帮忙翻译两段文字等我上传了照片在翻译,谢谢1

帮忙翻译两段文字
等我上传了照片在翻译,谢谢
1

With the rapid development of the Internet in recent years,information on the Internet became so much that it exceeds the effective limit of receiving,processing and using for an individual,which is known as the frequently mentioned data overloading.Recommendation system has been an important technology for dealing with the issue of data overloading and many algorithms has been continuously proposed for it,many of which has achieved fairly good results in customized service,E-business and computational advertising.Despite of all the proposed algorithms,the recommendation system still encounters various difficulties such as mass data processing,low accuracy of forecast,sparseness of data and cold boot etc.On the other side,with the advent of the social network services on the internet in the past few years,more and more users’ information in such network become usable.Some recommendation strategies has achieved remarkable results in using of such users’ information on certain social networks,but such information is not put into proper use in the current recommendation system.
This paper firstly introduced the current studies on the recommendation system,analyzed and summarized the advantages and disadvantages of some existing collaborative filtering algorithms.Meanwhile,it introduced some methods in computing the node similarity in the social network analysis,analyzed and summarized their respective principles and application scenarios.On the basis of relevant outcomes and in view of the issues facing the current collaborative filtering technologies,it made an in-depth research on combining the social network analyses with collaborative filtering technologies and proposed some effective solutions.
再问： 帮忙看下这个呗 http://zhidao.baidu.com/question/553808798.html
再答： 好的。