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Elsevier电子期刊(8)

在“Elsevier电子期刊”中，命中：8条，耗时：0.0729692 秒

在所有数据库中总计命中：28条

1.Incremental mining of weighted maximal frequent itemsets from dynamic databases

作者：Unil Yun ; ^{yunei@sejong.ac.kr" class="auth_mail" title="E-mail the corresponding author} ; Gangin Lee ^{ganginlee@sju.ac.kr" class="auth_mail" title="E-mail the corresponding author}

关键词：Data mining ; Frequent pattern mining ; Incremental mining ; Maximal pattern mining ; Weight conditions

刊名：Expert Systems with Applications

出版年：2016

2.RWFIM: Recent weighted-frequent itemsets mining

作者：Jerry Chun-Wei Lin^a ; ^b ; ^{jerrylin@ieee.org" class="auth_mail" title="E-mail the corresponding author} ; Wensheng Gan^a ; ^{wsgan001@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Philippe Fournier-Viger^c ; ^{philippe.fournier-viger@umoncton.ca" class="auth_mail" title="E-mail the corresponding author} ; Tzung-Pei Hong^d ; ^e ; ^{tphong@nuk.edu.tw" class="auth_mail" title="E-mail the corresponding author}

关键词：Weighted frequent itemsets mining ; Time-sensitive constraint ; Recent pattern ; Projected-based ; EW2P strategy

刊名：Engineering Applications of Artificial Intelligence

出版年：2015

3.Mining high-utility itemsets based on particle swarm optimization

作者：Jerry Chun-Wei Lin^a ; ^{jerrylin@ieee.org" class="auth_mail" title="E-mail the corresponding author} ; Lu Yang^a ; ^{luyang@ikelab.net" class="auth_mail" title="E-mail the corresponding author} ; Philippe Fournier-Viger^b ; ^{phifv@hitsz.edu.cn" class="auth_mail" title="E-mail the corresponding author} ; Jimmy Ming-Thai Wu^c ; ^{wmt@wmt35.idv.tw" class="auth_mail" title="E-mail the corresponding author} ; Tzung-Pei Hong^d ; ^f ; ^{tphong@nuk.edu.tw" class="auth_mail" title="E-mail the corresponding author} ; Leon Shyue-Liang Wang^e ; ^{slwang@nuk.edu.tw" class="auth_mail" title="E-mail the corresponding author} ; Justin Zhan^c ; ^{justin.zhan@unlv.edu" class="auth_mail" title="E-mail the corresponding author}

关键词：Evolutionary computation ; High-utility itemsets ; Particle swarm optimization ; Discrete ; Transaction-weighted utility model

刊名：Engineering Applications of Artificial Intelligence

出版年：2016

4.A new method for mining Frequent Weighted Itemsets based on WIT-trees

作者：Bay Vo^a ; ^{vdbay@itc.edu.vn} ; Frans Coenen^b ; ^{Coenen@liverpool.ac.uk} ; Bac Le^c ; ^{lhbac@fit.hcmus.edu.vn}

关键词：Data mining ; Frequent Weighted Itemset ; Frequent weighted support ; WIT-trees ; WIT-FWI

刊名：Expert Systems with Applications

出版年：2013

5.Mining frequent itemsets in data streams using the weighted sliding window model

作者：Pauray S.M. Tsai

关键词：Data mining ; Data stream ; Weighted sliding window model ; Association rule ; Frequent itemset

刊名：Expert Systems with Applications

出版年：2009

6.An incremental mining algorithm for high utility itemsets

作者：Chun-Wei Lin^a ; ^b ; ^{jerrylin@ieee.org} ; Guo-Cheng Lan^c ; ^{rrfoheiay@gmail.com} ; Tzung-Pei Hong^a ; ^d ; ^{tphong@nuk.edu.tw}

关键词：Utility mining ; High utility itemset ; Incremental mining ; FUP concept ; Two-phase algorithm

刊名：Expert Systems with Applications

出版年：2012

7.Novel alarm correlation analysis system based on association rules mining in telecommunication networks

作者：Tongyan Li ; Xingming Li

关键词：Alarm correlation analysis ; Association rules mining ; Neural network ; Weighted frequent pattern tree ; Weighted potential frequent itemsets

刊名：Information Sciences

出版年：2010

8.A scalable algorithm for the market basket analysis

作者：Luí ; s Cavique

关键词：Market basket analysis ; Frequent itemset mining ; Maximum-weighted clique

刊名：Journal of Retailing and Consumer Services

出版年：2007

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