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The impact of collocational features in Turkish Word Sense Disambiguation

机译:搭配特征在土耳其语词义歧义消除中的影响

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Word Sense Disambiguation (WSD) is the task of choosing the most appropriate sense of a word having multiple senses in a given context. Collocational features acquired from the words in neighborship with the ambiguous word are one of the important knowledge sources in this area. This paper explores the effective sets of collocational features in Turkish in order to obtain better Turkish WSD systems. A lexical sample dataset of highly polysemous nouns and verbs has been prepared as the initial step of the work. Several supervised learning algorithms have been tested on this data by supplying different feature sets to select the best performing features for both nouns and verbs in Turkish. Also, we investigated the impact of several collocational features of polysemous words and evaluated the performance of several supervised machine learning algorithms.
机译:词义消除歧义(WSD)是为给定上下文中具有多种意义的单词选择最合适的词义的任务。从与歧义词相邻的词中获得的并置特征是该领域中重要的知识来源之一。本文探索了土耳其语中的有效搭配特征集,以获得更好的土耳其WSD系统。作为工作的第一步,准备了一个高度多义名词和动词的词汇样本数据集。通过提供不同的功能集为土耳其语中的名词和动词选择表现最佳的功能,已对此数据测试了几种监督学习算法。此外,我们研究了多义词的多个搭配特征的影响,并评估了几种监督式机器学习算法的性能。

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