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    • 4. 发明授权
    • Learning expected values for facts
    • 学习事实的预期价值
    • US08560468B1
    • 2013-10-15
    • US13025117
    • 2011-02-10
    • Kevin LermanVinicius J. FortunaAndrew W. HogueJohn R. ProvineEngin Cinar SahinJohn J. Lee
    • Kevin LermanVinicius J. FortunaAndrew W. HogueJohn R. ProvineEngin Cinar SahinJohn J. Lee
    • G06F15/18
    • G06N5/02
    • Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for machine learning. In one aspect, a method includes receiving a collection of facts, each fact represented as an entity-attribute-value tuple; identifying expected values for one or more individual attributes, where the identifying expected values includes, for each particular attribute: identifying facts having the attribute, calculating a value score for facts of the collection of facts having the particular attribute for each particular value, calculating a global score for all facts of the collection having the attribute, and comparing the value score to the global score such that a value is identified as an expected value if the comparison satisfies a specified threshold.
    • 方法,系统和装置,包括在计算机存储介质上编码的用于机器学习的计算机程序。 一方面,一种方法包括接收事实的集合,每个事实表示为实体属性值元组; 识别对于每个特定属性的识别期望值包括的一个或多个个体属性的期望值,识别具有该属性的事实,为每个特定值具有特定属性的事实的收集事实计算事实的值得分,计算 具有所述属性的所述集合的所有事实的全局得分,并且将所述值得分与所述全局得分进行比较,使得如果所述比较满足指定阈值,则将该值识别为期望值。