Results 71 to 80 of about 9,218 (205)

Efficient Discovery of Association Rules and Frequent Itemsets through Sampling with Tight Performance Guarantees [PDF]

open access: yes, 2013
The tasks of extracting (top-$K$) Frequent Itemsets (FI's) and Association Rules (AR's) are fundamental primitives in data mining and database applications. Exact algorithms for these problems exist and are widely used, but their running time is hindered
Riondato, Matteo, Upfal, Eli
core  

A multi‐agent K‐means with case‐based reasoning for an automated quality assessment of software requirement specification

open access: yesIET Communications, Volume 19, Issue 1, January/December 2025.
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

Privacy Preserving Utility Mining: A Survey

open access: yes, 2018
In big data era, the collected data usually contains rich information and hidden knowledge. Utility-oriented pattern mining and analytics have shown a powerful ability to explore these ubiquitous data, which may be collected from various fields and ...
Chao, Han-Chieh   +4 more
core   +1 more source

An AI knowledge‐based system for police assistance in crime investigation

open access: yesExpert Systems, Volume 42, Issue 1, January 2025.
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

ENHANCED ALGORITHMS FOR MINING OPTIMIZED POSITIVE AND NEGATIVE ASSOCIATION RULE FROM CANCER DATASET

open access: yesICTACT Journal on Soft Computing, 2018
The most important research aspect nowadays is the data. Association rule mining is vital mining used in data which mines many eventual informations and associations from enormous databases.
I Berin Jeba Jingle, J Jeya ACelin
doaj   +1 more source

Research on Risk Identification of Coal Mine Ventilation Systems Based on HFACS and Apriori Algorithm

open access: yesAdvances in Civil Engineering, Volume 2025, Issue 1, 2025.
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

Unveiling Success Drivers in Gaming: A Machine Learning Study Across Steam, Twitch, and Metacritic

open access: yesInternational Journal of Computer Games Technology, Volume 2025, Issue 1, 2025.
This study employs machine learning to assess the relative impact of major platforms—Steam, Twitch, and Metacritic—on video game revenue. Through an integrated analysis of three comprehensive datasets comprising commercially successful titles on Steam, key predictors of financial performance were identified.
Jiesi Ma, Michael J. Katchabaw
wiley   +1 more source

Negative and Positive Association Rules Mining from Text Using Frequent and Infrequent Itemsets

open access: yesThe Scientific World Journal, 2014
Association rule mining research typically focuses on positive association rules (PARs), generated from frequently occurring itemsets. However, in recent years, there has been a significant research focused on finding interesting infrequent itemsets ...
Sajid Mahmood   +2 more
doaj   +1 more source

arules - A Computational Environment for Mining Association Rules and Frequent Item Sets [PDF]

open access: yes
Mining frequent itemsets and association rules is a popular and well researched approach for discovering interesting relationships between variables in large databases.
Bettina Grün   +2 more
core   +1 more source

Enhancing Interpretability: A Hierarchical Belief Rule‐Based (HBRB) Method for Assessing Multimodal Social Media Credibility

open access: yesInternational Journal of Intelligent Systems, Volume 2025, Issue 1, 2025.
User and artificial intelligence generated contents, coupled with the multimodal nature of information, have made the identification of false news an arduous task. While models can assist users in improving their cognitive abilities, commonly used black‐box models lack transparency, posing a significant challenge for interpretability.
Peng Wu   +4 more
wiley   +1 more source

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