About: Efficient Mining Under Rich Constraints Derived from Various Datasets     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

AttributesValues
rdf:type
Description
  • Mining patterns under many kinds of constraints is a key point to successfully get new knowledge. In this paper, we propose an efficient new algorithm Music-dfs which soundly and completely mines patterns with various constraints from large data and takes into account external data represented by several heterogeneous datasets. Constraints are freely built of a large set of primitives and enable to link the information scattered in various knowledge sources. Efficiency is achieved thanks to a new closure operator providing an interval pruning strategy applied during the depth-first search of a pattern space. A genomic case study shows both the effectiveness of our approach and the added-value of background knowledge such as free texts or gene ontologies in discovery of meaningful patterns.
  • Mining patterns under many kinds of constraints is a key point to successfully get new knowledge. In this paper, we propose an efficient new algorithm Music-dfs which soundly and completely mines patterns with various constraints from large data and takes into account external data represented by several heterogeneous datasets. Constraints are freely built of a large set of primitives and enable to link the information scattered in various knowledge sources. Efficiency is achieved thanks to a new closure operator providing an interval pruning strategy applied during the depth-first search of a pattern space. A genomic case study shows both the effectiveness of our approach and the added-value of background knowledge such as free texts or gene ontologies in discovery of meaningful patterns. (en)
  • Článek pojednává o algoritmu Music-dfs, který je efektivním, korektním a úplným algoritmem pro dolování vzorů. Zajímavé vzory jsou specifikovány na základě omezení, která jsou odvozena z databází různých typů. (cs)
Title
  • Efficient Mining Under Rich Constraints Derived from Various Datasets
  • Efektivní využití různorodých omezení při dolování vzorů z dat (cs)
  • Efficient Mining Under Rich Constraints Derived from Various Datasets (en)
skos:prefLabel
  • Efficient Mining Under Rich Constraints Derived from Various Datasets
  • Efektivní využití různorodých omezení při dolování vzorů z dat (cs)
  • Efficient Mining Under Rich Constraints Derived from Various Datasets (en)
skos:notation
  • RIV/68407700:21230/07:03133981!RIV08-AV0-21230___
http://linked.open.../vavai/riv/strany
  • 223;239
http://linked.open...avai/riv/aktivita
http://linked.open...avai/riv/aktivity
  • P(1ET101210513)
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
  • 419360
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/07:03133981
http://linked.open...riv/jazykVysledku
http://linked.open.../riv/klicovaSlova
  • constraints; gene expression; local patterns; microarray (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [CA528E07E384]
http://linked.open...i/riv/mistoVydani
  • Heidelberg
http://linked.open...i/riv/nazevZdroje
  • Knowledge Discovery in Inductive Databases
http://linked.open...in/vavai/riv/obor
http://linked.open...ichTvurcuVysledku
http://linked.open...cetTvurcuVysledku
http://linked.open...vavai/riv/projekt
http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Kléma, Jiří
  • Cremilleux, B.
  • Soulet, A.
number of pages
http://purl.org/ne...btex#hasPublisher
  • Springer-Verlag
https://schema.org/isbn
  • 978-3-540-75548-7
http://localhost/t...ganizacniJednotka
  • 21230
Faceted Search & Find service v1.16.118 as of Jun 21 2024


Alternative Linked Data Documents: ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 58 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software