| Summary: | A user profile can be considered as an interface of one’s characteristics, interests, thoughts, and preferences. This profile is dynamic as it is changed over time. Designing a user profile model that can track and accommodate these changes is important for providing personalized services on the Internet. This paper introduces a model for building a dynamic user profile based on the daily activities of the user and other users’ activities who are followed by this user. The proposed model tracks the user, learns from his activities, and finally reformulates the user profile. Using two different supervised learning classification algorithms, the user’s activities (tweets, retweets, etc.) are classified into a predefined list of topic categories of interest that are used to form and model the user’s dynamic profile. The primary results show that the proposed model can be used to accurately describe the user, and thus, could be the default user interface for others.
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