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 October 2026
With the emergence of digital newspapers and social media, one can easily suffer from information overload. The enormous amount of data they provide has created several new challenges for computational and data mining, e…
In Benin, after the GCSE (General Certificate of Secondary Education), learners can either enroll in a Technical and Vocational Education and Training (TVET), or further their studies in the general education. Majority o…
Slope stability has been a matter of concern for most geologists, mainly due to the fact that unstable slopes cause a greater number of accidents, which in turn reduces efficiency of mining operations. In order to reduce…
Among the educational data mining problems, the early prediction of the students' academic performance is the most important task, so that timely and requisite support may be provided to the needy students. Machine learn…
The Internet of Things (IoT) enable the IoT to sense and respond using the power of computing to autonomously come up with the best solutions for any industry today. However, Internet of Things have vulnerabilities since…
Student scores in TOEFL IBT reading, listening, and writing may reveal weaknesses and deficiencies in educational institutions. Traditional approaches and evaluations are unable to disclose the significant information hi…
In education sector, personalization is an evolutionary term that gained a high attention due to its effectiveness in raising the enterprise competence level. This research aims at proposing a novel model for effective s…
Heart diseases are considered one of the leading causes of death globally over the world. They are difficult to be predicted by a specialist physician as it is not an easy task which requires greater knowledge and expert…
Ever since the era of internet had ushered in cloud computing, there had been increase in the demand for the unlimited data available through cloud computing for data analysis, pattern recognition and technology advancem…
In a distributed storage and computing framework, traditional streaming data mining techniques are inefficient when processing massive amounts of data. In this paper, we take the copy in cloud storage as an allocatable r…
