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A Trajectory Clustering Method Based on Semantic Similarity

A technology of semantic similarity and trajectory clustering, applied in instruments, computing, character and pattern recognition, etc., can solve problems such as low efficiency and unreasonable clustering results, so as to improve efficiency, reduce clustering uncertainty, reduce The effect of counting the number of times

Active Publication Date: 2021-08-17
UNIV OF ELECTRONICS SCI & TECH OF CHINA
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Problems solved by technology

[0003] In view of the above research problems, the purpose of the present invention is to provide a trajectory clustering method based on semantic similarity, which solves the problem of low efficiency and unreasonable clustering results when the similarity measure in the prior art is used to mine data. The problem

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  • A Trajectory Clustering Method Based on Semantic Similarity
  • A Trajectory Clustering Method Based on Semantic Similarity
  • A Trajectory Clustering Method Based on Semantic Similarity

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Embodiment Construction

[0041] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0042] A trajectory clustering method based on semantic similarity, the following steps:

[0043] S1. Define the semantic trajectory based on the application field of the data to be mined, and then obtain the semantic trajectory similarity based on the defined semantic trajectory; wherein, the application field of the data to be mined is the social network field including latitude and longitude, scene label, time and weather information , transportation or tourism, and other fields that contain relevant data information.

[0044] The steps of semantic trajectory similarity are as follows:

[0045] S1.1. Given a sequence of semantic trajectories Among them, n is the number of points on the trajectory, is the track First points, Depend on attributes ( , ,..., )composition, Each of the attributes is composed of a distance attrib...

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Abstract

The invention discloses a trajectory clustering method based on semantic similarity, which belongs to the technical field of clustering methods, and solves the problem of low efficiency and unreasonable clustering results when the similarity measure in the prior art is used to mine data. question. The present invention defines semantic trajectories based on the application field of the data to be mined, and then obtains the similarity of semantic trajectories based on the semantic trajectories; given the trajectory training data set, extracts several trajectories, and calculates the similarity based on the defined semantic trajectory similarity using a box diagram degree threshold; cluster the tracks in the track set based on the similarity threshold. The present invention is used for trajectory clustering.

Description

technical field [0001] A trajectory clustering method based on semantic similarity is used for trajectory clustering and belongs to the technical field of clustering methods. Background technique [0002] Similarity measurement is an important research problem in trajectory data analysis. For most trajectory data mining problems, comparison between trajectories is required. Therefore, the complexity of trajectory similarity measurement will directly affect the operation of related technologies. efficiency and feasibility. In the prior art, the similarity measurement is mostly implemented by dynamic programming, which needs to calculate the pairwise distance of all trajectory points, specifically: dynamic programming needs to calculate the distance from each point of each trajectory to all points of all other trajectories, and the time is complicated The degree is very high, O( ), n is the number of points, when the number of trajectories increases a lot, the time required...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N20/20
CPCG06N20/20G06F18/23G06F18/22G06F18/214
Inventor 牛新征刘鹏飞望馨何玲杨胜瀚陈冬子刘鹏鹏王芳姝
Owner UNIV OF ELECTRONICS SCI & TECH OF CHINA
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