Results 61 to 70 of about 846,186 (212)
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 +2 more
wiley +1 more source
Frequent Itemset Mining for Big Data Using Greatest Common Divisor Technique
Data Science Journal, 2017 The discovery of frequent itemsets is one of the very important topics in data mining. Frequent itemset discovery techniques help in generating qualitative knowledge which gives business insight and helps the decision makers. In the Big Data era the need
Mohamed A. Gawwad +2 more
doaj +1 more source
Hiding co-occurring frequent itemsets [PDF]
Proceedings of the 2009 EDBT/ICDT Workshops, 2009 Knowledge hiding, hiding rules/patterns that are inferable from published data and attributed sensitive, is extensively studied in the literature in the context of frequent itemsets and association rules mining from transactional data. The research in this thread is focused mainly on developing sophisticated methods that achieve less distortion in data
openaire +3 more sources
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 +3 more
wiley +1 more source
Video Mining with Frequent Itemset Configurations [PDF]
, 2006 We present a method for mining frequently occurring objects and scenes from videos. Object candidates are detected by finding recurring spatial arrangements of affine covariant regions. Our mining method is based on the class of frequent itemset mining algorithms, which have proven their efficiency in other domains, but have not been applied to video ...
Quack, Till +2 more
openaire +1 more source
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 +8 more
wiley +1 more source
Accelerating Parallel Frequent Itemset Mining on Graphics Processors with Sorting
, 2013 Part 4: Session 4: Multi-core Computing and GPUInternational audienceFrequent Itemset Mining (FIM) is one of the most investigated fields of data mining.
Hsu, Ching-Hsien +9 more
core +1 more source
weighted frequent itemset algorithm based on dynamic itemset counting
, 2012 The existing weighted frequent itemset mining algorithms which are based on Apriori require multiple dataset scans.This paper proposes a weighted frequent itemset algorithm weighted frequent itemset mining based on dynamic itemset counting ...
罗雄飞, 秦丽君
core +1 more source
JUTI: Jurnal Ilmiah Teknologi Informasi, 2002 Data transaksi tiruan yang menyerupai transaksi nyata pada lingkungan ritel dibutuhkan dalam pengetesan teknik data mining untuk pencarian pola asosiasi dan pola sekuensial dari basis data berskala besar.
Arif Djunaidy +2 more
doaj +1 more source
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 +2 more
wiley +1 more source