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
In recent years, computational linguistic methods have been widely used in different literary studies where they have been proved useful in breaking into the mainstream of literary critical scholarship as well as in addr…
Educational Data Mining has been implemented in predicting student final grade in Indonesia. It can be used to improve learning efficiency by paying more attention to students who are predicted to have low scores, but in…
The advancement in Information Technology permits high volume of data to be generated in databases of institutions, organizations, government, including Law Enforcement Agencies (LEAs). Technologies have also been develo…
The importance of basic education is well noted in every country. Proper planning and utilization of resources at the basic level, helps in leveraging the success of education at all other levels of education in a countr…
Outlier detection over data streams is an important task in data mining. It has various applications such as fraud detection, public health, and computer network security. Many approaches have been proposed for outlier d…
Cancer is amongst the most challenging disorders to diagnose nowadays, and experts are still struggling to detect it on early stage. Gene selection is significant for identifying cancer-causing different parameters. The…
With the wide usage of World Wide Web (WWW) and social media platforms, fake news could become rampant among the users. They tend to create and share the news without knowing the authenticity of it. This would become the…
Cardiovascular Disease (CVD) is the foremost cause of death worldwide that generates a high percentage of Electronic Health Records (EHRs). Analyzing these complex patterns from EHRs is a tedious process. To address this…
The decision-making process, promptly on time, is a crucial success factor in large organizations. Generally, the data warehouses of these organizations grow rapidly with the data generated from various business activiti…
In recent years, the emergence of WWW (World Wide Web) led to the accumulation of huge amount of information and data. Hence the web is found to consist of unstructured and structured information that impacts the day to…
