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Methods for assessing and scoring user proficiency in topics determined by data from social networks and other sources

机译:评估和评分用户对社交网络和其他来源的数据确定的主题的熟练程度的方法

摘要

Embodiments provide for assessing and scoring user proficiency in topics determined by data from social networks and other sources. Embodiments can combine the information available to direct models, e.g., using user profiles, endorsements, etc., with data from various other external knowledge bases to find implicit topics for users, and other types of reasoning to compute proficiency scores. Implicit topics, i.e., those topics related to explicitly identified areas of expertise, can be determined based on a topic graph such as a Directed Acyclic Graph (DAG). Generally speaking, embodiments can traverse the topic graph for explicitly identified skills or topics and determine related or similar new skills based on nearby nodes of the graph. This approach can uncover skills that user that may not have disclosed as well as scoring users on skills based on the skill's similarity to those the user did claim.
机译:实施例提供了对由来自社交网络和其他来源的数据确定的主题中的用户熟练程度的评估和评分。实施例可以将可用于直接模型的信息(例如,使用用户简档,认可等)与来自各种其他外部知识库的数据相结合,以找到用户的隐含主题,以及其他类型的推理来计算熟练度得分。可以基于诸如有向无环图(DAG)之类的主题图来确定隐式主题,即与明确标识的专业领域相关的那些主题。一般而言,实施例可以遍历主题图以获得明确标识的技能或主题,并基于图的附近节点来确定相关或相似的新技能。这种方法可以发现用户可能尚未公开的技能,并且可以根据与用户声称的技能的相似性为用户评分。

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