首页>
外国专利>
INDUCTIVE MATRIX COMPLETION AND GRAPH PROXIMITY FOR CONTENT ITEM RECOMMENDATION
INDUCTIVE MATRIX COMPLETION AND GRAPH PROXIMITY FOR CONTENT ITEM RECOMMENDATION
展开▼
机译:内容项推荐的感应矩阵完成和图形接近度
展开▼
页面导航
摘要
著录项
相似文献
摘要
Users may consume and/or share information through various types of content items. For example, user may post a family photo through a social network, create a running blog through a microblogging service, etc. Because users may be overwhelmed by the amount of available content items, it may be advantageous to recommend content items, such as blogs to follow, to users. Accordingly, inductive matrix completion is used to evaluate user interactions with content items (e.g., a user following a blog), content item features (e.g., text and/or images of a blog is evaluated to identify a topic of the blog), and/or user features (e.g., a user liking or reblogging a blog, user demographics, user interests, etc.) to determine whether to recommend a content item to a user. Additionally, graph proximity is used to recommend content items based upon weights of edges connecting user nodes to content item nodes within a directed graph.
展开▼