HealthRecSys: A semantic content-based recommender system to complement health videos.
HealthRecSys: A semantic content-based recommender system to complement health videos.
复制标题
DOI：
10.1186/s12911-017-0431-7
复制
发表时间：
2017-05-15
影响因子：
3.5
通讯作者：
Fernandez-Luque L
中科院分区：
文献类型：
--
作者：
Sanchez Bocanegra CL;Sevillano Ramos JL;Rizo C;Civit A;Fernandez-Luque L
互联网及其普及继续以前所未有的速度增长。在线观看视频非常流行;据估计，每分钟有500小时的视频上传到YouTube（一种视频共享服务），到2019年，视频格式将占互联网流量的80%以上。与健康相关的视频在YouTube上非常受欢迎，但其质量始终是一个令人担忧的问题。提高在线视频质量的一种方法是提供额外的教育健康内容，例如网站，以支持健康消费者。本研究探讨了建立一个基于内容的推荐系统的可行性，该系统将健康消费者与来自MedlinePlus的知名健康教育网站联系起来，用于从YouTube获取给定的健康视频。本研究的数据集包括一系列与健康相关的视频及其可用元数据。语义技术（如SNOMED-CT和生物本体）被用来推荐来自MedlinePlus的健康网站。共有26名健康专业人员参与评估了253个推荐链接，共53个关于一般健康，高血压或糖尿病的视频。MedlinePlus推荐的健康网站与视频的相关性使用信息检索指标进行测量，例如标准化折扣累积增益和K处的精度。我们的系统推荐的大多数健康视频网站都是相关的，基于健康专业人员的评级。不同主题的归一化贴现累积收益在46%至90%之间。我们的研究证明了使用基于语义内容的推荐系统来丰富YouTube健康视频的可行性。除了医疗保健专业人员外，还需要对最终用户进行评估，以确定在非模拟信息搜索环境中对这些建议的接受程度。本文的在线版本（doi：10.1186/s12911-017-0431-7）包含补充材料，可供授权用户使用。
The Internet, and its popularity, continues to grow at an unprecedented pace. Watching videos online is very popular; it is estimated that 500 h of video are uploaded onto YouTube, a video-sharing service, every minute and that, by 2019, video formats will comprise more than 80% of Internet traffic. Health-related videos are very popular on YouTube, but their quality is always a matter of concern. One approach to enhancing the quality of online videos is to provide additional educational health content, such as websites, to support health consumers. This study investigates the feasibility of building a content-based recommender system that links health consumers to reputable health educational websites from MedlinePlus for a given health video from YouTube. The dataset for this study includes a collection of health-related videos and their available metadata. Semantic technologies (such as SNOMED-CT and Bio-ontology) were used to recommend health websites from MedlinePlus. A total of 26 healths professionals participated in evaluating 253 recommended links for a total of 53 videos about general health, hypertension, or diabetes. The relevance of the recommended health websites from MedlinePlus to the videos was measured using information retrieval metrics such as the normalized discounted cumulative gain and precision at K. The majority of websites recommended by our system for health videos were relevant, based on ratings by health professionals. The normalized discounted cumulative gain was between 46% and 90% for the different topics. Our study demonstrates the feasibility of using a semantic content-based recommender system to enrich YouTube health videos. Evaluation with end-users, in addition to healthcare professionals, will be required to identify the acceptance of these recommendations in a nonsimulated information-seeking context. The online version of this article (doi:10.1186/s12911-017-0431-7) contains supplementary material, which is available to authorized users.