The lattice-based approaches for mining association rules: a review-Reference-Cited by-同舟云学术

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The lattice-based approaches for mining association rules: a review

Published:2016-05-20 Issue:4 Volume:6 Page:140-151
ISSN:1942-4787
Container-title:Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
language:en
Short-container-title:WIREs Data Mining Knowl Discov

Author:

Le Tuong¹²,Vo Bay³⁴

Affiliation:

1. Division of Data Science; Ton Duc Thang University; Ho Chi Minh City Vietnam

2. Faculty of Information Technology; Ton Duc Thang University; Ho Chi Minh City Vietnam

3. Faculty of Information Technology; Ho Chi Minh City University of Technology; Ho Chi Minh City Vietnam

4. College of Electronics and Information Engineering; Sejong University; Seoul Republic of Korea

Publisher

Wiley

Subject

General Computer Science

Reference75 articles.

1. Training and assessing classification rules with imbalanced data;Menardi;Data Min Knowl Discov,2014

2. Text mining for market prediction: a systematic review;Nassirtoussi;Expert Syst Appl,2014

3. Learning and inspecting classification rules from longitudinal epidemiological data to identify predictive features on hepatic steatosis;Niemann;Expert Syst Appl,2014

4. Classification based on association rules: a lattice-based approach;Nguyen;Expert Syst Appl,2012

5. Extracting classification rules from modified fuzzy min-max neural network for data with mixed attributes;Shindea;Appl Soft Comput,2016

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1. Association rule mining with fuzzy linguistic information based on attribute partial ordered structure;Soft Computing;2023-09-20

2. Frequent pattern mining-based log file partition for process mining;Engineering Applications of Artificial Intelligence;2023-08

3. An Improving Approach for Top-Rank-k Frequent Pattern Mining;Vietnam Journal of Computer Science;2022-05-11

4. A new approach for efficiently mining frequent weighted utility patterns;Applied Intelligence;2022-04-12

5. FR-Tree: A novel rare association rule for big data problem;Expert Systems with Applications;2022-01

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