Vector model-based massive spatiotemporal data retrieval method and system

A space-time data and vector model technology, applied in the field of data processing, can solve problems such as wasting computing resources and reducing processing speed, and achieve the effects of reducing data volume, improving retrieval speed, and reducing computational complexity

Inactive Publication Date: 2017-05-10
SOUTH CHINA NORMAL UNIVERSITY
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Problems solved by technology

However, if it is processed directly without adopting measures such as optimized cache, the effect will be better than that of traditional databases, but some data will be proces...

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  • Vector model-based massive spatiotemporal data retrieval method and system
  • Vector model-based massive spatiotemporal data retrieval method and system

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Embodiment Construction

[0034] refer to figure 1 , the present invention a kind of massive spatio-temporal data retrieval method based on vector model, comprises the following steps:

[0035] Vectorize the data of event space and problem space to obtain spatiotemporal data vectors;

[0036] According to the target condition vector to be retrieved, the spatio-temporal data vector is subjected to dimensionality reduction processing;

[0037] Carry out vector operations on each dimension of the space-time data vector after dimension reduction processing and the target condition vector;

[0038] Judging the vector operation results, screening out the vector operation results that meet the preset conditions, and obtaining the corresponding retrieval results.

[0039] As a further preferred embodiment, the spatio-temporal data vector includes a time point attribute dimension, a time segment attribute dimension, a basic spatial attribute dimension and a derived spatial attribute dimension. Among them, th...

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Abstract

The invention discloses a vector model-based massive spatiotemporal data retrieval method and system. The method comprises the steps of performing vectorization processing on data of event space and problem space to obtain a spatiotemporal data vector; performing dimension reduction processing on the spatiotemporal data vector according to a target condition vector needed to be retrieved; performing vector operation on each dimension of the spatiotemporal data vector subjected to the dimension reduction processing and the target condition vector; and judging vector operation results, screening out the vector operation results meeting a preset condition, and obtaining corresponding retrieval results. The system comprises a spatiotemporal data vector representation module, a spatiotemporal data vector dimension reduction module, a spatiotemporal data vector operation module and a retrieval result judgment module. According to the method and the system, the to-be-queried data volume can be reduced, the calculation complexity is greatly lowered, and the retrieval efficiency is effectively improved. The method and the system can be widely applied to the field of retrieval.

Description

technical field [0001] The invention relates to the technical field of data processing, in particular to a method and system for retrieving massive spatio-temporal data based on a vector model. Background technique [0002] In today's big data era, in the face of so much data, returning query results within a reasonable time to help decision-making has become an urgent problem to be solved. For example, when a police officer locates a criminal suspect during criminal investigation and solving a case, he or she can use massive data such as tourism, airlines, and railways to find out the suspected gang of the criminal suspect based on the possible potential relationship with the criminal suspect. member. In this scenario, the mining of potential relationships is mostly related to criminal suspects in time or space. The public security department has tens of billions of data, and the data formats involve tables, texts, etc. In such a massive Among various forms of data, disco...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/2455G06F16/2237G06F16/27
Inventor 赵淦森李振宇廖智锐张奇支王欣明庄序填聂瑞华吴杰超任雪琦
Owner SOUTH CHINA NORMAL UNIVERSITY
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