User visiting prediction model establishment and user visiting prediction method and apparatus

A prediction model and user technology, applied in the field of information processing, can solve problems such as poor coverage and single data source, and achieve the effect of improving accuracy and optimizing user visit prediction technology

Active Publication Date: 2016-10-26
BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In the process of realizing the present invention, the inventor found that the main defect of the prior art is that each scheme in the prior art mainly relies on the positioning information of the user's GPS (Global Positioning System, Global Positioning System) and Wi-Fi near the point of interest. -Fi information, etc., the data source is relatively single, so there will be problems of poor coverage to varying degrees

Method used

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  • User visiting prediction model establishment and user visiting prediction method and apparatus
  • User visiting prediction model establishment and user visiting prediction method and apparatus
  • User visiting prediction model establishment and user visiting prediction method and apparatus

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no. 1 example

[0052] Figure 1a It is a flow chart of a method for establishing a user visit prediction model provided in the first embodiment of the present invention. The method of this embodiment can be executed by a device for establishing a user visit prediction model, and the device can use hardware and / or software It can be implemented, and generally can be integrated into the modeling server that completes the function of building the user visit prediction model, and used in conjunction with the data server that stores the map search data. The modeling server and the data server can be the same server or belong to the same server cluster. It can also be different servers, which is not limited in this embodiment. The method of this embodiment specifically includes:

[0053] 110. Generate candidate samples according to the user's map search data.

[0054] In this embodiment, the map search data specifically refers to the map location where the user sets the search location or the arr...

no. 2 example

[0079] figure 2 It is a flowchart of a method for establishing a user visit prediction model according to the second embodiment of the present invention. This embodiment is optimized on the basis of the above-mentioned embodiments. In this embodiment, according to the user's positioning trajectory data, select candidate samples that meet the user's actual visit conditions as training samples. Select a sample as the current processing sample; select a verification time interval according to the specified time interval in the current processing sample; obtain the positioning trajectory data of the target user corresponding to the current processing sample within the verification time interval; if If the acquired positioning track data and the search location in the current processing sample satisfy a set distance relationship condition, then the current processing sample is determined to be a training sample. Correspondingly, the method in this embodiment specifically includes...

no. 3 example

[0098] Figure 3a It is a flowchart of a method for establishing a user visit prediction model according to the third embodiment of the present invention. This embodiment is optimized based on the above embodiments. In this embodiment, it also preferably includes: obtaining the last search time in the training samples; calculating the difference between the last search time and the user's actual arrival at the search location. The difference between times is used as a training target value; the set regression model is trained using the last search time and the training target value, and the trained regression model is used as a visit time prediction model. Correspondingly, the method in this embodiment specifically includes:

[0099] 310. Generate candidate samples according to the user's map search data.

[0100] 320. According to the positioning track data of the user, select a candidate sample that satisfies the actual visit condition of the user as a training sample.

...

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Abstract

Embodiments of the present invention disclose a user visiting prediction model establishment and user visiting prediction method and apparatus. The user visiting prediction model establishment method comprises generating candidate samples according to map search data of a user; selecting the candidate sample satisfying an actual visiting condition of the user as a training sample according to positioning track data of the user; determining training characteristics corresponding to the training sample according to arrival mode associated information in the training sample; and training a set single-class classification training model by using the training characteristics corresponding to the training sample, and using the trained single-class classification training model as a user visiting prediction model. According to the technical scheme, the technical problems that for existing methods for calculating and deducing user visiting POI, due to the fact that the map search data are not considered, the data are single, and using coverage is poor to various degrees can be solved, an existing user visiting prediction technology can be optimized, and accuracy of user visiting prediction can be increased.

Description

technical field [0001] The embodiments of the present invention relate to information processing technology, and in particular to a user visit prediction model establishment and visit prediction method and device. Background technique [0002] With the continuous development of mobile Internet and mobile smart devices and terminals, terminal users generate a large amount of offline data such as positioning and trajectory. Offline data truly reflects the behavior characteristics of users in physical time and space, forms a good supplement to online data, improves the calculation of user portrait attributes, and is widely used in many specific applications such as online information push and precision marketing. In particular, if it can be determined or predicted that the user has visited a POI (Point Of Interest), such as a hotel, restaurant, etc., then information push that accurately hits the actual needs of the user can be completed. [0003] At present, there are roughly...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/9537
Inventor 汪天一许梦雯武政伟程允胜吴海山
Owner BAIDU ONLINE NETWORK TECH (BEIJIBG) CO LTD
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