作者: Lime石灰 時間: 2025-3-21 20:22 作者: 難聽的聲音 時間: 2025-3-22 04:05 作者: 肉體 時間: 2025-3-22 05:47
2197-6503 ches, privacy-preserving pattern mining, and pattern visualization. The remaining five chapters describe key techniques and applications, such as discovering concise representations and regular patterns...?.978-3-030-04921-8Series ISSN 2197-6503 Series E-ISSN 2197-6511 作者: BORE 時間: 2025-3-22 09:14
Duy-Tai Dinh,Van-Nam Huynh,Bac Le,Philippe Fournier-Viger,Ut Huynh,Quang-Minh Nguyenwill be derived according to their historical progress and their increasing complexity as well. It will be seen that they all share common structural properties978-3-540-15241-5978-3-642-50094-7Series ISSN 0075-8442 Series E-ISSN 2196-9957 作者: Germinate 時間: 2025-3-22 16:38 作者: 享樂主義者 時間: 2025-3-22 20:09 作者: cushion 時間: 2025-3-23 00:13
A Survey of High Utility Sequential Pattern Mining,the downward-closure property used in pattern mining to reduce the search space. This chapter introduces the problem of high utility sequence mining, the state-of-art algorithms, applications, present related problems and research opportunities. A key contribution of the chapter is to also provide a作者: URN 時間: 2025-3-23 03:03
Efficient Algorithms for High Utility Itemset Mining Without Candidate Generation,abase. By avoiding candidate generation, HUI-Miner can efficiently mine high utility itemsets. To further speed up the construction of utility-lists, HUI-Miner* introduces an improved structure called utility-list* and an horizontal method to construct utility-lists*. Experimental results show that 作者: 大暴雨 時間: 2025-3-23 09:28
Mining High-Utility Irregular Itemsets, . (.), for efficiently mining high-utility irregular itemsets. The new-modified utility list structure (.) is applied for maintaining occurrence information simultaneously with utility value of an itemset and also for fast calculation of total utility of the itemset. Moreover, a new pruning techniq作者: 植物群 時間: 2025-3-23 10:56 作者: dendrites 時間: 2025-3-23 16:50
Extracting Potentially High Profit Product Feature Groups by Using High Utility Pattern Mining and that combines high utility pattern mining and aspect based sentiment analysis in order to extract groups of features that potentially increase profit and that need to be improved in order to increase user satisfaction. Experiments performed on patterns extracted by the proposed approach in comparis作者: capillaries 時間: 2025-3-23 19:42
Metaheuristics for Frequent and High-Utility Itemset Mining,on of metaheuristics to FIM and HUIM. Several metaheuristics have been presented, based on evolutionary or swarm intelligence algorithms, such as genetic algorithms, particle swarm optimization, ant colony optimization and bee swarm optimization.作者: CAGE 時間: 2025-3-24 00:30
Mining Compact High Utility Itemsets Without Candidate Generation,ke current algorithms that provide incomplete results, CHUI-Mine can discover the complete closed. or maximal HUIs with no miss. A comprehensive investigation is also presented to compare the relative advantages of different compact representations in terms of computational cost and compactness. To 作者: 沖突 時間: 2025-3-24 06:16 作者: Aspiration 時間: 2025-3-24 07:08 作者: 憂傷 時間: 2025-3-24 14:24
Supachai Laoviboon,Komate Amphawaneat X as a Hilbert space by itself. If X is not closed we have to deal with its closure thereby being enforced to speak of limit end-of-period wealth positions (random variables which are arbitrarily close to being feasible end-of-period wealth positions). So all the results which will be derived wi作者: 媽媽不開心 時間: 2025-3-24 16:05
Cheng-Wei Wu,Philippe Fournier-Viger,Jia-Yuan Gu,Vincent S. Tsengt der Zinsstruktur, geht jedoch wie das .-Modell von einer mit der Restlaufzeit fallenden Volatilit?t der Zinsraten aus. Am Rentenmarkt l??t sich jedoch des ?fteren eine u-f?rmige Volatilit?tsfunktion beobachten. Zur Abbildung dieses Smile-Effektes der Volatilit?tsstruktur werden in dieser Arbeit da作者: 背心 時間: 2025-3-24 19:31
Wolfgang Jentner,Daniel A. Keim aus sogenannten Inverse Floaters resultierte, die in der Erwartung fallender Zinsen gekauft wurden. Inverse Floaters sind Anleihen, deren Zinsraten an einen variablen Referenzzins wie die London Interbank Offered Rate (LIBOR) gekoppelt sind. ?Inverse“ bedeutet, da? bei fallendem Referenzzins die Zi作者: BRAWL 時間: 2025-3-25 00:15
Philippe Fournier-Viger,Jerry Chun-Wei Lin,VincentPresents an overview of the theory and core methods used in utility mining.Covers recent advances in high-utility mining.Includes stream, incremental, sequence, and big data mining.Discusses important作者: 離開 時間: 2025-3-25 06:33 作者: 彩色 時間: 2025-3-25 10:51
