The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.
Data mining is the process of discovering patterns, correlations, and anomalies in large datasets using methods drawn from statistics, machine learning, and database systems. Core techniques include classification, clustering, association rule mining, regression, and anomaly detection, applied to structured data in relational databases, semi-structured data such as logs and JSON, and increasingly unstructured data such as text and images. A typical workflow involves data cleaning and preprocessing, feature selection or extraction, model application, and validation against held-out data to avoid overfitting. With global data volume estimated to approach 221 zettabytes by 2026 according to industry forecasts, scaling mining algorithms to high-volume, high-dimensional data has become a central research concern. Data mining underlies applications including market basket analysis, customer segmentation, credit risk scoring, predictive maintenance, and scientific data analysis in genomics and astronomy. As an open-access data mining journal, IJACSA covers novel algorithms, comparative performance studies, and domain-specific applications across business, healthcare, and engineering datasets.
Published in International Journal of Advanced Computer Science and Applications (IJACSA) · list last refreshed September 2026
Database and database systems have been used widely in almost, all life activities. Sometimes missed data items are discovered as missed or null values in the database tables. The presented paper proposes a design for a…
Data Mining is the extraction of knowledge from the large databases. Data Mining had affected all the fields from combating terror attacks to the human genome databases. For different data analysis, R programming has a k…
In the fast growing information era utility of technology are more precise than completing the assignment manually. The digital information technology creates a knowledge-based society with high-tech global economy which…
The main idea of the current work is to use a wireless Electroencephalography (EEG) headset as a remote control for the mouse cursor of a personal computer. The proposed system uses EEG signals as a communication link be…
Positive and negative association rules are important to find useful information hidden in large datasets, especially negative association rules can reflect mutually exclusive correlation among items. Association rule mi…
the adverse effects of electromagnetic radiation from mobile phones and communication towers on health issues are being well documented today. However, exact correlation between radiation of communication towers and thei…
The challenges of the standard clustering methods and the weaknesses of Apriori algorithm in frequent termset clustering formulate the goal of our research. Based on Association Rules Mining, an efficient approach for We…
Online mining of data streams poses many new challenges more than mining static databases. In addition to the one-scan nature, the unbounded memory requirement, the high data arrival rate of data streams and the combinat…
Pollutant forecasting is an important problem in the environmental sciences. Data mining is an approach to discover knowledge from large data. This paper tries to use data mining methods to forecast ?PM?_(2.5) concentrat…
Most of the existing classification techniques concentrate on learning the datasets as a single similar unit, in spite of so many differentiating attributes and complexities involved. However, traditional classification…
