Mining Interesting Sequential Patterns using a Novel Balanced Utility Measure

QR koda

Mining Interesting Sequential Patterns using a Novel Balanced Utility Measure

294

Shranjeno v:

Bibliografske podrobnosti
Những tác giả chính:	Dương, Văn Hải, Trương, Chí Tín, Lê, Hoài Bắc, Philippe, Fournier-Viger
Format:	Journal article
Jezik:	English
Izdano:	Elsevier 2024
Online dostop:	https://scholar.dlu.edu.vn/handle/123456789/3442
Oznake:	Označite Brez oznak, prvi označite!

Thư viện lưu trữ:	Thư viện Trường Đại học Đà Lạt

Podobne knjige/članki

Mining interesting sequences with low average cost and high average utility
od: Trương, Chí Tín, et al.
Izdano: (2023)

Mining High Utility Sequences with a Novel Utility Function
od: Huỳnh, Hanh Thông, et al.
Izdano: (2023)

Efficient high average-utility itemset mining using novel vertical weak upper-bounds
od: Trương, Chí Tín, et al.
Izdano: (2023)

Efficient vertical mining of high average-utility itemsets based on novel upper-bounds
od: Trương, Chí Tín, et al.
Izdano: (2023)

An Explicit Relationship between Sequential Patterns and their Concise Representations
od: Dương, Văn Hải, et al.
Izdano: (2023)

Efficient Algorithms to Mine Concise Representations of Frequent High Utility Occupancy Patterns
od: Dương, Văn Hải, et al.
Izdano: (2024)

CG-FHAUI: An efficient algorithm for simultaneously mining succinct pattern sets of frequent high average utility itemsets
od: Dương, Văn Hải, et al.
Izdano: (2024)

Data mining for association rules and sequential patterns :
od: Adamo, Jean-Marc
Izdano: (2001)

Efficient algorithms for simultaneously mining concise representations of sequential patterns based on extended pruning conditions
od: Dương, Văn Hải, et al.
Izdano: (2023)

EHUSM: Mining High Utility Sequences with a Pessimistic Utility Model
od: Philippe Fournier-Viger, et al.
Izdano: (2023)

EHAUSM: An efficient algorithm for high average utility sequence mining
od: Trương, Chí Tín, et al.
Izdano: (2024)

Frequent high minimum average utility sequence mining with constraints in dynamic databases using efficient pruning strategies
od: Trương, Chí Tín, et al.
Izdano: (2023)

Research on the sequential pattern mining algorithms using prefix-tree structure : Doctoral thesis - Major: Computer Science
od: Phạm Thị Thiết
Izdano: (2013)

Balancing the national interest
Izdano: (1987)

Efficient algorithms for mining frequent high utility sequences with constraints
od: Trương, Chí Tín, et al.
Izdano: (2023)

FMaxCloHUSM: An efficient algorithm for mining frequent closed and maximal high utility sequences
od: Trương, Chí Tín, et al.
Izdano: (2023)

Efficient Algorithms for Mining Closed and Maximal High Utility Itemsets
od: Dương, Văn Hải, et al.
Izdano: (2023)

Pattern mining: Current challenges and opportunities
od: Philippe Fournier-Viger, et al.
Izdano: (2023)

High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound
od: Trần, Thống, et al.
Izdano: (2024)

High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound
od: Trần, Thống, et al.
Izdano: (2024)

Efficient algorithms for mining closed and maximal high utility itemsets
od: Dương, Văn Hải, et al.
Izdano: (2023)

Fast generation of sequential patterns with item constraints from concise representations
od: Dương, Văn Hải, et al.
Izdano: (2021)

Measuring situational interest in academic domains /

Efficient mining of concise and informative representations of frequent high utility itemsets
od: Trần, Thống, et al.
Izdano: (2024)

Efficient mining of concise and informative representations of frequent high utility itemsets
od: Trần, Thống, et al.
Izdano: (2024)

FCloSM, FGenSM: two efficient algorithms for mining frequent closed and generator sequences using the local pruning strategy
od: Lê, Hoài Bắc, et al.
Izdano: (2023)

MFG-HUI: An Efficient Algorithm for Mining Frequent Generators of High Utility Itemsets
od: Dương, Văn Hải, et al.
Izdano: (2024)

A fine balance : a novel
od: Rohinton Mistry
Izdano: (2015)

Approximate high utility itemset mining in noisy environments
od: Yoonji Baek, et al.
Izdano: (2021)

H-FHAUI: Hiding Frequent High Average Utility Itemsets
od: Lê, Hoài Bắc, et al.
Izdano: (2023)

Data mining patterns :
Izdano: (2008)

Complex Pattern Mining
od: Appice, Annalisa, et al.
Izdano: (2020)

Biomass carbon measurements and substrate utilization patterns of microbial populations from soils amended with cadmium, copper, or zinc /
od: Knight, B. P.

Science and Technology in International Economic Law: Balancing Competing Interests, 1st edition
od: Bryan, Mercurio, editor, et al.
Izdano: (2020)

Balancing the triple bottom line in water supply planning for utilities /
od: Liner, Barry, Ph.D., P.E.

HUPSMT: An efficient algorithm for mining high utility-probability sequences in uncertain databases with multiple minimum utility thresholds
od: Trương, Chí Tín, et al.
Izdano: (2023)

Supervised Descriptive Pattern Mining
od: Ventura, Sebastián, et al.
Izdano: (2020)

MFG-HUI: An Efficient Algorithm for Mining Frequent Generators of High Utility Itemsets
od: Dương, Văn Hải, et al.
Izdano: (2024)

Mining association rules from high utility itemsets
od: Nguyễn, Thị Thúy Loan, et al.
Izdano: (2024)

Phosphorus compounds in sequential extracts of animal manures : Chemical speciation and a novel fractionation procedure /
od: Turner, Benjamin L.