PERSPeCT: Collaborative Filtering for Tailored Health Communications

Citation:
Adams, Roy J., Rajani S. Sadasivam, Kavitha Balakrishnan, Rebecca L. Kinney, Thomas K. Houston, and Benjamin M. Marlin. "PERSPeCT: Collaborative Filtering for Tailored Health Communications." Proceedings of the 8th ACM Conference on Recommender Systems. RecSys '14. New York, NY, USA: ACM, 2014. 329-332.

Abstract:

The goal of computer tailored health communications (CTHC) is to elicit healthy behavior changes by sending motivational messages personalized to individual patients. One prominent weakness of many existing CTHC systems is that they are based on expert-written rules and thus have no ability to learn from their users over time. One solution to this problem is to develop CTHC systems based on the principles of collaborative filtering, but this approach has not been widely studied. In this paper, we present a case study evaluating nine rating prediction methods for use in the Patient Experience Recommender System for Persuasive Communication Tailoring, a system developed for use in a clinical trial of CTHC-based smoking cessation support interventions.

Notes:

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