Email Classification Using Adaptive Ontologies Learning

Abstract

Email is a way of communication for the today’s internet world, private and government sector or public sector all are used email for communication with their clients. They can freely send number of mail to their client without disturbing them. Now a day email communication is also a way of advertising, some mail is also spam, lots of social mails are there. Categorization and handling lots of email is an important task for the researches, as they all are working in this field by using the Natural language processing and ontology extraction process. User get frustrated for handling lots of mails and reading those for finding there is any important mail, sometime user delete lots of mail without reading and in that case may be some important mail which contain the important information may be about meeting, seminar etc. is also deleted. For avoiding these scenarios here auto updation of schedule calendar procedure is proposed by the author. Concept extraction and clustering of concept is done based on fuzzy logic, similar mail pattern is grouped in a same cluster if similarity is less than threshold value a new cluster is defined for that. From the extracted concept author establish the relationship between them and generate the result. Computation overhead is also calculated for different set of mails and finds that it takes very less time in computing large email data set.