Abstract: With the rapid development of modern network technology,human society has entered the era of information.An increasing number of people prefer to talk and make friends with others through social networks.Besides the people or events which users initiatively focus on,social network will also recommend alternative users.However,most of the alternative users are the promotion of social networks.In this paper,for the accuracy and reliability of social networks recommendation,a new scheme based on tag matching was proposed.First,each word in the corpus is trained by Word2Vec,and then a word vectors space can be obtained and the similarity among words can be obtained by using the cosine similarity.Secondly,through the similarity comparison experiments,this paper chose an appropriate similarity value as the threshold to judge whether two words are similar.Finally,the similarity threshold was applied to the matching algorithm.The simulation experiments show that the recommend users are relatively reliable and accurate.

Key words: Friend recommendation, Similarity degree computing, Social networks, Word2Vec