The invention discloses a sign-in position prediction method based on personalized hierarchical kernel density estimation

A technology of kernel density estimation and prediction method, applied in the field of data analysis, can solve the problems of not solving data sparsity, not fully considering personalization, etc., and achieve the effect of solving data sparsity problem and accurate results

Active Publication Date: 2019-06-18
CHONGQING UNIV OF POSTS & TELECOMM
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Problems solved by technology

When considering the impact of geographic location on user sign-in, existing location prediction technologies do not fully consider the problem of personalization and do not solve the problem of data sparsity

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  • The invention discloses a sign-in position prediction method based on personalized hierarchical kernel density estimation
  • The invention discloses a sign-in position prediction method based on personalized hierarchical kernel density estimation
  • The invention discloses a sign-in position prediction method based on personalized hierarchical kernel density estimation

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Embodiment Construction

[0031] Embodiments of the present invention are described below through specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the content disclosed in this specification. The present invention can also be implemented or applied through other different specific implementation modes, and various modifications or changes can be made to the details in this specification based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the diagrams provided in the following embodiments are only schematically illustrating the basic concept of the present invention, and the following embodiments and the features in the embodiments can be combined with each other in the case of no conflict.

[0032] Please refer to Figure 1~3 , the present invention provides a geographical location prediction method based on personalized hierarchical kernel densi...

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Abstract

The invention relates to a sign-in position prediction method based on personalized hierarchical kernel density estimation, and belongs to the technical field of data analysis. The method comprises the following steps: S1, establishing binary kernel density estimation based on a geographic space by utilizing extracted sign-in position data; S2, constructing kernel density estimation of the adaptive bandwidth, and selecting respective bandwidth for each data point; S3, constructing personalized hierarchical kernel density estimation; And S4, calculating a parameter value by using a gradient descent algorithm. According to the method, personalized sign-in prediction is provided for the user, meanwhile, the problem of data sparsity caused by too few sign-in data is solved, the method is closeto the actual life, and the prediction result is more accurate.

Description

technical field [0001] The invention belongs to the technical field of data analysis, and relates to a check-in position prediction method based on individualized hierarchical kernel density estimation. Background technique [0002] With the popularization of smart terminals and the development of positioning technology, people's location information is easier to obtain than before, which gave birth to location-based social network (LBSN). LBSN provides location-related services, allowing users to "check in" at a physical location. For example, on sites such as Foursquare, Facebook, and Gowalla, users can selectively sign in to record their mobile behavior and corresponding location information, and can also share their location information with others. Traditional mobile phone call records use signal towers to determine the location of the mobile phone and restore the user's track, while location-based social networks provide a new dimension for mining people's mobile beha...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06Q50/00G06K9/62G06F16/29
Inventor 苏畅周秋丽谢显中
Owner CHONGQING UNIV OF POSTS & TELECOMM
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