BEST: International Journal of Algorithmic Data Science and Knowledge Discovery (BEST: IJADSKD) publishes peer-reviewed scientific papers for advancing the theory and applications of algorithms in data science and the process of discovering knowledge from data. The scope of the journal includes Algorithm Development, Knowledge Discovery, Applications, Big Data and Interdisciplinary Research. The journal is designed for academics, scholars, scientists, research scholars, industry practitioners, and advanced students. 


Types of paper 

Regular articles: These should describe new, carefully confirmed findings, innovative & creative research ideas, and experimental procedures that should be given in sufficient detail for others to verify the work. The length of a full paper should be the minimum required to describe and interpret the work clearly.

Short communications: A short communication is suitable for recording the results of complete small investigations or giving details of new models or hypotheses, innovative methods, techniques, creative models, etc. The style of main sections need not conform to that of full-length papers. Short communications are 2 to 4 printed pages (about 6 to 12 manuscript pages) in length.

Reviews: Submissions of reviews and perspectives covering topics of current interest are welcome and encouraged. Reviews should be concise and no longer than 4-6 printed pages (about 12 to 18 manuscript pages). Review manuscripts are also peer-reviewed.

Publication Frequency: 2 issues per year. Submission: Authors are requested to submit their papers electronically through the website, both in the Word document. 

Abstracting and Indexing:

Abstracted and indexed in many of the major global databases including Mendeley, Google Scholar, Issuu, ResearchBib, Citefactor, and Intexcopernicus.