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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao https://doi.org/10.1...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
https://doi.org/10.1109/grc.20...
Article . 2012 . Peer-reviewed
License: STM Policy #29
Data sources: Crossref
DBLP
Conference object . 2023
Data sources: DBLP
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Vertical mining for high utility itemsets

Authors: Wei Song 0004; Yu Liu; Jinhong Li;

Vertical mining for high utility itemsets

Abstract

Recently, high utility itemsets mining becomes one of the most important research issues in data mining due to its ability to consider different profit values for every item. In the past studies, most algorithms generate high utility itemsets from a set of transactions in horizontal data format. Inspired by the problem of frequent itemset mining, vertical mining may be a promising approach superior to horizontal mining. In this paper, a high utility itemsets mining algorithm based on vertical database layout is proposed. Candidate high utility itemsets are discovered by intersection of covers at first. Then, high utility itemsets are checked within candidates by scanning database once. Thus, the advantages of vertical database layout, such as low storage, and high efficiency, are utilized. Experimental results show that the proposed algorithm is both efficient and scalable.

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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!
7
Average
Top 10%
Average
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