Social network user position feature extraction method and device based on Mean shift and K-means clustering

• Main Authors: LYU CHAOPING, HE XU, WANG HAIYAN, SHI YINGJI
• Format: Patent
• Language: Chinese; English
• Published: 29.01.2021
• Subjects: CALCULATING; COMPUTING; COUNTING; DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES; ELECTRIC DIGITAL DATA PROCESSING; HANDLING RECORD CARRIERS; PHYSICS; PRESENTATION OF DATA; RECOGNITION OF DATA; RECORD CARRIERS; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR

The invention discloses a social network user position feature extraction method and device based on a Meanshift and K-means algorithm, and the method is used for solving a problem that a higher hot spot region, i.e., a position where a user is truly interested, in user sign-in frequency is found in massive user sign-in data. The implementation process of the method comprises the following steps:firstly, analyzing and preprocessing user sign-in data collected from a Flickr platform, selecting an area with dense and typical sign-in points as a research area, and then carrying out preliminary clustering on the sign-in data in a certain city range based on a Meanshift method; and carrying out secondary clustering on the screened large-scale clusters and excessively dense clusters based on aK-means method, and finally, according to a clustering result, carrying out division to corresponding POIs (Point of Interest), thereby completing user position feature extraction. By adopting the method provided by the invent