Results 81 to 90 of about 15,313,538 (164)
application/pdf; "January 29, 2009."; Testimony before the Kansas Legislature, House Utilities Committee, presented by David Springe, Consumer Counsel, Citizens' Utility Ratepayer Board.Testimony in opposition to House Bill 2020.
Springe, David.
core +1 more source
Mining High Utility Itemsets with Regular Occurrence
High utility itemset mining (HUIM) plays an important role in the data mining community and in a wide range of applications. For example, in retail business it is used for finding sets of sold products that give high profit, low cost, etc. These itemsets
Komate Amphawan +3 more
doaj +1 more source
High average-utility itemsets mining (HAUIM) is an emerging topic in data mining. Compared to traditional high utility itemset mining, HAUIM more fairly measures the utility of itemsets by considering their lengths (number of items).
Jerry Chun-Wei Lin +2 more
doaj +1 more source
CLS-Miner: efficient and effective closed high-utility itemset mining [PDF]
High-utility itemset mining (HUIM) is a popular data mining task with applications in numerous domains. However, traditional HUIM algorithms often produce a very large set of high-utility itemsets (HUIs).
Quang-Huy Duong +7 more
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This research proposes the optimization of the Frequent Closed High-Utility Itemset Mining (FCHUIM) algorithm for retail transaction datasets using heuristic-based pruning techniques, Observed Support Ratio (OSR), Observed Weighted Lift (OWL), and ...
Kinana Syah Sulanjari, Chastine Fatichah
doaj +1 more source
Selective Database Projections Based Approach for Mining High-Utility Itemsets
High-utility itemset mining (HilIM) is an emerging area of data mining and is widely used. HilIM differs from the frequent itemset mining (FIM), as the latter considers only the frequency factor, whereas the former has been designed to address both ...
Anita Bai +2 more
doaj +1 more source
Comparison and Analysis of Three Measures for High Average-Utility Itemset Mining
High average-utility itemset mining is a significant research direction in data mining. The traditional average-utility (AU) measure employs itemset length as the normalization benchmark, which mitigates the bias toward long itemsets; however, it does ...
Yumei Li +6 more
doaj +1 more source
application/pdf; "February 19, 2008."; Testimony before the Kansas Legislature, House Utilities Committee, presented by David Springe, Consumer Counsel, Citizens' Utility Ratepayer Board.Testimony in opposition to House Bill 2806.
Springe, David.
core +1 more source
application/pdf; "March 17, 2003."; Testimony before the Kansas Legislature, Senate Utilities Committee, presented by David Springe, Consumer Counsel, Citizens' Utility Ratepayer Board."CURB is strongly opposed to what H.B.
Springe, David.
core +1 more source
application/pdf; "January 30, 2012."; Testimony before the Kansas Legislature, House Utilities Committee, presented by David Springe, Consumer Counsel, Citizens' Utility Ratepayer Board.Testimony in opposition to House Bill 2512.
Springe, David.
core +1 more source

