基于FP-Growth算法的孟加拉语词义消歧研究

Mohammad Shibli Kaysar, Md. Asif Bin Khaled, Mahady Hasan, Mohammad Ibrahim Khan
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引用次数: 7

摘要

词义消歧是根据上下文确定歧义词的具体含义的工作。在自然语言处理领域,WSD是一个开放的问题,它的发展可以极大地辅助人类级别的机器翻译。本文提出了一种基于FP-Growth算法的孟加拉语词义消歧系统。此外,我们还实现了Apriori算法,并对两者进行了分析,以解释FP-Growth算法如何优于Apriori算法执行孟加拉语词义消歧。此外,在测试阶段,我们发现对于80%的测试句子,我们提出的方法可以检索出歧义词的确切含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Word Sense Disambiguation of Bengali Words using FP-Growth Algorithm
Word Sense Disambiguation (WSD) is the task of determining the specific meaning of an ambiguous word according to the context. In the realm of natural language processing, WSD is an open problem, and its development can significantly assist in human-level machine translation. In this paper, we have proposed a system for Bengali Word Sense Disambiguation through the FP-Growth algorithm. Moreover, we have also implemented the Apriori algorithm and presented an analysis on both of them to explain how the FP-Growth algorithm outperforms the Apriori algorithm performing Bengali Word Sense Disambiguation. Furthermore, In the testing phase we have found that for 80% of the test sentences, our proposed method can retrieve the exact meaning of an ambiguous word.
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