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A Simple Approach for Monolingual Event Tracking System in Bengali

机译:孟加拉语单晶体事件跟踪系统的简单方法

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Real-world applications have to take into consideration both topics and sentiments for precise opinion measurement. Topic and sentiment alignment is crucial for opinion retrieval, extraction, categorization, and aggregation on various issues. In this paper, we have reported a Monolingual Event (or, topic) Tracking system for Bengali. The system has been developed based on a newspaper corpus developed from the web archive of a leading Bengali newspaper. The goal of the system is to determine whether two news documents within a range of dates describe the same event. An event is a vector consisting of person, location, organization, title and date. A particular news document is described as a collection of such event vectors. A particular threshold value has been considered to check whether the number of event vectors of two separate news documents match at least by this threshold. Any particular news document of a date has been selected as the initial story. All the news documents within the preceding 15 and following 15 days have been considered as the target stories (or, documents). Evaluation results have demonstrated the Recall and Precision of 58.93% and 84.62%, respectively. The future works will look for interactions between topics and associated sentiments.
机译:现实世界的申请必须考虑到精确的观点测量的主题和情绪。主题和情绪对齐对于各种问题的意见检索,提取,分类和聚集至关重要。在本文中,我们报告了孟加拉的单机事件(或主题)跟踪系统。该系统已基于从领先的孟加拉语报纸的Web Archive开发的报纸语料库开发。该系统的目标是确定在一系列日期内的两个新闻文档是否描述了相同的事件。一个事件是由人,位置,组织,标题和日期组成的向量。特定新闻文件被描述为此类事件向量的集合。已经考虑了特定的阈值来检查两个单独的新闻文档的事件矢量的数量是否至少通过该阈值匹配。已选择日期的任何特定新闻文件作为初始故事。前面15岁及以下15天内的所有新闻文件都被视为目标故事(或文件)。评价结果证明了召回和精度分别为58.93%和84.62%。未来的作品将寻找主题与相关情绪之间的相互作用。

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