A method and system for destination recommendation based on multi-source heterogeneous information network
An information network, multi-source heterogeneous technology, applied in neural learning methods, geographic information databases, digital data information retrieval, etc., can solve the problems of sparseness, neglect, and scattered check-in data, and achieve the effect of improving accuracy
Active Publication Date: 2022-08-09
ZHEJIANG LAB
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However, these methods have some deficiencies. Firstly, due to the randomness of the user’s check-in behavior, the check-in data is relatively scattered and sparse. Neglect; therefore, there is still a lot of room for improvement in the accuracy of the current destination recommendation system
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[0031] Exemplary embodiments will be described in detail herein, examples of which are illustrated in the accompanying drawings. Where the following description refers to the drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the illustrative examples below are not intended to represent all implementations consistent with the present invention. Rather, they are merely examples of apparatus and methods consistent with some aspects of the invention as recited in the appended claims.
[0032] The terminology used in the present invention is for the purpose of describing particular embodiments only and is not intended to limit the present invention. As used in this specification and the appended claims, the singular forms "a," "the," and "the" are intended to include the plural forms as well, unless the context clearly dictates otherwise. It will also be understood that the term "an...
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The invention discloses a destination recommendation method and system based on a multi-source heterogeneous information network. The system includes a data preprocessing module, a multi-source information fusion module, and a heterogeneous neural network recommendation module. The data preprocessing module includes a data collection and data cleaning module. The present invention collects the data of the vehicle driving state from the OBD interface of the private car and the vehicle track information from the GPS interface, and checks and cleans the abnormality. Multi-source information fusion includes trajectory spatiotemporal information processing and meta-path-based heterogeneous graph construction scheme, which combines trajectory geographic information with semantic information, and builds multiple meta-paths to model structured spatial features. The heterogeneous neural network recommendation module includes an aggregation module and a dynamic interaction module, mining potential user interactions, and using dynamic heterogeneous networks to analyze users' destination preferences. The present invention can perform relatively accurate destination recommendation for the user by analyzing the travel trajectory of the user, and push the result to the user terminal.
Description
technical field [0001] The invention mainly relates to the field of recommendation systems, and mainly relates to a method and system for destination recommendation based on a multi-source heterogeneous information network. Background technique [0002] With the variety of sensor types, the expansion of mobile Internet deployment, and the rapid development of high-performance computing and reliable storage technologies, the extraction of trajectory data has become fast and intelligent. Under the current big data background, scholars understand the relationship between urban crowd movement behavior and spatial structure from the perspectives of groups, dynamics, and time and space, so as to solve various urban application problems, such as navigation services, advertising push, and traffic management. Among them, the location-based recommendation system has become a research hotspot, including Point-of-interest (POI) recommendation, next POI recommendation, destination recomm...
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IPC IPC(8): G06F16/29G06F16/215G06F16/2458G06F16/28G06N3/08
CPCG06F16/29G06F16/2465G06F16/215G06F16/285G06N3/08
Inventor 陈红阳方辉肖竹
Owner ZHEJIANG LAB