International
Journal of Hidden Data Mining and Scientific Knowledge Discovery Free (NO PUBLICATION FEES).
.07 | Seventh Year: Volume 07, Issue 01, 2022
completing the Seventh volume
Hidden data represents data or information that is more or less
hidden, unseen or encrypted so that it becomes difficult to extract it.
Scientific knowledge represents every information that comes by a
scientific way, such as theories, experimental observations or
scientific evidences of some phenomenon. The last term in the journal
title, namely "Discovery" has a great importance, since it means that
we are looking for scientific information particularly and hidden data
in general.
Authors are encouraged to submit their latest research results to
the HDSKD journal
Hence, we are proud to announce the opening of our fifth journal
issue in hidden data mining and scientific knowledge discovery and
encourage authors to submit their latest research results to HDSKD.
The criteria of selection are based on the review decision, which will
lead to the acceptance or the reject of the paper.
The readers are welcome too and can read, download the papers for a
scientific or academic purpose. The journal is a non-profit academic
source of knowledge and does not permit any commercial use of the
articles.
Call for Submission
Scope & Topics
.07 | FortHcoming
issues
Research felds
The journal welcomes all submissions in the domain of hidden data
mining and scientific knowledge discovery or related fields. Please
send your paper in pdf or word to the official email address of the
journal: editor.hdskd@gmail.com.Original & Unpublished research works
in all domains of HDSKD are wellcome
The following research fields are accepted for submission:
Hidden data, Encryption, Waterarking, Datamining, Text mining,
Information Retrieval, Knowledge discovery, Biometrics, Speaker
recognition, Face recognition, Stylomery, Religious documents analysis,
Scientific evidences in religious documents, Hidden signal processing,
Hidden computational linguitics, Scentific evidences analysis.
Journal Indexing Databases:


