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An Exploration On-demand Article Recommender System for Cancer Patients Information Provisioning
Author(s) -
M. Mehdi Afsar,
Trafford Crump,
Behrouz H. Far
Publication year - 2021
Publication title -
proceedings of the ... international florida artificial intelligence research society conference
Language(s) - English
Resource type - Journals
eISSN - 2334-0762
pISSN - 2334-0754
DOI - 10.32473/flairs.v34i1.128339
Subject(s) - computer science , provisioning , recommender system , baseline (sea) , cancer , knowledge management , world wide web , medicine , telecommunications , oceanography , geology
Information provision plays an important role in ed- ucating patients with serious illnesses, like cancer, to cope with their disease conditions and to actively partic- ipate in shared-decision making process. Recent stud- ies suggest that there is a lack of appropriate educa- tional resources for such patients, specifically prostate cancer patients. To address this issue, in this paper, a Knowledge-based Exploration on-demand article Rec- ommender System (called KERS) is proposed that can provide evidence-based information for patients. Rec- ognizing 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 knowledge- base developed by an expert in the field, KERS learns user interests as quickly as possible and then it ex- ploits 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 de- cisions, 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.

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