledku
| - Chmelař, Petr
- Stryka, Lukáš
|
| http://linked.open...vavai/riv/typAkce
| |
| http://linked.open.../riv/zahajeniAkce
| |
| http://linked.open...n/vavai/riv/zamer
| |
| number of pages
| |
| http://purl.org/ne...btex#hasPublisher
| - Vysoké učení technické v Brně
|
| https://schema.org/isbn
| |
| http://localhost/t...ganizacniJednotka
| |
| is http://linked.open...avai/riv/vysledek
of | |
![[RDF Data]](/fct/images/sw-rdf-blue.png)
![[cxml]](/fct/images/cxml_doc.png)
![[csv]](/fct/images/csv_doc.png)
![[text]](/fct/images/ntriples_doc.png)
![[turtle]](/fct/images/n3turtle_doc.png)
![[ld+json]](/fct/images/jsonld_doc.png)
![[rdf+json]](/fct/images/json_doc.png)
![[rdf+xml]](/fct/images/xml_doc.png)
![[atom+xml]](/fct/images/atom_doc.png)
![[html]](/fct/images/html_doc.png)