Semantic enriched category recommendation system for large-scale emails exploiting big data processing technologies

Abstract

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. © 2015 IEEE.