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Mining User Mobility Features for Next Place Prediction in Location-Based Services.

, , , and . ICDM, page 1038-1043. IEEE Computer Society, (2012)

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The Wisdom of the Few: A Collaborative Filtering Approach Based on Expert Opinions from the Web, , , , and . Proceedings of the 32Nd International ACM SIGIR Conference on Research and Development in Information Retrieval, page 532--539. New York, NY, USA, ACM, (2009)Temporal Defenses for Robust Recommendations., , and . PSDML, volume 6549 of Lecture Notes in Computer Science, page 64-77. Springer, (2010)Mobile-Based Experience Sampling for Behaviour Research., , , and . Emotions and Personality in Personalized Services, Springer, (2017)Measuring the impact of opening the London shared bicycle scheme to casual users, , and . Transportation research part C: emerging technologies, (2012)When User Experience Designers Partner with Data Scientists., and . AAAI Spring Symposia, AAAI Press, (2017)Bootstrapping a Destination Recommender System.. RecSys, page 341. ACM, (2017)Contextual dissonance: design bias in sensor-based experience sampling methods., , , and . UbiComp, page 183-192. ACM, (2013)Trust-Based Collaborative Filtering., , and . IFIPTM, volume 263 of IFIP Advances in Information and Communication Technology, page 119-134. Springer, (2008)Collaborative Filtering With Adaptive Information Sources, , and . (2009)Explores ways of adding "external" rating sources from experts in order to improve collaborative filtering results. Nearest neighbors does not seem to be always the optimal choice..How smart is your smartcard?: measuring travel behaviours, perceptions, and incentives., and . UbiComp, page 291-300. ACM, (2011)