Recent Advances in Data Mining: Methods, Trends, and Emerging Applications

Dear Collogues,

We are excited to invite you to contribute to this Special Issue, entitled ‘Recent Advances in Data Mining: Methods, Trends, and Emerging Applications’.

In recent years, data mining has emerged as a keystone of intelligent data analysis, enabling the discovery of hidden patterns, actionable insights, and predictive knowledge from massive and complex datasets. Powered by rapid progress in computing technologies, machine learning, big data infrastructure, and modern data mining techniques have found applications in a growing range of fields, including healthcare, finance, cybersecurity, social media, environmental sciences, and more.

This Special Issue aims to bring together the latest innovations, trends, challenges, and practical applications in the field of data mining. We invite high-quality contributions that explore new methodologies, theoretical frameworks, and real-world use-cases that highlight the transformative power of data mining in solving contemporary problems. Submissions may focus on algorithmic advances, novel applications, performance improvements, or interdisciplinary research integrating data mining with other emerging technologies such as cloud computing, edge AI, and blockchain.

We welcome original research articles, comprehensive review papers, and insightful case studies from academia and industry.

Topics of interest include, but are not limited to, the following:

• Novel data mining algorithms and frameworks;
• Data preprocessing and feature engineering techniques;
• Scalable and distributed data mining solutions;
• Mining structured, semi-structured, and unstructured data;
• Graph and network mining;
• Privacy-preserving data mining;
• Data mining in healthcare, finance, marketing, and cybersecurity;
• Temporal, spatial, and spatio-temporal data mining;
• Automated and interpretable data mining;
• Ethical and responsible data mining practices;
• Integration of data mining with AI, IoT, and cloud technologies;
• Emerging applications and interdisciplinary approaches;
• Pattern discovery in large-scale and unstructured data;
• Text mining and semantic analysis;
• Sentiment analysis and opinion mining.

Dr. Tehmina Amjad
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computers is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• data mining
• pattern discovery
• scalable algorithms
• privacy-preserving analytics
• feature selection
• graph mining
• real-world applications
• interpretability
• semantics analysis
• emerging trends