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SPAM DETECTION BY USING NETWORK AND TEXT EMBEDDING APPROACHES THESIS SUBMITTED TO THE GRADUATE SCHOOL OF NATURAL AND APPLIED SCIENCES OF MIDDLE EAST TECHNICAL UNIVERSITY RENNET SERVE VILLAIN PARTIAL
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Gather a dataset to train the spam detection model.
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Companies with email services that want to filter out spam emails to protect their users.
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Spam detection is achieved by using various algorithms and techniques to identify and filter out unwanted or unsolicited emails or messages.
Any individual or organization that sends out mass emails or messages is required to utilize spam detection techniques.
Spam detection can be implemented through software solutions that automatically scan and filter out spam emails based on certain criteria.
The purpose of spam detection is to protect users from receiving unwanted or harmful content, as well as to maintain the integrity of communication channels.
The reports generated by spam detection systems may include details on the number of spam emails detected, the type of spam, and any actions taken.
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