Journal of Data Analysis and Information Processing


Journal of Data Analysis and Information Processing (JDAIP) is an international journal dedicated to the latest advancement of data analysis and information processing methods. The goal of this journal is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in different areas of data analysis and information processing.

All manuscripts must be prepared in English and are subject to a rigorous and fair peer-review process. Generally, accepted papers will appear online within 3 weeks followed by printed hard copy. The journal publishes original papers including but not limited to the following fields:

· Application of Technology in Policy and Decision Making · Application of Technology in Teaching and Learning Process · Artificial Intelligence · Artificial Neural Networks · Big Data Analytic · Business Intelligence · Computational Intelligence · Data Mining · Data Modeling · Deep Learning · Digital Signal Processing · Dimension Reducing · Empirical Mode Decomposition · Fourier Analysis · Graph Mining · Image Processing, Video Processing · Information Extraction · Information Hiding · Information Retrieval · Information Theory · Knowledge Discovery · Machine Learning · Multivariate data analysis, Matrix Analysis · Pattern Recognition · Semantic Technology · Social Network Mining · Spatial and Temporal Data Analysis · Statistics · Statistics and Applied Probability · Stochastic Process · Stream Mining · Time Series Analysis · Wavelet Analysis

We are also interested in:

1) Short reports—2-5 page papers where an author can present an idea with theoretical background, but has not yet completed the research needed for a complete paper or an author presents preliminary data;

2) Short communications—2-5 page papers;

3) Technical notes—2-5 page papers;

4) Letters to the Editor;

5) Reviews (the number of pages is not restricted), Book reviews—Comments and critiques;

6) Advertisement.

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