Recommendation of Tourist Attractions and Route Based on Social Network Data Mining
- Resource Type
- Conference
- Authors
- Lou, Chao; Yang, Xi; Jin, Xingchen
- Source
- 2023 IEEE International Conference on Electrical, Automation and Computer Engineering (ICEACE) Electrical, Automation and Computer Engineering (ICEACE), 2023 IEEE International Conference on. :558-565 Dec, 2023
- Subject
- Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Web services
Transportation
Information filters
Classification algorithms
Data mining
Web sites
Recommender systems
Data Mining
Travel Recommendation
Text Classification
TF-IDF
CFC
- Language
Since growing travellers’ more and more preferring customisation service, this project indicates that such application is more user-oriented and more particular in personal preferences. Through extracting users’ posted geotagged photos and their information from photo sharing website supported by Flickr API. And we design a content filtering algorithm and improve existed TF-IDF algorithm to get user profile before listing travel suggestions via Yelp API and simulated a graphical route for reference by Google API. As a result, a travel recommendation system based on users' travel preferences excavated from social platform photos is achieved. According to the average accuracy rate (MAP) verification, the CFC algorithm used in this study performs better than the LC and CA algorithms in recommending popular scenic spots.