An Exploration On-demand Article Recommender System for Cancer Patients Information Provisioning

Abstract

Information provision plays an important role in educating patients with serious illnesses, like cancer, to cope with their disease conditions and to actively participate in shared-decision making process. Recent studies suggest that there is a lack of appropriate educational resources for such patients, specifically prostate cancer patients. To address this issue, in this paper, a Knowledge-based Exploration on-demand article Recommender System (called KERS) is proposed that can provide evidence-based information for patients. Recognizing the fact that exploration is expensive when the user of the system is a human, the main idea in KERS is to minimize exploration while achieving the maximum long-term satisfaction. Therefore, using a knowledgebase developed by an expert in the field, KERS learns user interests as quickly as possible and then it exploits this knowledge to recommend the best articles. Furthermore, KERS needs no information from users beforehand and it learns them through interacting with users. The system will help patients make informed decisions, and at the same time, will reduce the burden on the healthcare providers. The results of experiments have confirmed the effectiveness of the proposed system compared to baseline methods.