Research On LBS By POI Push Method In Mobile Environment

With the development of the mobile Internet, the push service of POI has played an important role of information push services. As an important part of moving map, POI carrying the user’s target search, property viewing, route query functions, thus positioning accuracy of POI data space, richness and clarity of expression attributes affects the quality and availability of mobile map directly. But now, there are still a lot of problems in POI expression on a moving map, especially when the user makes a query, the results of the query is not treated, more if the number of query results on a moving map,it will cause a lot of POI overlay, gland, resulting in severe space conflict, not only reduces the quality of the moving map, but also affect the use of the map and user awareness of the geographical environment. Due to the relatively low screen size and resolution of mobile devices, this problem is very prominent. Based on the study of the current push algorithm typical to POI, on the issue after the current push in the practical application of the algorithm to analyze the presence of problem, and point out a new push model of point of interest, we mainly focus on geographic information clustering, create a lightweight adaptive POI push model. The following outlines are the main contents and innovation of this paper:(1) To point out that the features and tasks in the mobile of POI push service. Push the point of interest on the existing algorithm time complexity analysis, pointing out the problems of these algorithms and disadvantages.(2) Based on the user’s historical trajectory clustering, to point out an clustering method of geographic information, dig out the user`s potential point of interest, as a point of interest on the basis of the updated weights.(3) A new point of interest classification.