Toponym recognition on Turkish tweets

Kezban Dilek Onal, P. Senkul, Ruken Cakici
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引用次数: 2

Abstract

In recent years, Twitter has become a popular platform for following and spreading trends, news and ideas all over the world. Geographical scope of tweets is crucial to many tasks like disaster management, event tracking and information retrieval. First step for assigning a geographical location to a tweet is toponym recognition. Toponym Recognition (Geoparsing) is identification of toponyms (place names) in a text. In this study, we investigated performance of three existing approaches for toponym recognition on Turkish tweets. We conducted experiments for measuring performance of the existing approaches on a sample data set. Best results have been obtained with the NER algorithm by Küçük et.al. However, we observed that existing NER algorithms for Turkish neglect the syntactic and semantic features of text.
土耳其语推文的地名识别
近年来,Twitter已经成为世界各地关注和传播趋势、新闻和想法的热门平台。推文的地理范围对于灾害管理、事件跟踪和信息检索等任务至关重要。为tweet分配地理位置的第一步是地名识别。地名识别(Geoparsing)是文本中地名(地名)的识别。在这项研究中,我们调查了三种现有的土耳其语推文地名识别方法的性能。我们在样本数据集上进行了实验,以衡量现有方法的性能。k k等人使用NER算法获得了最好的结果。然而,我们观察到现有的土耳其语NER算法忽略了文本的句法和语义特征。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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