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Performance Analysis of Recent Word Sense Disambiguation Techniques

机译:近期词感歧义技术的性能分析

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This paper presents recent advances in the in the area of Word Sense Disambiguation (WSD). While the supervised machine learning techniques have proven to be most efficient with the problem of availability of sense tagged data. While describing a few important techniques the paper then represents a comparative analysis among them. There is very less commonality among the data sets which have been used but it has been found out that the Genetic Algorithm based approach has the capability to beat other milestone techniques in the literature.
机译:本文介绍了近期词学歧义区(WSD)的进步。虽然监督机器学习技术已被证明是最有效的,但是在感知标记数据的可用性问题中最有效。在描述一些重要的技术的同时,纸张则表示它们之间的比较分析。已经使用的数据集之间存在非常少的共性,但已经发现基于遗传算法的方法具有击败文献中的其他里程碑技术的能力。

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