TinderBook:爱上文化TinderBook: Fall in Love with Culture |
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课程网址: | http://videolectures.net/eswc2019_buzio_tinderbook_love/ |
主讲教师: | Alberto Buzio |
开课单位: | ISMB-Istituto Superiore Mario Boella |
开课时间: | 2019-09-19 |
课程语种: | 英语 |
中文简介: | 每年出版的新书超过200万本,在众多的可用选项中选择一本好书是一项具有挑战性的工作。推荐系统通过根据用户阅读历史提供个性化建议,帮助选择书籍。然而,大多数图书推荐系统都是基于协作过滤的,涉及一个漫长的入职流程,需要对许多图书进行评级,然后才能提供好的推荐。Tinderbook通过一个基于卡片的好玩的用户界面,提供用户喜欢的一本书的书籍推荐,该界面不需要创建帐户。Tinderbook深深植根于语义技术,使用DBpedia知识图来丰富书籍描述,并扩展混合式最新知识图嵌入算法,以推导冷启动建议的项目相关度度量。Tinderbook是公开的,已经引起了公众的兴趣,包括热情的读者、学生、图书馆员和研究人员。在线评估表明,Tinderbook几乎达到了推荐精度的50%。 |
课程简介: | More than 2 millions of new books are published every year and choosing a good book among the huge amount of available options can be a challenging endeavor. Recommender systems help in choosing books by providing personalized suggestions based on the user reading history. However, most book recommender systems are based on collaborative filtering, involving a long onboarding process that requires to rate many books before providing good recommendations. Tinderbook provides book recommendations, given a single book that the user likes, through a card-based playful user interface that does not require an account creation. Tinderbook is strongly rooted in semantic technologies, using the DBpedia knowledge graph to enrich book descriptions and extending a hybrid state-of-the-art knowledge graph embeddings algorithm to derive an item relatedness measure for cold start recommendations. Tinderbook is publicly available and has already generated interest in the public, involving passionate readers, students, librarians, and researchers. The online evaluation shows that Tinderbook achieves almost 50% of precision of the recommendations. |
关 键 词: | Tinderbook; 机器学习; 图书推荐系统; DBpedia知识图; 提供用户喜欢的书籍推荐 |
课程来源: | 视频讲座网 |
数据采集: | 2022-09-20:cyh |
最后编审: | 2022-09-21:cyh |
阅读次数: | 5 |