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User Preference Elicitation, Rating Sparsity and Cold Start.

, , , and . Collaborative Recommendations, WorldScientific, (2018)

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Recommendations with Optimal Combination of Feature-Based and Item-Based Preferences., , and . UMAP, page 269-273. ACM, (2016)Selective contextual information acquisition in travel recommender systems., and . J. Inf. Technol. Tour., 17 (1): 5-29 (2017)Techniques for cold-starting context-aware mobile recommender systems for tourism., , and . Intelligenza Artificiale, 8 (2): 129-143 (2014)STS: Design of Weather-Aware Mobile Recommender Systems in Tourism., , , , and . AI*HCI@AI*IA, volume 1125 of CEUR Workshop Proceedings, CEUR-WS.org, (2013)Hybridisation techniques for cold-starting context-aware recommender systems.. RecSys, page 405-408. ACM, (2014)Hybrid Solution of the Cold-Start Problem in Context-Aware Recommender Systems.. UMAP, volume 8538 of Lecture Notes in Computer Science, page 484-489. Springer, (2014)User Personality and the New User Problem in a Context-Aware Point of Interest Recommender System., , and . ENTER, page 537-549. Springer, (2015)User Preference Elicitation, Rating Sparsity and Cold Start., , , and . Collaborative Recommendations, WorldScientific, (2018)Switching hybrid for cold-starting context-aware recommender systems., , and . RecSys, page 349-352. ACM, (2014)Personality-Based Active Learning for Collaborative Filtering Recommender Systems., , , and . AI*IA, volume 8249 of Lecture Notes in Computer Science, page 360-371. Springer, (2013)