Mobile Intelligent Recommendation Platform For Public Transportation Users

As we all know, desktop Internet had appeared an explosive growth, and people’s desire of information is satisfied via Internet so far. Almost every industry is influenced by Internet.On the other side, with the growing of the smart phones, mobile internet which once be the expand part of the traditional Internet, has been played more and more important role in the whole Internet environment. Comparing with the desktops, smart phones are much more convenient, more personalized and more sensible. The services based on the smart phones which are very popular recently have appeared to be a location or context-aware based one. All of above proves that the SOLOMO (Social, Location, and Mobile) is successful.Especially to the public transportation customers, we dig into and finally find that customers’latent demand via public transportation is the purpose of getting out, we design the recommendation platform for the customers not only make the line selection convenient but also give customers a relevant recommendation of both bus line and the position of interest around. In this way, we made the public transportation service and the personalized recommendation service on the smart phone combined together.To the detail of this thesis, we divide it to these parts:First of all, we investigate the public transportation service domestic and overseas and made a conclusion that personalized public transportation service is innovative and valuable, and then we start to design the whole system. Second, after we analyze the data of the POI and public transportation, we made a further abstraction of the data to meet the algorithm demands. Finally, we try to implement every single API of the platform under the improved the transfer, index and recommendation algorithm. At last, we give a full feature test and high availability test on the platform to verify the functionality.