Forthcoming articles

International Journal of Knowledge Engineering and Data Mining

International Journal of Knowledge Engineering and Data Mining (IJKEDM)

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International Journal of Knowledge Engineering and Data Mining (2 papers 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
    Abstract: Tiko is known for its fertile azonal soils of volcanic and fluvial origin that supports the growth of banana, palm and rubber by agro-base corporations. Being a low lying region, Tiko estuary is drained by numerous water bodies, with river Mungo being the most outstanding. This has enabled the deposition of sand that serves as an important resource for infrastructural development. Technology has encouraged exploiters to embark on industrial extraction of this highly demanded non-ferrous mineral. This study identifies and locates the areas of industrial sand exploitation, x-ray the extraction method, determine output and analyse the impact of the activity on the environment using a triangulation approach in sourcing data, it was observed that between 2012 and 2018, nine companies were involved in industrial sand mining with a mean production of 74,556 m3 and 100,319,500 FCFA paid as taxes. Recommendations have been proposed to ensure the sustainability of the activity.
    Keywords: Industrial extraction; River Mungo; Royalty; Sand mining; Sustainable.
    DOI: 10.1504/IJKEDM.2019.10021017