Dynamic Interest Model Based On Context Awareness And Its Application

With the further development of the information age, a lot of data information resource filled with people’s lives. It’s bringing great convenience, but at the same time it increases the difficulty in giving the information needed for the query."Big Data" era is coming to further promote the development of intelligent search engines and recommendation systems. With its active and efficient service, recommended system improve the information recommendation service architecture of the Internet, the user experience and it provides a new direction for digital information reform.Recent studies on the recommendation system mainly focused on two aspects of the application and recommend improved algorithm. From the application perspective, discuss how recommender systems used in various fields, in order to bring convenience is the key. Other studies are recommended from the perspective of the algorithm, and by improving the algorithm to improve the integration of a preferred system operation speed and accuracy recommended. Regardless of the level from which that improve user satisfaction is the most fundamental. Therefore, the research mainly from the user’s point of view, focusing on the customer experience, through the acquisition and analysis of user scenarios to create a user interest model based on situational awareness, combined with an appropriate recommendation algorithm, the model is applied to a digital library books recommended in order to enhance the reader satisfaction.Through access to large number of documents, to determine the feasibility of the study and on the basis of research and analysis carried out as follows.Paper studies the impact of user interest scenario and user scenarios classification. Through RFID/GPS technology and scenario models including primary user time, place and other situations is acquired and identified.Secondly, on the basis of user interest model is introduced on added interest to the user perception of the scene. User interest is the key recommendation system, as well as collecting user browsing behavior implicit object of interest and task-oriented scenarios of interest in addition to the dominant interest in the user’s own identity outside. Based on this, we propose the integration of context-aware user interest model in real time, and use the user experience feedback to update the model, designed to provide users with more accurate recommendation.Finally, the model is applied to interest on the digital library bibliographic recommendation, with appropriate recommendation algorithm, to obtain a more accurate, readers meet recommended system scenarios.