Email category recommendation system based on semantic web exploiting big data processing techniques
Nowadays, people who use the Internet have at least one email address. Email has become 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 work, we had proposed a category recommendation system using big data technologies that give meaning to the words from a clustering result of the contents of the mass email. After removing stopwords in the email, the email contents in distributed server environment are clustered by exploiting Latent Dirichlet Allocation (LDA) algorithm. And then, top 10 keywords are recommended by utilizing social folksonomy such as the tag cluster with clustered email. Finally, the high-level concept word among 10 keywords is recommended as email category label to the user.
