A framework for sms spam filtering

The growth of technology has brought more convenient to human. Example, Short Message Service (SMS) enable human to communicate with each other. The popularity of SMS messages induced spam message issues increases, as people tend to mislead the beneficial from the technology. This paper proposed methods on how to filter the spam messages. In the content of this paper, the discussions are mainly how to use the functionality of bag-of-words, importance of feature extraction and classification for the incoming unknown messages. Once the keywords are being trained, the testing set prototype will able to classify the short text message. In order to train the dataset, this project requires to search more sample SMS dataset. The objective of this project is to prevent users from receiving spam messages. Therefore, the topic of this Final Year Project is Framework Method for SMS Spam filtering. Basically there is a difference between filtering email and SMS. SMS does not have header unlike email. Therefore, users very hard to determine the SMS is a spam or ham