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

Active Publication Date: 2019-05-03
杭州掌维科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, at present, many advertisements are placed randomly, that is, each time a user comes, an advertisement is randomly selected to serve him, and the delivery efficiency is very low
At the same time, the arbitrariness of advertising also makes users feel disgusted

Method used

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  • A mobile internet advertisement recommendation method based on collaborative filtering
  • A mobile internet advertisement recommendation method based on collaborative filtering

Examples

Experimental program
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Embodiment Construction

[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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PUM

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Abstract

The invention discloses a mobile Internet advertisement recommendation method based on collaborative filtering. The method includes: step 1, acquiring user sign-in data and microblog text data; step 2, preprocessing the user sign-in data and microblog text data; Step 3, calculate user interest similarity; Step 4, use hierarchical clustering method to analyze user check-in data, and compare the similarity of user behavior trajectories from both overall and local aspects according to the spatio-temporal intersection of user behavior trajectories , and through a linear combination, the similarity of user behavior trajectories is obtained; step 5, comprehensively considering the similarity of user interests, the similarity of user behavior trajectories, and the influence of user behavior similarity in different time periods and the popularity index of advertisements, using The recommendation method of collaborative filtering calculates the recommendation value of mobile Internet advertisements and recommends the top-ranked advertisements to users.

Description

technical field [0001] The invention relates to the field of data mining, in particular to a collaborative filtering-based mobile Internet advertisement recommendation method. Background technique [0002] Advertising is a media method used to persuade potential consumers to take some action (purchase, registration or attention, etc.). , ads are everywhere. With the rapid development of mobile Internet technology, the attention of many advertisers has shifted from traditional media advertising to mobile Internet advertising. However, at present, many advertisements are placed randomly, that is, each time a user comes, an advertisement is randomly selected to be served to him, and the delivery efficiency is very low. At the same time, the arbitrariness of advertising also disgusts users. In the face of this situation, the personalized and precise placement of mobile Internet advertisements has attracted extensive attention from researchers. [0003] In terms of advertisin...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9535G06K9/62G06Q30/02
CPCG06F16/9535G06Q30/0251G06F18/231G06F18/22
Inventor 刘兴伟田雪松夏梅宸牟峰张晓丽严兵
Owner 杭州掌维科技有限公司
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