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- W2959691736 abstract "Natural Language Processing <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>11</sup> Henceforth: NLP is an emerging research area in today's era. The NLP resources are quite useful when it comes to building a machine capable of translating between linguistic pairs - a solution that strives to resolve the language barrier problems. Based on this premise, we are focusing our research on feature identification from large text collections of Albanian language. `Rule-based' or statistical Part-of-Speech <sup xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>22</sup> Henceforth: POS (POS) taggers are sought to be utilized that would either need considerable time for rule development or a sufficient amount of manually labelled data. In light of this, the impact of this research is based on exploring numerous cases that are conducive to progress and further development of this field. One of the goals of this paper is to conduct a systematic review study; to explore and analyze existing research that seek to target low resources language such as is the case of the Albanian language. According to prior observation of published research conducted since 2015, we are focusing our research on studies that have been published in areas that are relevant to Natural Language Processing. Based on considerable load of related research on this field, it is essential to conduct a review and provide an outline of the research situation as well as current developments in this specific but important field of research." @default.
- W2959691736 created "2019-07-23" @default.
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- W2959691736 date "2019-06-01" @default.
- W2959691736 modified "2023-09-26" @default.
- W2959691736 title "A Systematic Mapping Study of Language Features Identification from Large Text Collection" @default.
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- W2959691736 doi "https://doi.org/10.1109/meco.2019.8760042" @default.
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