Springer Nature Switzerland AG 2019作者: paragon 時間: 2025-3-25 11:58
High-Utility Pattern Mining978-3-030-04921-8Series ISSN 2197-6503 Series E-ISSN 2197-6511 作者: Harness 時間: 2025-3-25 19:53 作者: INERT 時間: 2025-3-25 20:56 作者: GRIPE 時間: 2025-3-26 02:50 作者: 大火 時間: 2025-3-26 05:29
A Survey of High Utility Pattern Mining Algorithms for Big Data,ts ., defined based on a domain objective, is no less than a minimum utility threshold. Several high utility pattern mining algorithms have been proposed in the last decade, yet most do not scale to the type of data we are nowadays dealing with, the so-called .. This chapter aims to provide a compre作者: custody 時間: 2025-3-26 11:20 作者: SHOCK 時間: 2025-3-26 13:48
Efficient Algorithms for High Utility Itemset Mining Without Candidate Generation,ole in real-life applications such as market analysis. Traditional high utility itemset mining algorithms generate candidate itemsets and subsequently compute the exact utilities of these candidates. These algorithms have the drawback of generating numerous candidates most of which are discarded for作者: Aboveboard 時間: 2025-3-26 19:22
High Utility Association Rule Mining, well as find out customer trends based on their carts. To achieve this, a number of studies have examined high utility itemsets (HUIs). Traditional association rule mining algorithms only generate a set of highly frequent rules, but these rules do not provide useful answers for what the high utilit作者: STEER 時間: 2025-3-27 00:32
Mining High-Utility Irregular Itemsets,thods and data structures have been proposed to improve efficiency of mining for such itemsets. Besides, HUIM is extended in several aspects including the regarding of “regularity or irregularity of occurrence” on high utility itemsets. This leads to the emerging of high-utility regular itemsets min作者: 不連貫 時間: 2025-3-27 04:28
A Survey of Privacy Preserving Utility Mining,fit or weight) in transaction or sequence databases. HUPM can be applied in various fields such as market basket analysis, website clickstream analysis, stock market analysis, retail and bioinformatics. In the era of information technology, it has become easy to locate and access information. A grea作者: Epithelium 時間: 2025-3-27 08:08 作者: 猛然一拉 時間: 2025-3-27 11:07
Metaheuristics for Frequent and High-Utility Itemset Mining,thods, which explore very large search spaces to find near-optimal solutions in a reasonable time. Some metaheuristics are inspired by biological and physical phenomenons. During the last two decades, two population-based methods named evolutionary algorithms and swarm intelligence have shown high e作者: 好色 時間: 2025-3-27 14:43
Mining Compact High Utility Itemsets Without Candidate Generation,ucial problem that too many HUIs tend to be produced. This seriously degrades the performance of HUI mining in terms of execution and memory efficiency. Moreover, it is very hard for users to discover meaningful information in a huge number of HUIs. In this paper, we address this issue by proposing 作者: 賠償 時間: 2025-3-27 20:50 作者: manifestation 時間: 2025-3-28 01:35 作者: INCUR 時間: 2025-3-28 02:31
Loan T. T. Nguyen,Thang Mai,Bay Vodel, where agents may rearrange their portfolios at every time t ∈ [O,T]. For that purpose continuous-time selffinancing trading strategies are introduced in Section 4.1. Continuous-time selffinancing trading strategies allow for continuously rearranging the basic securities without requiring nor ge作者: 可耕種 時間: 2025-3-28 08:03 作者: Gleason-score 時間: 2025-3-28 14:29 作者: Frenetic 時間: 2025-3-28 16:59
Cheng-Wei Wu,Philippe Fournier-Viger,Jia-Yuan Gu,Vincent S. Tsengelle mit Hilfe der Baumverfahren von ./. (1990) bzw. . (1992) numerisch approximieren lassen. Als Einfaktormodelle werden in Abschnitt 6.1 die zeitstetige Version des Modells von ./.. und die zinsstrukturkonforme Variante des .-Modells beschrieben. Nachteil aller Einfaktormodelle ist jedoch, da? die作者: 憂傷 時間: 2025-3-28 22:19
Wolfgang Jentner,Daniel A. Keimind Finanztitel, deren Wert sich von dem Wert eines Basisinstrumentes (Underlying) ableitet. Basisinstrumente k?nnen u.a. Waren, andere Finanztitel, Indizes, W?hrungen und Zinsen sein. Millarden-Verluste aus dem Gesch?ft mit ?l-Terminkontrakten waren die Ursache dafür, da? die Metallgesellschaft End作者: overshadow 時間: 2025-3-28 23:56 作者: 滑稽 時間: 2025-3-29 05:22
2197-6503 cremental, sequence, and big data mining.Discusses important.This book presents an overview of techniques for discovering high-utility patterns (patterns with a high importance) in data. It introduces the main types of high-utility patterns, as well as the theory and core algorithms for high-utility作者: gimmick 時間: 2025-3-29 11:08
