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Semantic Spectral Clustering with Contrastive Learning and Neighbor Mining
Deep spectral clustering techniques are considered one of the most efficient clustering algorithms in data mining field. The similarity between...
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Privacy-preserving data (stream) mining techniques and their impact on data mining accuracy: a systematic literature review
This study investigates existing input privacy-preserving data mining (PPDM) methods and privacy-preserving data stream mining methods (PPDSM),...
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An Efficient Framework for Web Content Mining Systems Using Improved CD-PAM Clustering and the A-CNN Technique
The World Wide Web's expansion (WWW) has made finding appropriate information difficult, and web classification has emerged as an alternative...
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Clustering customer orders in a smart factory using sequential pattern mining
In a smart factory, setting a production plan, relocating production equipment, and producing small batches of various products in real-time at a low...
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Split incremental clustering algorithm of mixed data stream
Clustering has been recognized as one of the most prominent functions in data mining. It aims to partition a given set of elements into homogeneous...
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A smart intelligent approach based on hybrid group search and pelican optimization algorithm for data stream clustering
Big data applications generate a huge range of evolving, real-time, and high-dimensional streaming data. In many applications, data stream clustering...
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Clustering from Data Streams
Clustering is one of the most popular data mining techniques. In this article, we review the relevant methods and algorithms for designing cluster...
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Data clustering: application and trends
Clustering has primarily been used as an analytical technique to group unlabeled data for extracting meaningful information. The fact that no...
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Frequent item-set mining and clustering based ranked biomedical text summarization
The difficulty of deriving value out of vast available scientific literature in a condensed form lead us to look for a proficient theme based...
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A Survey and Experimental Review on Data Distribution Strategies for Parallel Spatial Clustering Algorithms
The advent of Big Data has led to the rapid growth in the usage of parallel clustering algorithms that work over distributed computing frameworks...
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Excel and Data Mining
Let’s get right to the topic. Why do we need to learn Excel in our data mining endeavor? It is true that there are some outstanding data mining...
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Student assessment in cybersecurity training automated by pattern mining and clustering
Hands-on cybersecurity training allows students and professionals to practice various tools and improve their technical skills. The training occurs...
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Data Clustering Mining Method of Social Network Talent Recruitment Stream Based on MST Algorithm
In order to solve the problem that the data clustering mining method of social network talent recruitment stream is affected by the score of graph...
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Maxmin distance sort heuristic-based initial centroid method of partitional clustering for big data mining
The revolution of digital and communication technologies is producing an enormous amount of data. Therefore, the nature of classical data changes...
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Image-based random rotation for preserving the data in data mining process
The privacy and security of big data have become a major concern in recent years, necessitating privacy-preserving data mining strategies to preserve...
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Privacy-Preserving Data Mining
The growth of data mining has raised concerns among privacy advocates. Some of this is based on a misunderstanding of what data mining does. The...
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Evaluation of Chemical Data by Clustering Techniques
Obtaining more useful information by applying mathematical techniques from chemical data obtained by different methods can be defined as chemometry....
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Examining students’ course trajectories using data mining and visualization approaches
The heterogeneous data acquired by educational institutes about students’ careers (e.g., performance scores, course preferences, attendance record,...
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An optimized SVM-RFE based feature selection and weighted entropy K-means approach for big data clustering in mapreduce
In the digitalized world, efficient big data clustering is necessary for massive data generation. The clustering algorithm plays an important role in...
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Efficient Clustering on Encrypted Data
Clustering is a significant unsupervised machine learning task widely used for data mining and analysis. Fully homomorphic encryption allows data...