Results 61 to 70 of about 2,811 (218)
Implementasl Algoritma Charm-L Dalam Menggali Frequent Closed Itemset [PDF]
, 2006 Himpunan Frequent Closed Itetnset Dapat Digunakan Untuk Mengeta.Hui Support Dari Semua Frequent Itemset Secara Tepat, Dan Jumlabnya Jebih Sedikit Daripada Jmnlah Frequent Itemset Yang Ditemukan Pada Minimum Support Yang Sama Algoritma CHARM-L ...
Kurniawati, Yenny
core
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
Journal of Advanced Transportation, Volume 2026, Issue 1, 2026.The purpose of this study was to explore the risk factors for autonomous vehicle (AV) crashes and their interdependencies. A total of 659 AV crash data were collected between 2018 and July 2024 from AV crash reports published by the California Department of Motor Vehicles.
Tao Wang +4 more
wiley +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
Identifying the Focus Word in Natural Language Questions Based on Association Rules
International Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.Knowledge base‐based intelligent question‐answering systems have insufficient understanding of the questions. In the early stages of research, it is effective in most cases that the existing natural language question‐understanding methods can answer questions by connecting entities and relationships when ignoring the identification of focus words ...
Xin Hu +5 more
wiley +1 more source
Class Association Rule Pada Metode Associative Classification
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2011 Frequent patterns (itemsets) discovery is an important problem in associative classification rule mining. Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP)-growth, and Transaction Data Location (Tid)-list ...
Eka Karyawati, Edi Winarko
doaj +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
Frequent Itemset Generation using Double Hashing Technique
, 2012 In data mining, frequent itemsets plays an important role which is used to identify the correlations among the fields of database.In this paper, we propose a new association rule mining algorithm called Double Hashing Based Frequent Itemsets, (DHBFI) in ...
Krishnamurthy, M. +3 more
core +1 more source
Computational Intelligence, Volume 41, Issue 4, August 2025.ABSTRACT Machine learning techniques are increasingly used for high‐stakes decision‐making, such as college admissions, loan attribution, or recidivism prediction. Thus, it is crucial to ensure that the models learnt can be audited or understood by human users, do not create or reproduce discrimination or bias and do not leak sensitive information ...
Julien Ferry +4 more
wiley +1 more source
Content Validity of Creativity Self‐Report Questionnaires From PISA 2022
The Journal of Creative Behavior, Volume 59, Issue 2, June 2025.ABSTRACT The present paper questions the content validity of the eight creativity‐related self‐report scales available in PISA 2022's context questionnaire and provides a set of considerations for researchers interested in using these indexes. Specifically, we point out some threats to the content validity of these scales (e.g., creative thinking self ...
B. Goecke, S. Weiss, B. Barbot
wiley +1 more source