Spam Message Classification Using C4.5 and Steepest Ascent Hill Climbing and Genetic Algorithm for Feature Selection
D. Saraswathi, R. K. Kavitha · 2024
Text messaging is a feature of the mobile industry that is frequently utilized. The purpose of text message is to generate revenue for its creators. Spam is the colloquial word for unsolicited bulk messages containing commercial content. Spam via text message is used to spread phishing links and for commercial gain. The user’s phone alerts them to incoming messages every time text message spam reaches their inbox. In addition to taking up space on the user’s phone and wasting time, text message spam leaves the recipient disappointed when it becomes apparent that the message is unsolicited. These days, there are several developed algorithms accessible to detect spam text messages. even if text message spam still has an impact on users. The mobile sector must implement the finest text message filtering possible. The suggested study uses C4.5 decision tree in conjunction with a steeepeset ascent hill climbing and genetic algorithm to identify spam in text message. The suggested approach used decision trees to classify the optimal characteristics after they were discovered using metaheuristic methods. Comparing this hybrid strategy to the current classification methods, performance was superior.