Reserch On Key Technologies Of Small Social Networks Based On The IOS Platform

Social network develops from the early BBS era to the micro-entertainment era of information age after expering the entertainmentera, and now has entered the era of vertical applications with the rise of the mobile Internet. The scale of social network users continues to expand, information is also accelerating the speed of updating. It becomes more difficult for users to find valuable and reliable information quickly and accurately in a flood of information. How to help social networks provide better services which can meet the needs of users has become the focus of attention to the academic and Internet areas.This article competes products research on existing main stream social networks, and finds personalized recommendation service demand in social networks, as well as the use situation of personalized recommendation in existing social networks with the user research combining online and offline mode. In currently social networks, the traditional personalized recommendation algorithm can not make their own social networks to meet the complexities of high quality recommendation.In response to these problems, this paper focuses on the influence of chain connections of phone address book, user profile, social contentandthe time factortopersonalized recommendation method, and propose the idea that the nature of meeting the needs of individual users is to measure the information value of social information for the individual user, and then based on this to achieve high-quality personalized recommendation.There commended methodintroduces achain of social relations between people, according to phone address book divide friends into once contacts and second degree contacts, and taking into account connections to measure the value of information, then to determine the value of information to the target user with the key word tags extracted from the content, time, information publisher, the interests of information recipient. Ultimately realize personalized recommendation in social network. Experiments show that the model based on user interest for personalized recommendation algorithmis effective connections.The main work of this thesis are:(1)to make a brief overview ofthe history and current developments ofsocial networks;(2)to make a detailed functional analysis for existing main stream social networking platform, and the use of personalized recommendation;(3)to do user research, needs analysis and product design for small social networks;(4)proposed user interest model based on connections, study there commended algorithm of this model;(5)on the iOS platform, finish the related design and implementation for this small socialnetworks;Finally, we realize the research objectives of this paper to provide some references for further study in small social networks.