A Smart Tourism Recommendation Algorithm Based on Cellular Geospatial Clustering and Multivariate Weighted Collaborative Filtering
Bibliographic Data
| ID | 22033540 |
|---|---|
| Authors | Xiao Zhou (0000-0003-3445-306X, Sichuan University), Jiangpeng Tian (0000-0002-6158-499X, PLA Information Engineering University, corresponding author), Jian Peng (0000-0003-0332-0248, Sichuan University), Mingzhan Su (0000-0003-4205-9812, PLA Information Engineering University) |
| Year | 2021 |
| Volume | 10 |
| Issue | 9 |
| Pages | 628 |
| Publication date | 2021-09-19 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi10090628 |
| OpenAlex | W3201408774 |
| Language | EN |
| Citations received | 1 |
| References cited | 27 |
Tourist attraction and tour route recommendation are the key research highlights in the field of smart tourism. Currently, the existing recommendation algorithms encounter certain problems when making decisions regarding tourist attractions and tour routes. This paper presents a smart tourism recommendation algorithm based on a cellular geospatial clustering and weighted collaborative filtering. The problems are analyzed and concluded, and then the research ideas and methods to solve the problems are introduced. Aimed at solving the problems, the tourist attraction recommendation model is set up based on a cellular geographic space generating model and a weighted collaborative filtering model. According to the matching degree between the tourists’ interest needs and tourist attraction feature attributes, a precise tourist attraction recommendation is obtained. In combination with the geospatial attributes of the tourist destination, the spatial adjacency clustering model based on the cellular space generating algorithm is set up, and then the weighted model is introduced for the collaborative filtering recommendation algorithm, which ensures that the recommendation result precisely matches the tourists’ needs. Providing precise results, the optimal tour route recommendation model based on the precise tourist attraction approach vector algorithm is set up. The approach vector algorithm is used to search the optimal route between two POIs under the condition of multivariate traffic modes to provide the tourists with the best motive benefits. To verify the feasibility and advantages of the algorithm, this paper designs a sample experiment and analyzes the resulting data to obtain the relevant conclusion
Algorithm · Cluster analysis · Collaborative filtering · Data mining · Geography · Geospatial analysis · Information retrieval · Machine learning · Recommender system · Tourism · Computer Science · Digital Marketing and Social Media · Diverse Aspects of Tourism Research · E-commerce and Technology Innovations
| Citations per year | 0.33 |
|---|---|
| Citation span | 2023 - 2023 (1) |
| Highly cited | No |