Results 71 to 80 of about 905 (211)
Mining High Utility Itemsets Based on Pattern Growth without Candidate Generation
Mining high utility itemsets (HUIs) has been an active research topic in data mining in recent years. Existing HUI mining algorithms typically take two steps: generating candidates and identifying utility values of these candidate itemsets.
Yiwei Liu, Le Wang, Lin Feng, Bo Jin
doaj +1 more source
Abstract Predicting the future health state of a transformer can offer early warning of latent defects and faults within the transformer, thereby facilitating the formulation of power outage maintenance plans and power dispatch strategies. However, existing prediction methods based on the structure of ‘splicing prediction and diagnosis method’ suffer ...
Peng Zhang +5 more
wiley +1 more source
ABSTRACT Background and Aims Infertility, as defined by the World Health Organization, is the inability to conceive after 12 months of regular, unprotected intercourse. This study aimed to identify factors influencing infertility by applying data mining techniques, specifically rule‐mining methods, to analyze diverse patient data and uncover relevant ...
Hosna Heydarian +3 more
wiley +1 more source
High Utility Itemset Mining by Using Binary PSO Algorithm
The goal of pattern mining is to find some novel patterns from a given database. High utility itemset mining (HUIM) is a research direction of the pattern mining as a sub-domain of data mining.
TAO BODONG
core
This paper proposed an Automated Quality Assessment of SRS (AQA‐SRS) framework by integrating four popular methods which are; NLP, K‐means, MAS, and CBR to assess the quality of SRS documents. The NLP utilize for feature extraction, K‐means for features clustering, MAS for interactive assessment and feature selection decision, and CBR for managing the ...
Mohammed Ahmed Jubair +6 more
wiley +1 more source
Mining actionable combined high utility incremental and associated patterns
© 2016 IEEE. High Utility Itemsets(HUI) Mining, instead of Frequent Pattern Mining (FIM), has been an attractive theme in data mining domain for over a decade since it can be regarded as an alternative way for researchers to identify actionable patterns.
Jingyu Shao +5 more
core +1 more source
An AI knowledge‐based system for police assistance in crime investigation
Abstract The fight against crime is often an arduous task overall when huge amounts of data have to be inspected, as is currently the case when it comes for example in the detection of criminal activity on the dark web. This work presents and describes an artificial intelligence (AI) based system that combines various tools to assist police or law ...
Carlos Fernandez‐Basso +4 more
wiley +1 more source
Pencarian High Utility Itemset pada Dataset YooChoose Buys
Abstrak. Perkembangan e-commerce yang pesat, membuat strategi penjualan harus dioptimalkan untuk meningkatkan keuntungan bisnis. Dalam upaya untuk meningkatkan keuntungan, penting untuk mengidentifikasi pola pembelian pelanggan yang dapat memberikan ...
Gunawan, Ridowati, Nugroho, Rangga
core +1 more source
Optimization of High Utility Itemset Mining from Large Transaction Databases on multi core processor
High utility itemset mining is an emerging era that extends frequent itemset mining to identify itemsets in a transaction database with utility values associated with every item above a given threshold.
, Ms. Yogita S. Khot, Prof. Mrs. Manasi K. Kulkarni
core +1 more source
The coal industry has always been a typically high‐risk industry with frequent accidents and extremely adverse impacts. Cases of accidents in coal mine ventilation systems serve as a concentrated demonstration of accident hazards and hold significant value for identifying key risk factors that may induce disasters in coal mine ventilation systems. This
Mingjia Jing +4 more
wiley +1 more source

