عنوان

High-utility pattern mining :

شابک

3030049213

شابک

3030049221

شابک

9783030049218

شابک

9783030049225

شابک اشتباه

3030049205

شابک اشتباه

9783030049201

عنوان اصلي

High-utility pattern mining :

نام عام مواد

[Book]

ساير اطلاعات عنواني

theory, algorithms and applications /

نام نخستين پديدآور

editors, Philippe Fournier-Viger, Jerry Chun-Wei Lin, Roger Nkambou, Bay Vo and Vincent S. Tseng.

محل نشرو پخش و غیره

Cham, Switzerland :

نام ناشر، پخش کننده و غيره

Springer,

تاریخ نشرو بخش و غیره

[2019]

نام خاص و کميت اثر

1 online resource

عنوان فروست

Studies in big data,

مشخصه جلد

volume 51

شاپا ي ISSN فروست

2197-6511 ;

متن يادداشت

Includes bibliographical references.

متن يادداشت

Intro; Preface; Contents; A Survey of High Utility Itemset Mining; 1 Introduction; 2 Problem Definition; 2.1 Frequent Itemset Mining; 2.2 High Utility Itemset Mining; 2.3 Key Properties of the Problem of High Utility Itemset Mining; 3 Algorithms; 3.1 Two Phase Algorithms; 3.2 One Phase Algorithms; 3.3 A Comparison of High Utility Itemset Mining Algorithms; 4 Extensions of the Problem; 4.1 Concise Representations of High Utility Itemsets; 4.2 Top-k High Utility Itemset Mining; 4.3 High Utility Itemset Mining with the Average Utility Measure

متن يادداشت

3 Approaches to Top-K High Utility Itemset Mining3.1 Two-Phase Methods; 3.2 One-Phase Methods; 4 Performance Analysis of State-of-the-Art Top-K HUI Mining Methods; 4.1 Experimental Design; 4.2 Experimental Results; 5 Top-K High Utility Pattern Mining Variants; 6 Open Issues and Future Research Opportunities; 7 Conclusions; References; A Survey of High Utility Pattern Mining Algorithms for Big Data; 1 Introduction; 2 High Utility Pattern Mining: Overview; 2.1 Overview of Pattern Mining Methodologies; 3 Overview of Big Data Paradigms; 3.1 Parallel Processing; 3.2 Distributed Platforms

متن يادداشت

3.1 Mining High Utility-Probability Sequential Patterns in Uncertain Databases3.2 High-Utility Sequential Pattern Mining with Multiple Minimum Utility Thresholds; 3.3 Top-k High Utility Sequential Pattern Mining; 3.4 Mining Periodic High Utility Sequential Patterns; 3.5 Related Problems; 4 Research Opportunities; 5 Conclusion; References; Efficient Algorithms for High Utility Itemset Mining Without Candidate Generation; 1 Introduction; 2 Background; 2.1 Preliminaries; 2.2 Related Work; 3 Mining High Utility Itemsets; 3.1 Utility-List Structure; 3.2 The Proposed Method: HUI-Miner

متن يادداشت

3.3 Data Stream Mining4 Scalable and Parallel High Utility Itemset Mining; 4.1 Scalable Serial Processing; 4.2 Distributed and Parallel Processing; 5 High Utility Sequential Pattern Mining; 5.1 Serial Processing; 5.2 Distributed and Parallel Processing; 6 Conclusions and Future Directions; References; A Survey of High Utility Sequential Pattern Mining; 1 Introduction; 2 Problem Definition and Algorithm; 2.1 Definition of the High Utility Sequential Pattern Mining Problem; 2.2 Upper Bounds on umax and their Key Properties; 2.3 Algorithms; 3 Extensions of the Problem

متن يادداشت

4.4 High Utility Itemset Mining with Negative Utilities4.5 High Utility Itemset Mining with Discount Strategies; 4.6 Mining High Utility Itemset with a Maximum Length Constraint; 4.7 Mining High Utility Itemsets that Are Correlated; 4.8 Periodic High Utility Itemset Mining; 4.9 On-Shelf High Utility Itemset Mining; 4.10 High Utility Itemset Mining in Dynamic Databases; 4.11 Other Extensions; 5 Research Opportunities; 6 Open-Source Implementations; 7 Conclusion; References; A Comparative Study of Top-K High Utility Itemset Mining Methods; 1 Introduction; 2 Preliminaries and Problem Statement

بدون عنوان

0

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

بدون عنوان

8

متن يادداشت

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 pattern mining, and describes recent advances, applications, open-source software, and research opportunities. It also discusses several types of discrete data, including customer transaction data and sequential data. The book consists of twelve chapters, seven of which are surveys presenting the main subfields of high-utility pattern mining, including itemset mining, sequential pattern mining, big data pattern mining, metaheuristic-based approaches, privacy-preserving pattern mining, and pattern visualization. The remaining five chapters describe key techniques and applications, such as discovering concise representations and regular patterns.

منبع سفارش / آدرس اشتراک

Springer Nature

شماره انبار

com.springer.onix.9783030049218

عنوان

High-utility pattern mining.

شماره استاندارد بين المللي کتاب و موسيقي

9783030049201

موضوع مستند نشده

Big data.

موضوع مستند نشده

Data mining.

موضوع مستند نشده

Big data.

موضوع مستند نشده

COMPUTERS-- General.

موضوع مستند نشده

Data mining.

موضوع مستند نشده

COM-- 000000

موضوع مستند نشده

UYQ

موضوع مستند نشده

UYQ

شماره

ويراست

شماره رده

مستند نام اشخاص تاييد نشده

Fournier-Viger, Philippe

مستند نام اشخاص تاييد نشده

Lin, Jerry Chun-Wei

مستند نام اشخاص تاييد نشده

Nkambou, Roger,1966-

مستند نام اشخاص تاييد نشده

Tseng, Vincent S.

مستند نام اشخاص تاييد نشده

Vo, Bay

تاريخ عمليات

20200823081046.0

قواعد فهرست نويسي ( بخش توصيفي )

pn

نام الکترونيکي

نوع ماده

[Book]

تكميل شده

Y