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Tensor-based user track mining method

A user trajectory and user technology, applied in special data processing applications, instruments, calculations, etc.

Active Publication Date: 2015-08-19
HUAZHONG UNIV OF SCI & TECH
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  • Description
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AI Technical Summary

Problems solved by technology

The mining of user trajectories in the existing technology mainly starts from the location, and researches the user's hot interest location rules to find frequent patterns for recommendation; the disadvantage is that the location is only a part of the trajectory, and the moving route between connecting locations is also a very important trajectory. a part of

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Embodiment Construction

[0022] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention. In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not constitute a conflict with each other.

[0023] Such as figure 1 As shown, the tensor-based user track data mining method of the present invention includes the following steps:

[0024] (1) Obtain the user's historical trajectory data. The trajectory is the imprint left by the moving object (person or vehicle) moving in space over time. The user's historical trajectory data point P is in the following format (user ID, longitude, lati...

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Abstract

The present invention discloses a tensor-based user track mining method. The tensor-based user track mining method comprises: (1) acquiring history track data of a user; (2) dividing data with time difference exceeding a predetermined time threshold in the history track data to form a plurality of segments of continuous track data; (3) extracting an arrest point of the user in each segment of track on account of each segment of continuous track data; (4) dividing the arrest point into a start point and a destination point and acquiring a corresponding road segment in sequence by a map matching method; (5) building a three-dimensional tensor by using the arrest point and the road segment sequence; (6) finding a related hotspot road segment between the start point and the destination point for a user search request (S,Q); and (7) calculating a recommended path according to a road segment weight set. The tensor-based user track mining method according to the present invention has the advantages as follows: only longitude and latitude of each of the start point and the destination point are provided for searching the hotspot recommended path between the start point and the destination point for the user search request; and the user does not need to understand the background implied data structure.

Description

technical field [0001] The invention belongs to the field of mobile Internet information technology, and more specifically, relates to a tensor-based user trajectory mining method. Background technique [0002] The research based on user trajectory location data is one of the current research hotspots of the mobile Internet. The trajectory is the imprint left by a moving object (object such as a person or a vehicle) moving in space over time. With the rapid development of mobile device embedded technology, GPS positioning technology has been widely used in mobile devices. With the popularity of location-based services (Location Based Service, LBS), users can upload and share their trajectory data at any time through various platforms such as Google+ or Foursquare, and a large amount of trajectory data is being accumulated in daily life. And serve different types of applications. However, most of the applications are using the raw data of GPS, such as the longitude and lati...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 余辰金海洪钦敏姚德中
Owner HUAZHONG UNIV OF SCI & TECH
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