HELPeR - Health e-Librarian with Personalized Recommender
As the Internet has become a prominent source of health information to guide patients’ decision-making and self-management activities, patients strongly indicate they need navigational support to locate appropriate information on the Internet. The overall goal of this project is to build and implement a “Health E-Librarian with Personalized Recommendations (HELPeR)” - a personalized information access system with a hybrid recommender engine that adapts to different aspects of the patient: information needs based on the user’s profile, the user’s uniquely expressed information interests, and the level of user’s disease-related knowledge. The overall goal of our project is to build and implement a “Health E-Librarian with Personalized Recommendations (HELPeR)”, a personalized digital librarian that provides individualized, reliable online information relevant to the patient’s needs, interests, and knowledge across the disease trajectory.
This study is funded by NIH through the National Library of Medicine by grant R01-LM013038-02 (2019 - 2023).
Contents
Research Team
This project is a collaboration between the School of Nursing and the School of Computing and Information, University of Pittsburgh.
School of Computing and Information Team
- PI: Daqing He, Peter Brusilovsky
- Graduate researchers: Khushboo Thaker, Zhenmin Hong, Zhendong Wang, Behnam Rahdari, Mohammad Hassany
School of Nursing
- PI: Young Ji Lee, Heidi Donovan
- Postdoctoral researchers: Susan Birkhoff, Leah Rosenblum
- Graduate researchers: Yu Chi, Vivian Hui, Youjia Wang,
University Library System
SP: Mary Lou Klem
Project Home Page
For a detailed description of our vision and goals, see the [home page of the project http://www.pitt.edu/~dah44/helper/]
