Personalized recommendation method for remote sensing satellite data

Abstract

The invention belongs to a recommendation method, and particularly relates to a remote sensing satellite data personalized recommendation method. The method comprises the following steps: firstly, obtaining satellite description information, user information and priori knowledge between user industries and data types by constructing a satellite resource pool and an expert knowledge base; then, according to the user information and the recent behavior data of the user, sorting the remote sensing satellite data by adopting a comprehensive recommendation algorithm to obtain a recommended data list; and finally, recommending the satellite data meeting the requirements of the user or being interested by the user to the user. The remote sensing satellite data recommendation system has the remarkable effects that (1) by utilizing the remote sensing satellite data recommendation system, a user does not need to provide clear input; and (2) by analyzing historical behaviors or working fields of the user, data capable of meeting requirements and interests are actively recommended to the user, continuous and personalized services are provided, a data interaction mechanism is converted, and the problem of reliability of remote sensing satellite data services is solved.

Description

technical field [0001] The invention belongs to a recommendation method, in particular to a remote sensing satellite data personalized recommendation method. Background technique [0002] As an important basic resource, remote sensing satellite data are widely used in many fields such as national defense, economy, transportation, energy, and environmental protection. Remote sensing satellite data has the characteristics of massive, multi-source, heterogeneous, etc. The specific description is as follows: First, satellite data cover a wide range and time span, and a large amount of historical remote sensing satellite data has been accumulated. At the same time, thousands of satellites are flying over the earth , carrying various model loads, new remote sensing satellite data are generated every moment, and more and more satellites are launched into the sky, resulting in an explosive growth in data volume. Second, there are various sources of remote sensing satellite data, in...

AI Technical Summary

Problems solved by technology

The third is that satellite data has observation periodicity, and can conduct long-term observations of the same area from different angles. However, remote sensing data from different satellite sources are different in storage formats, organization methods, metadata standards, and many other aspects. Traditional data management It is difficult to realize the overall management of multi-source satellite data, and it is difficult to meet the needs of personalized data customization

This traditional remote sensing satellite data service requires users to have certain professional knowledge, which limits the scope of remote sensing data sharing to a certain extent; and as the volume of data increases, it is difficult to guarantee the accuracy of data by this passive retrieval method and timeliness, leading to an increasingly imbalance between remote sensing information processing capabilities and data acquisition capabilities

In addition, a large amount of accumulated historical data has not been effectively utilized, occupying limited storage space for a long time, and exacerbated the "overload" of remote sensing satellite data

Images