Forthcoming articles


International Journal of Knowledge Engineering and Data Mining


These articles have been peer-reviewed and accepted for publication in IJKEDM, but are pending final changes, are not yet published and may not appear here in their final order of publication until they are assigned to issues. Therefore, the content conforms to our standards but the presentation (e.g. typesetting and proof-reading) is not necessarily up to the Inderscience standard. Additionally, titles, authors, abstracts and keywords may change before publication. Articles will not be published until the final proofs are validated by their authors.


Forthcoming articles must be purchased for the purposes of research, teaching and private study only. These articles can be cited using the expression "in press". For example: Smith, J. (in press). Article Title. Journal Title.


Articles marked with this shopping trolley icon are available for purchase - click on the icon to send an email request to purchase.


Articles marked with this Open Access icon are freely available and openly accessible to all without any restriction except the ones stated in their respective CC licenses.


Register for our alerting service, which notifies you by email when new issues of IJKEDM are published online.


We also offer RSS feeds which provide timely updates of tables of contents, newly published articles and calls for papers.


International Journal of Knowledge Engineering and Data Mining (1 paper in press)


Regular Issues


  • Building an annotated corpus for Albanian using bilingual projections and regular expressions   Order a copy of this article
    by Arbana Kadriu 
    Abstract: We present research done on creating an annotated corpus for Albanian. This corpus is achieved combining unsupervised part-of-speech tagging using bilingual projections with regular expressions. Albanian-English text from a free parallel corpus for the Balkan languages is used as a basis. The annotating process is based on the universal part-of-speech tag system. As the result of the projected tagging, we gained a tagged corpus in Albanian for 60,000 sentences. We investigate the main pitfalls in the output gained from the parallel projection and use this analysis to define replacement rules for part of our tagged corpus, which will change 18% of the initial text. We investigate the effectiveness of the tagged corpus using four different part-of-speech taggers, the best result of which is of 94% accuracy. We discuss further improvements to this corpus, which to our knowledge is the biggest annotated corpus in Albanian.
    Keywords: POS tagging; Albanian language; bilingual projection; corpus creation.
    DOI: 10.1504/IJKEDM.2019.10020367