A mobile internet advertisement recommendation method based on collaborative filtering
A mobile Internet and collaborative filtering technology, applied in the field of mobile Internet advertising recommendation based on collaborative filtering, can solve the problems of low delivery efficiency, random advertisement placement and user disgust, and achieve the best matching effect
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[0034] The present invention will be described in detail below in conjunction with the accompanying drawings.
[0035] as attached figure 1 Shown, the inventive method carries out according to the following steps:
[0036] Step 1: Obtain user check-in data and microblog text data posted by users, where user check-in data includes user ID, check-in location, check-in time, and check-in date, etc., and check-in location includes the latitude and longitude of the geographic location where the user checks in and the check-in "point of interest" (Point of Interest, POI);
[0037] Location-based mobile social networks (LBSN) such as Sina Weibo, Jiepang, Renren, Foursquare, and Gowalla have developed rapidly in recent years. A large number of users use these services to record spatio-temporal behavior trajectories in the form of check-in. Therefore, they can provide API to capture the required user sign-in data;
[0038] As a sharing and communication platform, Weibo allows users ...
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