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Machine learning technique for recommendation of skills in a social networking service based on confidential data

机译:机器学习技术,用于基于机密数据推荐社交网络服务中的技能

摘要

In an example embodiment, each of a plurality of members of a social networking service is mapped to a weighted skill vector, each weighted skill vector including a list of skills for the member with an associated weight indicating a strength of the skill. Members of the social networking service who belong to an industry are aggregated to obtain a weighted matrix of members and skills along with compensation vectors indicating compensation for each of the members in the matrix. The weighted matrix of members and skills and corresponding compensation vectors are used to train a machine learning skill monetary value prediction model to output a predicted monetary value for a skill contained in a candidate vector fed to the machine learning skill monetary value prediction model. A recommendation is provided to a member of one or more skills to add based on output of the model.
机译:在示例实施例中,将社交网络服务的多个成员中的每个成员映射到加权技能向量,每个加权技能向量包括该成员的技能列表,该列表具有指示技能强度的关联权重。将属于某个行业的社交网络服务的成员进行汇总,以获取成员和技能的加权矩阵以及指示矩阵中每个成员的补偿的补偿向量。成员和技能的加权矩阵以及相应的补偿向量用于训练机器学习技能货币价值预测模型,以输出包含在馈送到机器学习技能货币价值预测模型的候选向量中的技能的预测货币价值。向一个或多个技能的成员提供推荐,以根据模型的输出进行添加。

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