Results 61 to 70 of about 2,690 (229)
Health Science Reports, Volume 8, Issue 1, January 2025.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
DiffNodesets: An efficient structure for fast mining frequent itemsets
, 2016 Mining frequent itemsets is an essential problem in data mining and plays an important role in many data mining applications. In recent years, some itemset representations based on node sets have been proposed, which have shown to be very efficient for ...
Deng, Zhi-Hong
core +1 more source
International Journal of Computational Intelligence SystemsIn the process of data extraction, the rigid partitioning mechanism of fixed time windows leads to spatiotemporal heterogeneity mismatches in data distribution, resulting in semantic confusion and redundancy accumulation in mining results. To address the
Jie Zhang +3 more
doaj +1 more source
Negative and Positive Association Rules Mining from Text Using Frequent and Infrequent Itemsets
The 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
IET 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
Taxonomy-Based Pruning in Generalized Frequent Itemsets Mining [PDF]
, 2012 The original purpose of data mining is for analysis of supermarket transaction data. Now with the rapid development in business, industry and science, data mining is used in lots of domains, so mining interesting information from large database becomes ...
Ma, LinLin
core
Mining Frequent Itemsets in Correlated Uncertain Databases
, 2015 Recently, with the growing popularity of Internet of Things (IoT) and pervasive computing, a large amount of uncertain data, e.g., RFID data, sensor data, real-time video data, has been collected.
Chen, Lei, Tong, Yong Xin, She, Jieying
core +1 more source
An AI knowledge‐based system for police assistance in crime investigation
Expert 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
Mining frequent itemsets in a stream, in: [PDF]
, 2007 Mining frequent itemsets in a datastream proves to be a difficult problem, as itemsets arrive in rapid succession and storing parts of the stream is typically impossible. Nonetheless, it has many useful applications; e.g.
Joris J M Gillis +3 more
core
Frequent Itemsets Mining with Chemical Reaction Optimization Metaheuristic
, 2018 International audienceFrequent Itemsets mining is a key concept in Association Rule Mining task, it aims to discover the frequent itemsets in a transactional dataset.Nowadays large amounts of data needs to be analysed, thus the use of traditional ...
Abdesslem Layeb +5 more
core +1 more source