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Gibbs Sampling Subjectively Interesting Tiles

descriptionPublicationkeyboard_double_arrow_right Part of book or chapter of book , Conference object , Article 01 Jan 2020 Belgium, France English Publisher:Springer International PublishingFunded by:EC | FORSIED, EC | PEGASUS-2
Authors: Bendimerad, Anes; Lijffijt, Jefrey; Plantevit, Marc; Robardet, Céline; de Bie, Tijl;

doi: 10.1007/978-3-030-44584-3_7

handle: 1854/LU-8647584

Gibbs Sampling Subjectively Interesting Tiles

Abstract

The local pattern mining literature has long struggled with the so-called pattern explosion problem: the size of the set of patterns found exceeds the size of the original data. This causes computational problems (enumerating a large set of patterns will inevitably take a substantial amount of time) as well as problems for interpretation and usability (trawling through a large set of patterns is often impractical).

Countries
Belgium, France
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Keywords

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI], Mathematics and Statistics, Technology and Engineering, Subjective interestingness, Gibbs sampling, Pattern mining, Pattern sampling, [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], [INFO.INFO-LG] Computer Science [cs]/Machine Learning [cs.LG], KNOWLEDGE DISCOVERY

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
3
Average
Average
Average
Green
hybrid