Research And Application On Personalized Recommendation Algorithm Based On Context Awareness

With the vigorous development of the Internet industry,it brings people great convenience in the life,at the same time,it also brings the serious problem of information overload.Nowadays personalized recommendation has become one of the important means to solve the problem of information overload,its applications have penetrated in the various fields and all aspects of people's life.Personalized recommendation technology based on context awareness has become the focus of research,it can make the recommendation more effective and make the user more satisfied with the results of the recommendation because that it takes full account of the role of contextual information and the context information of users and commodities is integrated into the recommended algorithm.In this paper,the traditional recommendation algorithm and context awareness are seen as the premise of study,from a perspective of practical application,aiming at the problem of recommender system in various situations currently,an improved algorithm which have higher accuracy and user satisfaction is proposed and applied,the main contents of this paper are as follows:(1)This paper gives a brief introduction which aims to the existing recommendation algorithms,context awareness theory and context awareness recommendation technology and makes a detailed analysis aiming to their research status and existing problems.(2)Aiming at the problem of low accuracy and user satisfaction in the recommendation algorithm,an improved collaborative filtering recommendation algorithm based on context similarity is proposed.According to the effect of magnetic force in physical point charges,the situational factor is introduced,a new model of user context and commodity is constructed;According to the Coulomb's law,a user similarity formula is redefined after adding to the concept of magnetic force;Finally,a more accurate prediction is calculated according to the new score aggregate function so that it can be recommended.The good performance of the improved algorithm is verified theoretically and experimentally.(3)It is applied to the system based on the improved recommendation algorithm,the system of dining recommendation based on context awareness is designed in detail.The business requirements and performances requirement in dining recommendation system are analyzed;Each module of the system function are designed in detail secondly,especially the design and realization of core algorithm which is in the recommendation module;Finally,according to the analysis and comparison of the recommendation results which from recommendation system in the traditional algorithm and dining recommendation system in the improved algorithm,the feasibility and scientificity of the improved algorithm are verified.