{"title":"Surveying Older Adults About a Recommender System for a Digital Library","authors":"Adam Maus, A. Atwood","doi":"10.1145/2732158.2732185","DOIUrl":null,"url":null,"abstract":"We present results from a survey of adults, 63 and older, about the potential implementation of a recommender system within a digital library of health-related content. We studied how these older adults perceive the idea of a recommender system and different aspects of its design. We presented four different types of recommender systems in the survey and our results indicate that this group would prefer a system based on explicit feedback in the form of ratings that measure the helpfulness of content. Reinforcing previous research, we learned this group is interested in a system that explains why it recommended content and they do not want to spend much time creating a profile of interests to warm the system. We discuss where we would use this recommender system, how we designed the survey for our audience, and plans for future studies on this subject.","PeriodicalId":177570,"journal":{"name":"Proceedings of the 20th International Conference on Intelligent User Interfaces Companion","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 20th International Conference on Intelligent User Interfaces Companion","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2732158.2732185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We present results from a survey of adults, 63 and older, about the potential implementation of a recommender system within a digital library of health-related content. We studied how these older adults perceive the idea of a recommender system and different aspects of its design. We presented four different types of recommender systems in the survey and our results indicate that this group would prefer a system based on explicit feedback in the form of ratings that measure the helpfulness of content. Reinforcing previous research, we learned this group is interested in a system that explains why it recommended content and they do not want to spend much time creating a profile of interests to warm the system. We discuss where we would use this recommender system, how we designed the survey for our audience, and plans for future studies on this subject.