论文标题
使用基于情感的特征以阿拉伯语进行问题识别
Question Identification in Arabic Language Using Emotional Based Features
论文作者
论文摘要
随着社交媒体网络上内容的增长，企业和服务提供商已经对确定客户的问题感兴趣。通过与阿拉伯用户的增加成正比的文本的增长，跟踪这些问题变得非常具有挑战性，因此很难手动跟踪。通过自动确定在社交媒体网络上寻求答案的问题并定义其类别，我们可以通过找到现有答案，甚至将它们路由到负责在客户服务中回答这些问题的人来自动回答。这将导致节省时间和精力，并增强客户反馈并改善业务。在本文中，我们实施了一个二进制分类器，将阿拉伯语文本分类为寻求答案的问题。我们为最先进的功能添加了基于情感的功能。实验评估已经完成并表明这些情绪特征提高了分类器的准确性。
With the growth of content on social media networks, enterprises and services providers have become interested in identifying the questions of their customers. Tracking these questions become very challenging with the growth of text that grows directly proportional to the increase of Arabic users thus making it very difficult to be tracked manually. By automatic identifying the questions seeking answers on the social media networks and defining their category, we can automatically answer them by finding an existing answer or even routing them to those responsible for answering those questions in the customer service. This will result in saving the time and the effort and enhancing the customer feedback and improving the business. In this paper, we have implemented a binary classifier to classify Arabic text to either question seeking answer or not. We have added emotional based features to the state of the art features. Experimental evaluation has done and showed that these emotional features have improved the accuracy of the classifier.
