Journal Name: International Journal of Machine Learning and Engineering
Short Name: IJMLE
ISSN Print: 3136-8808
ISSN Online: 3136-8816
Frequency: Tri-Annually
Name of Publisher: Lyndon & Francis Publishing Group
Archiving Policy
The International Journal of Machine Learning and Engineering (IJMLE) is committed to ensuring the long-term preservation and accessibility of the articles it publishes. To ensure the continued availability of the journal’s content, the following archiving practices are in place:
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Open Access: All articles published in IJMLE are available to readers freely and openly upon publication, allowing for wide distribution and usage.
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Digital Preservation: IJMLE partners with reputable digital archiving services, such as CLOCKSS, PKP Preservation Network (PN), and Portico, to ensure the long-term digital preservation of its content. This guarantees that all published material remains accessible even if the journal's website or hosting infrastructure faces disruption.
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Public Access Repositories: Authors are encouraged to deposit their articles in institutional repositories or subject-specific repositories, such as arXiv, SSRN, and other publicly accessible databases, in accordance with open access and self-archiving policies.
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Backup and Security: The journal maintains regular backups of all published content, stored in secure, geographically diverse locations to prevent data loss and to ensure continuity in case of technical issues.
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DOI Registration: Each article published in IJMLE is assigned a unique Digital Object Identifier (DOI), which ensures permanent citation and retrieval of the content. These DOIs are registered with Crossref, a trusted DOI registration agency, ensuring long-term discoverability.
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Content Retention: All articles are retained in their original form on the journal’s platform for ongoing access by readers. Older issues are also preserved in the archive section of the journal’s website, which is continuously maintained and updated.
