A Dating Mobile Application Design And Implementation Based On K-Nearest-Neighbor Algorithm

2007 is destined to be an extraordinary year, in this year, Google and Apple were released their first smart mobile phone, limited to the technical conditions, the intelligent mobile phone function is still not perfect, but with the two mobile phone released that marked the arrival of the era of intelligent mobile phone. The intelligent mobile phone provides the basis platform for mobile software developers who can use this platform to write software to extend the function of mobile phone. After a few years, the price of intelligent mobile phone was down to the range of people that can accept, more and more people began to make use of intelligent mobile phone, it means to everyone with a palm computer on his hand, which is responsible for the management of daily works, more and more people begin to enjoy the convenience brought by the intelligent mobile phone and it began to spread. Later, with the promotion of mobile phone hardware and network speed, software running on it can do more and more work, division of mobile software becomes more and more detailed, which appeared in the category of software dedicated to chat with friends, people can meet new friends, or contact with friends thousands of miles away through the software at any time.In 2011 the outbreak of the mobile Internet, a lot of chat software come out in this wave, there are some security risks because this kind of software is for almost all user groups. As a student, we hope to develop a chat app specialized for college students, students can chat with each other through the software, and we hope that the software can guide the students to do some meaningful things. With several senior leaderships, we have implemented such a chat software, students can release activities through it, and recruit other interested students to participate in, we want to fully mobilize the enthusiasm of the students, guide them leave the bedroom, and we have reached some achievements after the software was on the line. Due to the friends-matching function is not perfect since then, the matching success rate is low and user experience is not friendly, the software is forced to interrupt after a period of time. After the project is stopped, the author decided to rewrite its friends-matching function, try to find a suitable matching algorithm and improve it according to the actual situation of the software, in addition to solve the problems mentioned above, the match must satisfy a certain degree of flexibility, to other chat software that simply match database fields such as age and gender, the friends-matching algorithm should be dynamically adjusted by user’s behavior. After a period of time, the author adopts k NN algorithm to rewrite friends-matching function and write a new background logic individually, to improve friends-matching algorithm while retaining the other functions.