土耳其推特上的问题识别

Zeynep Banu Ozger, B. Diri, Canan Girgin
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引用次数: 1

摘要

问题识别是自然语言处理的一个领域,也是信息抽取的一个领域。这项工作的目的是检测包含问题表达的土耳其语推文。该应用程序包含三个阶段:对数据集应用一些预处理步骤,以清除不必要的数据,如Retweet,通过基于规则的方法确定候选推文,并使用条件随机场提取真正包含问题的推文。为此,收集并标记了一百万条推文。Tweets是不符合语法的数据类型。根据结果;这种模式在推特上取得了很大的成功。此外,这是第一个关于识别土耳其推文问题的研究。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Question identification on Turkish tweets
Question identification is a field Natural Language Processing and also Information Extraction. The aim of work is detecting Turkish tweets which are including question expressions. The application contains three stages: applying some pre-processing steps to data set for cleaning unnecessary data like Retweet, determining candidate tweets via a rule-based method and extracting tweets which are really include questions using Conditional Random Fields. For this purpose one million tweets were collected and labeled. Tweets are ungrammatical data type. According to results; the model developed has been largely successful on tweets. Additionally, it is a first study about identifying questions on Turkish tweets.
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