@article{article_841299, title={Separation of Incoming E-Mails Through Artificial Intelligence Techniques}, journal={Avrupa Bilim ve Teknoloji Dergisi}, pages={690–696}, year={2021}, DOI={10.31590/ejosat.841299}, author={Yağanoğlu, Mete and Irmak, Erdal}, keywords={Spam Tespiti, Doğal Dil İşleme, Yapay Zeka, Makine Öğrenmesi}, abstract={Technological developments are making individuals and organizations ever more dependent on e-mail to communicate and share information. Increasing use of e-mail as an important and popular method of communication poses potentially serious threats to the Internet and society. Spam e-mails cause security problems for internet users, and waste storage, bandwidth and productivity resources. The increase in the volume of spam e-mails has created an intense need for the development of more reliable and robust antispam filters. Therefore, it has become necessary to recommend adaptive spam detection models. In this paper, an intelligent system for the detection and filtering of spam e-mails is described. Machine learning methods aim to create the best models using the available data, and to analyze new data in the most accurate way, with the help of the model created using previous data. In this study, spam detection was carried out using machine learning methods. The classification achieved a success rate of 98,2% in spam detection.}, number={21}, publisher={Osman SAĞDIÇ}