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ISPRS Int. J. Geo-Inf. 2018, 7(2), 40;

A Space-Time Periodic Task Model for Recommendation of Remote Sensing Images

1,2, 3 and 1,2,*
School of Resource and Environment Science, Wuhan University, Wuhan 430079, China
Chinese Academy of Surveying and Mapping, Beijing 100830, China
Alibaba Group, Hangzhou 311121, China
Author to whom correspondence should be addressed.
Received: 31 October 2017 / Revised: 14 January 2018 / Accepted: 21 January 2018 / Published: 29 January 2018
(This article belongs to the Special Issue Machine Learning for Geospatial Data Analysis)
PDF [4741 KB, uploaded 29 January 2018]


With the rapid development of remote sensing technology, the quantity and variety of remote sensing images are growing so quickly that proactive and personalized access to data has become an inevitable trend. One of the active approaches is remote sensing image recommendation, which can offer related image products to users according to their preference. Although multiple studies on remote sensing retrieval and recommendation have been performed, most of these studies model the user profiles only from the perspective of spatial area or image features. In this paper, we propose a spatiotemporal recommendation method for remote sensing data based on the probabilistic latent topic model, which is named the Space-Time Periodic Task model (STPT). User retrieval behaviors of remote sensing images are represented as mixtures of latent tasks, which act as links between users and images. Each task is associated with the joint probability distribution of space, time and image characteristics. Meanwhile, the von Mises distribution is introduced to fit the distribution of tasks over time. Then, we adopt Gibbs sampling to learn the random variables and parameters and present the inference algorithm for our model. Experiments show that the proposed STPT model can improve the capability and efficiency of remote sensing image data services. View Full-Text
Keywords: remote sensing images; recommendation; topic model; user preference remote sensing images; recommendation; topic model; user preference

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Zhang, X.; Chen, D.; Liu, J. A Space-Time Periodic Task Model for Recommendation of Remote Sensing Images. ISPRS Int. J. Geo-Inf. 2018, 7, 40.

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