Abstract
With the advent of internet connectivity availability along with the fast pace of latest information available on the web, a lot of information is available for the user. The main challenge associated with a recommendation system is to recommend useful information to the user at right time. This paper proposes a novel context aware personalized content recommendation using ontology based spreading activation algorithm. Ontology concepts are used to describe the things in a particular domain. By analyzing the content items and user ontological profiles, meaningful content items are recommended to the users. The use of ontology allows defining the domain knowledge, whereas the spreading activation algorithm learns user pattern by discovering user behavior. In this paper, we developed a recommendation system which provide content recommendation to user based on user interests which gets changes over the period of time and system learns this using the spreading Activation algorithm.
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