辅助:卵巢癌患者和护理人员的互动推荐系统

Proceedings of the 16th ACM Conference on Recommender Systems Pub Date : 2022-09-18 DOI:10.1145/3523227.3551471

Behnam Rahdari, Peter Brusilovsky, Daqing He, Khushboo Thaker, Zhimeng Luo, Young ji Lee

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引用次数: 3

摘要

向卵巢癌患者及其护理人员推荐在线资源是一项具有挑战性的任务。一方面，推荐的项目必须是相关的、最近的和可靠的。另一方面，它们需要与用户对特定疾病的卫生知识水平相匹配。在这个演示中，我们描述了HELPeR的整体架构和关键组件，这是一个针对卵巢癌患者及其护理人员的知识自适应交互式推荐系统。

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HELPeR: An Interactive Recommender System for Ovarian Cancer Patients and Caregivers

Recommending online resources to patients with ovarian cancer and their caregivers is a challenging task. On one hand, the recommended items must be relevant, recent, and reliable. On the other hand, they need to match the user’s levels of disease-specific health literacy. In this demonstration, we describe the overall architecture and key components of HELPeR, a knowledge-adaptive interactive recommender system for ovarian cancer patients and their caregivers.

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Proceedings of the 16th ACM Conference on Recommender Systems

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