Abnormal advertisement flow detection method based on user portrait
A traffic detection and user technology, applied in the computer field, can solve the problems of advertiser loss in the online advertising industry, malicious cheating in the online advertising business, etc., and achieve the effects of increasing timeliness and speeding up monitoring
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Embodiment 1
[0025] Specifically, as shown in the figure, a method for detecting abnormal advertising traffic based on user portraits includes the following steps:
[0026] Step 1. Track user behavior on the advertisements viewed by users: collect user attribute information and user behavior information, locate users through cookie information in the browser, and secondly locate users through IP information;
[0027] Step 2. Characteristic analysis of user attributes: For the user attributes, behavior information and overall traffic conditions within a time period collected by a single user analysis, each attribute and behavior will generate a user label;
[0028] Step 3: Analyze the profile of a single user on the basis of Step 2: through aggregation and analysis of the historical data of multiple user tags, further adjust the user characteristic information; this step analyzes the historical context data of the user, that is, a single user behavior cannot Accurately outline user portrait...
Embodiment 2
[0032] In order to predict abnormal traffic more accurately, on the basis of Embodiment 1, in Step 4, user traffic can be further analyzed in terms of time and region. The specific steps are as follows:
[0033] (1) Statistical data according to time, region, and advertisement type dimensions. The time dimension is divided into hours, days, and months. The geographical dimension is divided according to the actual geographic location, and the advertisement type is divided according to the advertisement type data browsed by the user;
[0034] (2) Analyze user historical data on the basis of step (1), calculate traffic trends, and predict the abnormal situation of time advertisements according to the trend data.
[0035] In the second step of the present invention, the user label includes the following information:
[0036] The user identifier is the unique identification information of the user, which is used to connect the text and attributes of the user; the IP address, which ...
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