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Towards Named Entity Recognition Method for Microtexts in Online Social Networks: A Case Study of Twitter

机译:面向在线社交网络中微文本的命名实体识别方法:以Twitter为例

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Given a certain question, named entity recognition (NER) methods can be an efficient strategy to extract relevant answers. The goal of this work is to extend NER methods for analyzing a set of micro texts, which are short text on online social media. To do so, we propose two contextual closure properties to discover contextual clusters of micro texts, which can be expected to improve the performance of NER tasks. Experimental results demonstrate the feasibility of the proposed method for extracting relevant information in online social network applications.
机译:给定特定问题,命名实体识别(NER)方法可以是提取相关答案的有效策略。这项工作的目的是扩展NER方法,以分析一组微型文本,这些微型文本是在线社交媒体上的短文本。为此,我们提出了两个上下文关闭属性来发现微文本的上下文聚类,可以期望这些属性可以改善NER任务的性能。实验结果证明了该方法在在线社交网络应用中提取相关信息的可行性。

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