Abstract- Nowadays due to increase volume of data, finding correct and accurate data becomesignificant challenge which without computer systems that is impossible. Then, we always need asystem which can find suitable information in short time within vast of data. Recomm
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Abstract- Nowadays due to increase volume of data, finding correct and accurate data becomesignificant challenge which without computer systems that is impossible. Then, we always need asystem which can find suitable information in short time within vast of data. Recommendationsystems are solution of this problem. Recommendation systems by using Data Mining technique canprovide appropriate offers and choose prominent information from among large of data. In this systemif the user logged for first time, as his/her profile is null, so by using approach based on collaborationany similar user for this user is not found which represent Cold-Start problem. Therefore, it isintroduced resource recommendation system based on tagging which can help users for choosingsuitable resource and integrating resource among all users.The present method resolved Cold-Start problem in the beginning executes system by combined andintegrated methods based on content, collaboration, related words and user profile. If system does notcontain any information and start work for first time, it is recommend to user by using resourcecontent and related words that means it is greatest advantage of present system rather than previoussystems. The proposed system offers to user based on user's personal interests, interests of similarusers, content resources, databases which associated with ontology and related words. The results ofexperiment reveal that in present system accuracy and efficiency offers improved versus othermethods.
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