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Method based on combined component path to recognize similar travelers

A recognition method and traveler technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve the problems of missing similar relationships, reducing the accuracy of service provision, lack of research on multi-attribute semantic relationship mining, etc., to achieve algorithm performance Good, intuitive and understandable semantics, high recall and precision

Active Publication Date: 2018-07-06
CHANGAN UNIV
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Problems solved by technology

[0004] In view of the complexity of urban traffic travel, existing research focuses more on the independent modeling and identification of a certain attribute. Although multiple attributes are allowed to be fused multiple times, due to the lack of mining research on the semantic relationship of multiple attributes, the model only Inferring the final attributes may miss similar relationships due to different attribute associations, thereby reducing the accuracy of serving

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  • Method based on combined component path to recognize similar travelers
  • Method based on combined component path to recognize similar travelers
  • Method based on combined component path to recognize similar travelers

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Embodiment Construction

[0035] The method for identifying similar travelers proposed by the present invention will be specifically described below in conjunction with the accompanying drawings.

[0036] Step 1: Data processing, preprocessing the data in the early stage, including location stay point cluster identification, time serialization fuzzy processing, access service semantic extension, etc., and converting it into the required format;

[0037] Classical heterogeneous information networks are generally defined as triples G=, where V is a collection of nodes with different properties, including different subject objects. E is a collection of edges, which describes various semantic associations between different subject objects, and A is a collection of node types, representing the type to which the subject objects belong. The network allows complex relationships between many types of nodes.

[0038] In the present invention, the original GPS data is specifically processed to include the travel...

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Abstract

A method based on a combined component path to recognize similar travelers is characterized in that tempo-spatial GPS (global positioning system) trajectories are used to construct a heterogeneous travel network model; the definition of a travel component path is provided; a component path set is selected from the heterogeneous travel network model; user similarity calculation is achieved via a travel similarity measure algorithm; travel behavior similarity between two users is predicted. The method herein has higher recall ratio and precision ratio than single-component-based path methods; the method has good visual intelligible semantic property, and is helpful for accurately discovering potential users and similar groups to provide them with more precise and differential services.

Description

technical field [0001] The invention belongs to the field of behavior recognition, and in particular relates to a similar traveler recognition method based on compound meta-paths. Background technique [0002] With the popularity of smart phones and the wide use of various positioning devices, the acquisition of various travel data of users has become more real-time, easier and more accurate. Therefore, research on user travel issues is developing rapidly, such as research on travel group discovery, transportation service recommendation, location-based social networks, route planning, and other related work. At the same time, by studying the travel of users, we can provide users with better travel experience and travel services. [0003] The research of big data and the emergence of smart devices make travel similarity get a lot of attention. In the similarity research of user travel, the main problem is the feature selection of travel and how to solve the sparsity of user...

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/23G06F18/22
Inventor 唐蕾赵亚玲陈君杨祎祯贾景池
Owner CHANGAN UNIV
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