Results 41 to 50 of about 2,506 (215)

A survey of itemset mining

, 2017
Itemset mining is an important subfield of data mining, which consists of discovering interesting and useful patterns in transaction databases. The traditional task of frequent itemset mining is to discover groups of items (itemsets) that appear ...
Jerry Chun‐Wei Lin, Vo, Bay, Bay Vo, Tin Truong Chi, Zhang, Ji, Philippe Fournier‐Viger, Hoai Bac Le, Chi, Tin Truong, Le, Hoai Bac, Lin, Jerry Chun-Wei, Ji Zhang, Fournier-Viger, Philippe   +11 more
core   +1 more source

Frequent itemset mining in high dimensional data: a review [PDF]

, 2018
This paper provides a brief overview of the techniques used in frequent itemset mining. It discusses the search strategies used; i.e. depth first vs. breadth-first, and dataset representation; i.e. horizontal vs. vertical representation.
Nurul Fariza Zulkurnain, Fatimah Audah Md. Zaki, Md. Zaki, Fatimah Audah, Zulkurnain, Nurul Fariza   +3 more
core   +1 more source

SECURE ASSOCIATION RULE MINING ON VERTICALLY PARTITIONED DATA USING FULLY HOMOMORPHIC ENCRYPTION

ICTACT Journal on Soft Computing, 2021
Cloud Computing is a leading innovation technology that guides to access applications over the web. The data owner’s data can be gotten to and controlled in the cloud.
M Yogasini, B N Prathibha
doaj   +1 more source

A Hybrid Approach for Mining Frequent Itemsets [PDF]

2013 IEEE International Conference on Systems, Man, and Cybernetics, 2013
Frequent item set mining is a fundamental element with respect to many data mining problems. Recently, the PrePost algorithm has been proposed, a new algorithm for mining frequent item sets based on the idea of N-lists. PrePost in most cases outperforms other current state-of-the-art algorithms.
Bay Vo, Frans Coenen, Tuong Le, Tzung-Pei Hong   +3 more
openaire   +1 more source

Right-Hand Side Expanding Algorithm for Maximal Frequent Itemset Mining

Applied Sciences, 2021
When it comes to association rule mining, all frequent itemsets are first found, and then the confidence level of association rules is calculated through the support degree of frequent itemsets.
Yalong Zhang, Wei Yu, Qiuqin Zhu, Xuan Ma, Hisakazu Ogura   +4 more
doaj   +1 more source

Personalized and Explainable Aspect‐Based Recommendation Using Latent Opinion Groups

Computational Intelligence, Volume 42, Issue 2, April 2026.
ABSTRACT The problem of explainable recommendation—supporting the recommendation of a product or service with an explanation of why the item is a good choice for the user—is attracting substantial research attention recently. Recommendations associated with an explanation of how the aspects of the chosen item may meet the needs and preferences of the ...
Maryam Mirzaei, Jörg Sander, Eleni Stroulia   +2 more
wiley   +1 more source

Critical Review for One‐Class Classification: Recent Advances and Reality Behind Them

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 1, March 2026.
This review presents a new taxonomy to summarize one‐class classification (OCC) algorithms and their applications. The main argument is that OCC should not learn multiple classes. The paper highlights common violations of OCC involving multiple classes.
Toshitaka Hayashi, Dalibor Cimr, Hamido Fujita, Richard Cimler   +3 more
wiley   +1 more source

Behavior Decoding Delineates Seizure Microfeatures and Associated Sudden Death Risks in Mouse Models of Epilepsy

Annals of Neurology, Volume 99, Issue 1, Page 231-247, January 2026.
Objective Behavior and motor manifestations are distinctive yet often overlooked features of epileptic seizures. Seizures can result in transient disruptions in motor control, often organized into specific behavioral sequences that can inform seizure types, onset zones, and outcomes.
Yuyan Shen, Jaden Thomas, Xianhui Chen, Jaden Zelidon, Mariam Najeeb, Abigayle Hahn, Ping Zhang, Aaron Sathyanesan, Bin Gu   +8 more
wiley   +1 more source

A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM

IEEE Access
Frequent itemset mining (FIM) and high utility itemset mining (HUIM) are popular data mining techniques used in various real-world applications such as retail-market, bio-medicine, and click-stream analysis.
Muhammad Waheed Ashraf, M. Asif Naeem, Heejeong Jasmine Lee   +2 more
doaj   +1 more source

Global Copper Deposit Dataset: A New Open‐Source Database for Advanced Data Analysis and Exploration Targeting

Geoscience Data Journal, Volume 13, Issue 1, January 2026.
We build a new, open‐source global copper deposit dataset (GCDD), facilitating AI‐driven data analysis for exploration targeting and improving our understanding of copper mineralizing systems and their mappable expressions. The GCDD hosts information about 1483 copper deposits worldwide, capturing key deposit attributes such as location, genetic type ...
Bin Wang, Renguang Zuo, Oliver P. Kreuzer   +2 more
wiley   +1 more source