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Bengali Stop Word and Phrase Detection Mechanism

机译:孟加拉语停用词和词组检测机制

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摘要

Though plenty of research works have been done on stop word/phrase detection, there is no work done on Bengali stop wordsand stop phrases. This research innovates the definition and classification of Bengali stop words and phrases and implementstwo approaches to identify them. First one is a corpus-based approach, while the second one is based on the finite-stateautomaton. Performance of both approaches is measured and compared. Result analysis shows that corpus-based methodoutperforms the finite-state automaton-based method. The corpus-based and finite-state automaton-based method shows 90%and 80% of accuracy, respectively, for stop word detection and 80% and 70% accuracy, respectively, for stop phrase detection.
机译:尽管在停用词/短语检测方面已经进行了大量研究工作,但孟加拉语停用词和停用词组尚无任何工作。本研究创新了孟加拉语停用词和短语的定义和分类,并实现了两种识别方法。第一个是基于语料库的方法,而第二个是基于有限状态自动机。测量和比较两种方法的性能。结果分析表明,基于语料库的方法优于基于有限状态自动机的方法。基于语料库和基于有限状态自动机的方法对于停用词检测分别显示90%和80%的准确性,对于停用短语检测分别显示80%和70%的准确性。

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