Special section on mining knowledge from scientific data

Guest Editorial: Special Section on Music Data Mining

M USIC has been an important application area for data mining and machine learning techniques for many years. Music data mining is an interdisciplinary area that studies computational methods for understanding and delivering music data and is a topic of growing importance with large commercial relevance and substantial potential. It attracts researchers not only from computer science, electrica...

Effective Data Mining Using Neural Network [Concise Papers in the Special Section] - Knowledge and Data Engineering, IEEE Transactions on

Classification is one of the data mining problems receiving great attention recently in the database community. This paper presents an approach to discover symbolic classification rules using neural networks. Neural networks have not been thought suited for data mining because how the classifications were made is not explicitly stated as symbolic rules that are suitable for verification or inte...

Special Section on Knowledge-Based Software Engineering

The Institute of Electronics, Information and Communication Engineering (IEICE) Transactions on Information and Systems announces a forthcoming special section on “Knowledge-Based Software Engineering” to be published in July 2018. The objective of this special section is to publish and overview recent progress in the interdisciplinary area of Artificial Intelligence and Software Engineering. B...

Special Track on Data Mining

Data mining is the process of extracting hidden patterns from data. With data ever increasing in volume, its mining into usable information is becoming increasingly important. Data mining approaches are commonly used in a wide range of profiling services, including marketing, fraud detection, and scientific discovery. e FLAIRS Data Mining special track is devoted to data mining with the aim of...

Guest Editorial: Special Section on Enabling Technologies and Methodologies for Knowledge Discovery and Data Mining in Smart Grids