Abstract
A multi-aspect tourism information perception method based on multi-source social media data fusion was proposed in order to improve the efficiency of travel knowledge acquisition and provide effective travel assistance for users. A cross-media multi-aspect correlation approach was proposed to connect fragmented travel information after a preprocessing step for the heterogeneous travel related data, which resorted to the “scene-feature characterization” in order to make a multi-aspect characterization. The perception method mined typical travel route from historical travelogues based on the sequential pattern mining, which can be regarded as the recommended route. Connecting cross-media information was based on the similarity between the reviews and the image contexts. Results of experiments over a dataset of eight domestic popular scenic spots, which was collected from Dazhongdianping and Mafengwo, indicate that the approach makes a fine-grained characterization for the scenic spots and the provided travel route can meet different users' needs.
| Original language | English |
|---|---|
| Pages (from-to) | 663-668 |
| Number of pages | 6 |
| Journal | Zhejiang Daxue Xuebao (Gongxue Ban)/Journal of Zhejiang University (Engineering Science) |
| Volume | 51 |
| Issue number | 4 |
| DOIs | |
| State | Published - 1 Apr 2017 |
Keywords
- Crowd intelligence
- Intelligent recommendation
- Multi-aspect characterization
- Scenic spot profiling
- Social media data fusion