Next Location Recommendation: A Multi-context Features Integration Perspective Article Swipe
Xuemei Wei
,
Chunli Liu
,
Yezheng Liu
,
Yang Li
,
Kai Zhang
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-2120726/v1
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.21203/rs.3.rs-2120726/v1
Next location recommendation aims to mine users’ historical trajectories to predict their potentially preferred locations in the next moment. Although previous studies have explored the idea of incorporating location or social contextual information for recommendation, they still suffer from several major limitations: (1) not fully considering the semantic associations between locations, (2) not considering the heterogeneity in preferences of socially linked users, (3) not fully utilizing contextual information from distinctive sources to further improve the recommendation performance. In this paper, we propose a novel multi-context-based next location recommendation model that incorporates location context, trajectory context, and social context to obtain comprehensive users’ preferences while allowing for interactions between contexts. Specifically, we first develop an efficient method combining both high-order location graphs and location semantic graphs to characterize subtle associations between locations. Then we explore the social contextual information and introduce the location subgraph which considers heterogeneous preferences among friends. Finally, we use the LSTM and geo-dilated LSTM to capture the spatio-temporal associations between users’ trajectories and integrate various contextual information to improve model performance. Extensive experiments on three real datasets show that our model has superior results in the next location recommendation task over other baselines.
Related Topics
Concepts
Computer science
Context (archaeology)
Perspective (graphical)
Recommender system
Information retrieval
Trajectory
Data science
Task (project management)
Machine learning
Spatial contextual awareness
Data mining
Artificial intelligence
World Wide Web
Geography
Archaeology
Physics
Economics
Astronomy
Management
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.21203/rs.3.rs-2120726/v1
- https://www.researchsquare.com/article/rs-2120726/latest.pdf
- OA Status
- green
- Cited By
- 1
- References
- 42
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4304778072
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4304778072Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.21203/rs.3.rs-2120726/v1Digital Object Identifier
- Title
-
Next Location Recommendation: A Multi-context Features Integration PerspectiveWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-10-12Full publication date if available
- Authors
-
Xuemei Wei, Chunli Liu, Yezheng Liu, Yang Li, Kai ZhangList of authors in order
- Landing page
-
https://doi.org/10.21203/rs.3.rs-2120726/v1Publisher landing page
- PDF URL
-
https://www.researchsquare.com/article/rs-2120726/latest.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.researchsquare.com/article/rs-2120726/latest.pdfDirect OA link when available
- Concepts
-
Computer science, Context (archaeology), Perspective (graphical), Recommender system, Information retrieval, Trajectory, Data science, Task (project management), Machine learning, Spatial contextual awareness, Data mining, Artificial intelligence, World Wide Web, Geography, Archaeology, Physics, Economics, Astronomy, ManagementTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2024: 1Per-year citation counts (last 5 years)
- References (count)
-
42Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| publication_date | 2022-10-12 |
| publication_year | 2022 |
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