顾及用户画像的多源遥感信息智能推荐方法

An intelligent recommendation method of multi-source remote sensing information considering user portrait

近年来,我国各类卫星井喷式发展,随之带来的海量卫星遥感数据保障服务的主动性不够、个性化不足等现实问题日益凸现,严重制约了卫星遥感的多领域智能应用。本文针对该问题,设计了一种顾及用户画像的遥感信息智能推荐方法。首先,构建融时间、空间、载荷、分辨率、产品级别5项核心元素的可扩展主题用户画像模型;然后,对模型中各元素权重、区间长度、分布特征值等进行具体表达,给出解算方法;最后,结合各元素权重及兴趣特征值,计算待分发数据与用户兴趣特征值的关联度,定量解算推荐度,实现遥感数据有序智能推荐。对国家减灾中心和北京市公安局禁毒总队两个用户近3 a实际需求订单的试验结果表明,该模型方法解算构建的各主题元素分布特征符合用户实际应用特点,推荐度较高,平均优于94%。研究成果为工程化实现天基遥感信息个性化服务及智能推荐提供了模型方法。

with the development of military-civilian-commercial satellites in recent years,many practical problems such as the lack of initiative and the lack of personalization in remote sensing data services have becoming increasingly serious,which restrict the intelligent application of remote sensing in multiple fields.Aiming at the problems,this paper designs an active recommendation method of remote sensing information based on user portrait model.Firstly,an extensible user portrait model was constructed that included five theme elements,including time,space,sensor,resolution and product level;Secondly,the weight,interval length and distribution characteristics of each element in the model are expressed and calculated in detail;Finally,combined with the weight and the interest characteristic of each element,the recommendation degree and the correlation degree between the data to be distributed and the interest characteristic value are calculated,so as to realize the ordered active recommendation of remote sensing data.Taking two users of the National Disaster Reduction Center of China and Beijing Anti-drug Brigade as examples,the experimental results based on real demand orders in past three years show that the distribution characteristics of the theme elements can objectively reflect the actual needs of users,and the average recommendation accuracy is better than 94%.The research results provide a model method for engineering realization of remote sensing data personalized service and intelligent recommendation.