INTELLIGENT SERVICE PUSH METHOD BASED ON ACTIVE GEOGRAPHIC PERCEPTION

• Published in: International archives of the photogrammetry, remote sensing and spatial information sciences. remote sensing and spatial information sciences., 2020-02, Vol.XLII-3/W10, p.245-248
• Main Authors: Jiang, J. W., Li, J. W., Wei, J. S., Su, Z. P.
• Format: Article
• Language: English
• Subjects: Feature extraction; Methods; Motivation; Perception; Real time; Retrieval
• ISSN: 2194-9034; 1682-1750; 2194-9034
• DOI: 10.5194/isprs-archives-XLII-3-W10-245-2020

In view of the lack of consideration of user behavior motives in traditional personalized precision service systems, the accuracy of service content is not high.In order to solve this problem, research on personalized accurate service push method based on active geographic perception. By constructing a geographic feature information model, get the characteristics of the user's destination in real time, and then infer the user's behavioral motivation. Focusing on active geographic awareness technology and personalized precision service methods, the concept, principle, process and key technologies of active geographic sensing are studied, determined the main research content of active geographic perception and the relationship. Then analyze and discuss the construction method of active geographic awareness architecture, developed a geographic feature content system and studied its extraction and weight calculation methods. By the way, according to the characteristics of active geo-sensing, an active awareness API conforming to high efficiency and real-time is designed. Then explored the personalized accurate service push method based on active geographic perception,designed three processes of geographic awareness, service retrieval and service push, a service retrieval and delivery method is proposed. Finally, a personalized precise service system based on active geographical perception is designed. By adding geographic features to the personalized precision service, it can make up for the lack of service personalization and lack of precision caused by ignoring user motivation, which provides a new idea for more accurate and personalized service push.