Results 61 to 70 of about 15,313,957 (171)
High Utility Itemsets Identification in Big Data
High utility itemset mining is an important data mining problem which considers profit factors besides quantity from the transactional database. It helps find the most valuable products/items that are difficult to track using only the frequent data ...
Tamrakar, Ashish
core +1 more source
A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases
Analyzing customer transactions to discover high-utility itemsets is a popular task, which consists of finding the sets of items that are purchased together and yield a high profit.
Bay Vo +4 more
doaj +1 more source
PUC: parallel mining of high-utility itemsets with load balancing on spark
Distributed programming paradigms such as MapReduce and Spark have alleviated sequential bottleneck while mining of massive transaction databases. Of significant importance is mining High Utility Itemset (HUI) that incorporates the revenue of the items ...
Brahmavar Anup Bhat +2 more
doaj +1 more source
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
High-utility Itemsets Mining Algorithm Based on Double Binary Particle Swarm Optimization [PDF]
High-utility itemset mining algorithm is an important part of association analysis.By improving the basic binary particle swarm optimization algorithm,a Double Binary Particle Swarm Optimization(DBPSO) algorithm is proposed.The minimum utility threshold ...
JIN Xiaole,LIU Xiabi,MA Xiao
doaj +1 more source
A Design‐Driven Machine Learning Approach for Invariant Mining in a Smart Grid
An ICS is vulnerable to cyber‐attacks arising from within its communication network or directly from the SCADA and devices such as PLCs. The study reported here presents a scenario‐specific invariant mining approach to detect anomalies in plant behaviour.
Danish Hudani +5 more
wiley +1 more source
Literature Review on Efficient Algorithms for Mining High Utility Itemsets from Transactional Databases [PDF]
This paper presenting a survey on finding itemsets with high utility. For finding itemsets there are many algorithms but those algorithms having a problem of producing a large number of candidate itemsets for high utility itemsets which reduces mining ...
, Ketkee Kailas Gaikwad, Mininath Nighot
core +1 more source
This paper presents a data‐driven framework for operational safety rule extraction and vulnerable node identification in power grids with high renewable penetration. The effectiveness of the proposed method is verified on the IEEE 39‐bus system for static security assessment. ABSTRACT High renewable energy penetration introduces significant uncertainty
Zhilin Huang +6 more
wiley +1 more source
ABSTRACT Urban bus accidents present major safety and operational challenges, particularly in densely populated metropolitan areas. This study develops a machine learning‐based analytical framework to identify, quantify, and interpret the factors associated with severe bus accidents.
Bowei Chen +3 more
wiley +1 more source
Using Multi-Conditional Minimum Thresholds in Temporal Fuzzy Utility Mining
In the field of fuzzy utility mining, the characteristics of transaction time have been a widely studied topic in data mining. However, using a single-conditional threshold for all items does not suffice to reflect the true properties of items.
Wei-Ming Huang +3 more
doaj +1 more source

