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- Title
A Convolutional Neural Network and Matrix Factorization-Based Travel Location Recommendation Method Using Community-Contributed Geotagged Photos.
- Authors
Ameen, Thaair; Chen, Ling; Xu, Zhenxing; Lyu, Dandan; Shi, Hongyu
- Abstract
Travel location recommendation methods using community-contributed geotagged photos are based on past check-ins. Therefore, these methods cannot effectively work for new travel locations, i.e., they suffer from the travel location cold start problem. In this study, we propose a convolutional neural network and matrix factorization-based travel location recommendation method to address the problem. Specifically, a weighted matrix factorization method is used to obtain the latent factor representations of travel locations. The latent factor representation for a new travel location is estimated from its photos by using a convolutional neural network. Experimental results on a Flickr dataset demonstrate that the proposed method can provide better recommendations than existing methods.
- Subjects
CONVOLUTIONAL neural networks; MATRIX decomposition; COMMUTING; TRAVEL
- Publication
ISPRS International Journal of Geo-Information, 2020, Vol 9, Issue 8, p464
- ISSN
2220-9964
- Publication type
Article
- DOI
10.3390/ijgi9080464