Title
Context-Aware Matrix Factorization for the Identification of Urban Functional Regions with POI and Taxi OD Data
Abstract
The identification of urban functional regions (UFRs) is important for urban planning and sustainable development. Because this involves a set of interrelated processes, it is difficult to identify UFRs using only single data sources. Data fusion methods have the potential to improve the identification accuracy. However, the use of existing fusion methods remains challenging when mining shared semantic information among multiple data sources. In order to address this issue, we propose a context-coupling matrix factorization (CCMF) method which considers contextual relationships. This method was designed based on the fact that the contextual relationships embedded in all of the data are shared and complementary to one another. An empirical study was carried out by fusing point-of-interest (POI) data and taxi origin-destination (OD) data in Beijing, China. There are three steps in CCMF. First, contextual information is extracted from POI and taxi OD trajectory data. Second, fusion is performed using contextual information. Finally, spectral clustering is used to identify the functional regions. The results show that the proposed method achieved an overall accuracy (OA) of 90% and a kappa of 0.88 in the study area. The results were compared with the results obtained using single sources of non-fused data and other fusion methods in order to validate the effectiveness of our method. The results demonstrate that an improvement in the OA of about 5% in comparison to a similar method in the literature could be achieved using this method.
Year
DOI
Venue
2022
10.3390/ijgi11060351
ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION
Keywords
DocType
Volume
urban functional regions, identification, matrix factorization, POI data, OD trajectory data
Journal
11
Issue
ISSN
Citations 
6
2220-9964
0
PageRank 
References 
Authors
0.34
0
7
Name
Order
Citations
PageRank
Changfeng Jing112.04
Yanru Hu200.34
Hongyang Zhang300.68
Mingyi Du411.03
Shishuo Xu501.35
Xian Guo601.01
Jie Jiang722.74