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Semantic Enriched Category Recommendation System for Large-Scale Emails Exploiting Big Data Processing Technologies

机译:利用大数据处理技术的大型邮件的语义丰富类别推荐系统

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摘要

Nowadays, people who use the Internet have at least one email account. Email is important means of information sharing and communications. For example, email is used for business communications or business advertisements, and personal use, such as checking bills or keeping in touch with others. However, it has become difficult to manage email as the amount of email usage increases. In this paper, we propose a semantic enriched category recommendation system for large-scale emails exploiting big data technologies. First of all, an email pre-processing process is performed. And then, through Latent Dirichlet Allocation (LDA) algorithm from Mahout the email contents in distributed server environment are clustered. A word representing the cluster, the category, from extracted cluster should determine. That way, the semantic relationships of cluster inner words analyze using the Flickr. Finally, the semantic enriched category is recommended to user.
机译:如今,使用Internet的人们至少拥有一个电子邮件帐户。电子邮件是信息共享和交流的重要手段。例如,电子邮件用于商业通信或商业广告,以及用于个人用途,例如检查账单或与他人保持联系。然而,随着电子邮件使用量的增加,已经变得难以管理电子邮件。在本文中,我们为利用大数据技术的大型电子邮件提出了一种语义丰富的类别推荐系统。首先,执行电子邮件预处理过程。然后,通过Mahout的潜在Dirichlet分配(LDA)算法对分布式服务器环境中的电子邮件内容进行聚类。应当从提取的群集中确定代表群集的单词(类别)。这样,群集内部单词的语义关系就使用Flickr进行分析。最后,向用户推荐语义丰富的类别。

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