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Traffic knowledge graph construction method based on cross-media data

A knowledge map and construction method technology, applied in the field of data analysis and state management, can solve the problems of limited information, different storage methods and data formats, difficult storage and utilization, etc., to achieve wide application, convenient manipulation of traffic data, and improve the effect Effect

Pending Publication Date: 2020-12-15
TONGJI UNIV
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  • Abstract
  • Description
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AI Technical Summary

Problems solved by technology

Due to the variety of sources of traffic data, their own forms and types are different, so the respective storage methods and data formats are different, it is difficult to store and utilize in a unified way, and from the nature of traffic data, the data of a single media can only be obtained Information on the one hand, the amount of information is very limited

Method used

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  • Traffic knowledge graph construction method based on cross-media data
  • Traffic knowledge graph construction method based on cross-media data
  • Traffic knowledge graph construction method based on cross-media data

Examples

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Embodiment 1

[0050] Such as figure 1 with figure 2As shown, a traffic knowledge map construction method based on cross-media data integrates cross-media traffic data into an organic whole, and builds the relationship between cross-media traffic data, making the application of traffic data more extensive, including The following steps:

[0051] Step S1: Obtain and process multi-source heterogeneous traffic raw data;

[0052] Step S2: Transform raw traffic data into traffic entities through knowledge representation and knowledge storage methods, form a preliminary traffic knowledge graph and store it in the graph database;

[0053] Step S3: Through the method of knowledge fusion and knowledge reasoning, correlate and expand the preliminary traffic knowledge map to form a cross-domain traffic knowledge map based on cross-media data.

[0054] Traffic raw data include floating car GPS speed data and traffic accident text data.

[0055] The GPS speed data of the floating car is structured d...

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Abstract

The invention relates to a traffic knowledge graph construction method based on cross-media data. The method specifically comprises the following steps of S1, obtaining and processing multi-source heterogeneous traffic original data; S2, converting the traffic original data into traffic entities through a knowledge representation and knowledge storage method to form a preliminary traffic knowledgegraph, and storing the preliminary traffic knowledge graph in a graph database; and S3, associating and expanding the preliminary traffic knowledge graph through a knowledge fusion and knowledge reasoning method to form a cross-domain traffic knowledge graph based on cross-media data. Compared with the prior art, the invention has the advantages that the traffic data processing efficiency is improved, the application of the traffic data is wider, and the practicability and the high efficiency are better.

Description

technical field [0001] The invention relates to the field of data analysis and state management, in particular to a method for constructing a traffic knowledge graph based on cross-media data. Background technique [0002] Knowledge graphs, as a formalized description framework using relatively common semantic knowledge, are being used on a large scale in various fields. The general representation method of the knowledge map is a structured triple, that is, G=(E, R, S), where E represents a set of entities, R represents a set of relationships, and S represents a set of triples. Triples are used to describe the head entity, tail entity and the relationship between the facts in a specific domain. [0003] The advantage of the knowledge graph is that its description form is unified, which facilitates the integration and fusion of different types of knowledge. In the current big data era, the trend of multi-source data is obvious. If you want to use big data, you must unify it...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/36G06F16/35G06K9/62G08G1/01
CPCG06F16/367G06F16/35G08G1/0125G08G1/0133G06F18/2321
Inventor 李健徐晨捷
Owner TONGJI UNIV
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