ricochet: context and complementarity-aware, ontology-based pois recommender system
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- 1. Ricochet: Context and Complementarity-Aware, Ontology-based POIs Recommender System Chun Lu, Philippe Laublet, Milan Stankovic SALAD 2014 May 26th, 2014 Crete, Greece
- 2. Outline Introduction Ricochet system Evaluation Conclusion
- 3. Introduction Point of interest (POI) Increasing popularity of POIs recommender systems Dissatisfaction with recommendations of existing systems
- 4. Whats wrong?
- 5. Whats wrong? Before & after a check-in, recommendations remain unchanged. Research questions User study
- 6. Ricochet System Criteria Contextual criteria Intrinsic criteria Criteria of complementarity
- 7. Ricochet System Criteria of complementarity Each POI category is mapped to a particular feeling. [Savage et al., 2012] Arts & Entertainment = "feeling artsy" Nightlife = "feeling like a party animal" College & Education = "feeling nerdy" Great Outdoors = "feeling outdoorsy" Food = "feeling hungry" Shops = "feeling shopaholic"
- 8. Ricochet System Criteria of complementarity Having a certain feeling Go to a certain POI Visit a POI Having a certain feeling Just-visited POI causes a feeling Going-to POI satisfies it
- 9. Ricochet System Criteria of complementarity Physical activities possess a specific assessable intensity. [Tapia et al., 2007] Intensity of expressiveness Cognitive, emotional, physical POIs classified into four intensity levels Daily life = alternation of different intensities
- 10. Ricochet System Sample of OntoPOI
- 11. Ricochet System Recommendation engine API : Yelp & Jena & Google Maps
- 12. Evaluation Two versions of Ricochet Process Metrics: precision, recall, normalized Discounted Cumulative Gain
- 13. Results The complementarity improves the relevance of the recommendations.
- 14. Conclusion & Future work Ricochet : improve the relevance by considering the complementarity Refine the complementarity Integrate to existing systems
- 15. Questions & Answers Thanks for your attention! Any questions?
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