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
This article explores data mining techniques in health care. In particular, it discusses data mining and its application in areas where people are affected severely by using the under- ground drinking water which consist…
The technology of automatic document summarization is maturing and may provide a solution to the information overload problem. Nowadays, document summarization plays an important role in information retrieval. With a lar…
In today’s world, healthcare is the most important factor affecting human life. Due to heavy work load it is not possible for personal healthcare. The proposed system acts as a preventive measure for determining whether…
Data mining and multiagent approach has been used successfully in the development of large complex systems. Agents are used to perform some action or activity on behalf of a user of a computer system. The study proposes…
Summary: Several papers have been published about the prediction of hepatitis C virus (HCV) polyprotein cleavage sites, using symbolic and non-symbolic machine learning techniques. The published papers achieved different…
Past observations have shown that a frequent item set mining algorithm are purported to mine the closed ones because the finish provides a compact and a whole progress set and higher potency. Anyhow, the newest closed it…
The clustering or partitioning of a dataset’s records into groups of similar records is an important aspect of knowledge discovery from datasets. A considerable amount of research has been applied to the identification o…
the supervision of the academic performance of engineering students is vital during an early stage of their curricula. Indeed, their grades in specific core/major courses as well as their cumulative General Point Average…
Few years ago, the information flow in health care field was relatively simple and the application of technology was limited. However, as we progress into a more integrated world where technology has become an integral p…
This paper presents the results of a study carried out to identify the factors that influence the further education desires of Sri Lankan youth. Statistical modeling has been initially used to infer the desires of the yo…
