• Aug 11, 2015 News!IJMLC Vol.5, No.5 has been published with online version.The topics cover the following 3 specific scientific areas, namely, Computer Information Technology, Machine Learning and Pattern Recognition, and Visual Information Processing and Visualization.   [Click]
  • Apr 01, 2015 News!Vol.4, No.2 has been indexed by EI(Inspec)!   [Click]
  • Sep 16, 2015 News!The papers published in Vol.5, No.5 have all received dois from Crossref.
General Information
    • ISSN: 2010-3700
    • Frequency: Bimonthly
    • DOI: 10.18178/IJMLC
    • Editor-in-Chief: Dr. Lin Huang
    • Executive Editor:  Ms. Cherry L. Chen
    • Abstracing/Indexing: Engineering & Technology Digital Library, Google Scholar, Crossref, ProQuest, Electronic Journals Library, DOAJ and EI (INSPEC, IET).
    • E-mail: ijmlc@ejournal.net
Dr. Lin Huang
Metropolitan State University of Denver, USA
It's my honor to take on the position of editor in chief of IJMLC. We encourage authors to submit papers concerning any branch of machine learning and computing.

International Journal of Machine Learning and Computing (IJMLC) is an international academic open access journal which gains a foothold in Singapore, Asia and opens to the world. It aims to promote the integration of machine learning and computing. The focus is to publish papers on state-of-the-art machine learning and computing. Submitted papers will be reviewed by technical committees of the Journal and Association. The audience includes researchers, managers and operators for machine learning and computing as well as designers and developers.

All submitted articles should report original, previously unpublished research results, experimental or theoretical, and will be peer-reviewed. Articles submitted to the journal should meet these criteria and must not be under consideration for publication elsewhere. Manuscripts should follow the style of the journal and are subject to both review and editing.

Featured Article
Integrating Product Association Rules and Customer Moving Sequential Patterns for Product-to-Shelf Optimization
Chieh-Yuan Tsai and Sheng-Hsiang Huang
Volume 5, Number 5, pp. 344-352
Previous studies in product-to-shelf assignment area usually applied the space elasticity to optimize product assortment and space allocation models. However, a well product-to-shelf assignment strategy should not only consider product assortment and space elasticity. Thus, this study develops a data mining method for solving the product-to-shelf assignment problem ....[Read More]
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