Abstract:
As the number of items increases dramatically, the problem of information overload becomes more serve when browsing and searching. The agents overcome this problem and help the user interaction on a working environment on the user's interests and desires. The user's interest information is obtained from the user registration and user's activities. Depending on this information the system calculates the collaborative recommendation for user requirements using the agglomerative clustering algorithm and linear regression for the new user and content-based recommendation for existing user using naïve Bayesian classification. This system provides assistance to the user by solving problem through agent user interaction.
