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Procedia Computer Science
Article . 2018 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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Procedia Computer Science
Article
License: CC BY NC ND
Data sources: UnpayWall
DBLP
Conference object . 2023
Data sources: DBLP
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Mining High-Utility Patterns in Uncertain Tensors

Authors: Aurélien Coussat; Nicolas Nadisic; Loïc Cerf;

Mining High-Utility Patterns in Uncertain Tensors

Abstract

Abstract Transactional datasets are 0/1 matrices, which generically stand for objects having Boolean properties. If every cell of the matrix is additionally associated with a real number called utility, a high-utility itemset relates to a all-ones sub-matrix with utilities that sum to a high-enough value. This article shows that “having a total utility exceeding a threshold” is a piecewise (anti-)monotone constraint, even in presence of both positive and negative utilities. For that reason, a generic algorithm, multidupehack, can prune the search of the high-utility patterns defined in a broader context than the 0/1 matrix: the uncertain tensor. Moreover, the utilities may relate to only some of the dimensions, the patterns can be forced (or not) to be closed and to satisfy additional constraints. A real-world application, which exploits all those possibilities, is presented. Despite its versatility, the proposal is also shown competitive when it comes to mining 0/1 matrices, a special case treated by dozens of specific algorithms.

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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
gold