MODEL FOR RECOMMENDING TRAVEL DIRECTIONS BASED ON USER NETWORK PROFILE PHOTOS

This study introduces a novel approach for recommending travel directions by analyzing user network profile photos. Traditional travel recommendation systems often rely on text-based input or user historical behavior, which can be limiting in capturing users’ real-time preferences and context. In contrast, our proposed model utilizes visual data from social network profile photos to infer users’ current interests and potential travel needs.The model operates in three key phases: image analysis, interest inference, and recommendation generation. In the image analysis phase, profile photos are processed using advanced computer vision techniques, including facial recognition, object detection, and scene understanding, to extract relevant features.