Topic-based Social Network Event Recommendation Algorithms And Systems:Research And Implementation

With the fast development of Internet and the explosion of all kinds of information,people are flooded with complicated information.To solve this severe “information overload” problem,recommendation system has been proposed which is an intelligent aided decision system.Nowadays,extensive research for recommender system is conducted,which can be widely used in e-commerce or offline events application,etc.The traditional recommendation algorithms are mainly divided into the following categories: collaborative filtering recommendation algorithm,content-based recommendation,and hybrid recommendation algorithm.And there are two categories in collaborative filtering recommendation algorithm,one is model-based collaborative filtering,and the other is Memory-based collaborative filtering.In this article,we proposed effective algorithms for the cold-start event problem in social network through a lot of literature reading.Firstly,considering the traditional content based recommendation ideas,we extract the text attributes of activities,by using LDA topic model and combining the time function with the user's behavior weights to establish the long-term and short-term of the user interest features,which can provide an effective and rapid activity recommendation.Secondly,we propose three hybrid recommendation algorithms which make use of the relationship of users in social network to build adjacency matrix and similarity matrix of users and events that aim to cluster user into similar user communities.These algorithms proposed can solve event cold-start problem efficiently.Thirdly,we design and develop a complete recommendation system,which apply the previously mentioned recommendation algorithm into this recommendation system to put these theories into practice.Finally,for the proposed algorithm,we verify the effectiveness of algorithm by doing experiment with database crawled from Douban event.For the recommendation system,we verify the high concurrency and high availability of the system with professional test software testing.