公开(公告)号：US20150242492A1

公开(公告)日：2015-08-27

申请号：US14636067

申请日：2015-03-02

申请人： FEM, INC.

发明人： Meghana BHATT ,  Rachel PAYNE ,  Natasha MOHANTY

IPC分类号： G06F17/30

CPC分类号： G06F17/30604 ,  G06F17/30023 ,  G06F17/30029 ,  G06F17/30058 ,  G06F17/3082 ,  G06F17/30864

摘要： Techniques for analyzing media content are described. One technique generally comprises performing a regression analysis for characters in a plurality of media content based on user demographics, content outcome measure, and character models. The technique determines an attribute of significance. In some embodiments, the technique selects media content for display that depicts a character having at least a threshold value of the attribute of significance. In some embodiments, the technique displays media analytics for the attribute of significance determined based on a value of the attribute of significance exceeding a threshold significance value.

摘要翻译： 描述用于分析媒体内容的技术。 一种技术通常包括基于用户人口统计，内容结果测量和角色模型对多个媒体内容中的字符执行回归分析。 该技术决定了重要性的属性。 在一些实施例中，该技术选择描绘具有至少具有有效属性的阈值的角色的媒体内容。 在一些实施例中，该技术显示基于超过阈值显着性值的有效属性的值确定的有效属性的媒体分析。

公开(公告)号：US20180137122A1

公开(公告)日：2018-05-17

申请号：US15786351

申请日：2017-10-17

申请人： FEM, Inc.

发明人： Rachel PAYNE ,  Meghana BHATT ,  Natasha MOHANTY

IPC分类号： G06F17/30

CPC分类号： G06F16/435 ,  G06F16/24578 ,  G06F16/3334 ,  G06F16/43 ,  G06F16/44 ,  G06F16/48 ,  G06F16/68 ,  G06F16/78 ,  G06F16/7867

摘要： Techniques for recommending media are described. A character preference function comprising a plurality of preference coefficients is accessed. A first character model comprises a first set of attribute values for the plurality of attributes of a first character. The first and second characters are associated with a first and second salience value, respectively. A second character model comprises a second set of attribute values for the plurality of attributes of a second character of the plurality of characters. A first character rating is calculated using the plurality of preference coefficients and the first set of attribute values. A second character rating of the second character is calculated using the plurality of preference coefficients with the second set of attribute values. A media rating is calculated based on the first and second salience values and the first and second character ratings. A media is recommended based on the media rating.

公开(公告)号：US20140280250A1

公开(公告)日：2014-09-18

申请号：US14065332

申请日：2013-10-28

申请人： FEM, Inc

发明人： Rachel PAYNE ,  Meghana BHATT ,  Natasha MOHANTY

IPC分类号： G06F17/30

CPC分类号： G06F17/30029 ,  G06F17/30023 ,  G06F17/30038 ,  G06F17/30058 ,  G06F17/3053 ,  G06F17/30663 ,  G06F17/30749 ,  G06F17/30817 ,  G06F17/3082

摘要： Techniques for recommending media are described. A character preference function comprising a plurality of preference coefficients is accessed. A first character model comprises a first set of attribute values for the plurality of attributes of a primary character. A second character model comprises a second set of attribute values for the plurality of attributes of a secondary character. The primary and secondary characters are associated with first and second predetermined salience values, respectively. A first character rating is calculated using the plurality of preference coefficients and the first set of attribute values. A second character rating of the secondary character is calculated using the plurality of preference coefficients with the second set of attribute values. A media rating is calculated based on the first and second salience values and the first and second character ratings. Media is recommended to a user based on the media rating.

摘要翻译： 描述介质介质的技术。 访问包括多个偏好系数的字符偏好函数。 第一字符模型包括用于主要角色的多个属性的第一组属性值。 第二字符模型包括次要字符的多个属性的第二组属性值。 主要和次要字符分别与第一和第二预定显着值相关联。 使用多个偏好系数和第一组属性值来计算第一字符等级。 使用具有第二组属性值的多个偏好系数来计算辅助字符的第二字符等级。 基于第一和第二显着值以及第一和第二字符等级来计算媒体评级。 根据媒体评级，向用户推荐媒体。

公开(公告)号：US20160357742A1

公开(公告)日：2016-12-08

申请号：US15238677

申请日：2016-08-16

申请人： FEM, Inc.

发明人： Rachel PAYNE ,  Meghana BHATT ,  Natasha MOHANTY

IPC分类号： G06F17/30

CPC分类号： G06F17/30029 ,  G06F17/30023 ,  G06F17/30038 ,  G06F17/30058 ,  G06F17/3053 ,  G06F17/30663 ,  G06F17/30749 ,  G06F17/30817 ,  G06F17/3082

摘要： Techniques for recommending media are described. A character preference function comprising a plurality of preference coefficients is accessed. A first character model comprises a first set of attribute values for the plurality of attributes of a first character. The first and second characters are associated with a first and second salience value, respectively. A second character model comprises a second set of attribute values for the plurality of attributes of a second character of the plurality of characters. A first character rating is calculated using the plurality of preference coefficients and the first set of attribute values. A second character rating of the second character is calculated using the plurality of preference coefficients with the second set of attribute values. A media rating is calculated based on the first and second salience values and the first and second character ratings. A media is recommended based on the media rating.

公开(公告)号：US20160306872A1

公开(公告)日：2016-10-20

申请号：US15132197

申请日：2016-04-18

申请人： FEM, Inc.

发明人： Meghana BHATT ,  Rachel PAYNE ,  Natasha MOHANTY

IPC分类号： G06F17/30

摘要： Techniques for analyzing media content are described. One technique generally comprises performing a regression analysis for characters in a plurality of media content based on user demographics, content outcome measure, and character models. The technique determines an attribute of significance. In some embodiments, the technique selects media content for display that depicts a character having at least a threshold value of the attribute of significance. In some embodiments, the technique displays media analytics for the attribute of significance determined based on a value of the attribute of significance exceeding a threshold significance value.

公开(公告)号：US20160041978A1

公开(公告)日：2016-02-11

申请号：US14800020

申请日：2015-07-15

申请人： FEM, Inc.

发明人： Rachel PAYNE ,  Meghana BHATT ,  Natasha MOHANTY

IPC分类号： G06F17/30

CPC分类号： G06F17/30029 ,  G06F17/30023 ,  G06F17/30038 ,  G06F17/30058 ,  G06F17/3053 ,  G06F17/30663 ,  G06F17/30749 ,  G06F17/30817 ,  G06F17/3082

摘要： Techniques for recommending media are described. A character preference function comprising a plurality of preference coefficients is accessed. A first character model comprises a first set of attribute values for the plurality of attributes of a first character. The first and second characters are associated with a first and second salience value, respectively. A second character model comprises a second set of attribute values for the plurality of attributes of a second character of the plurality of characters. A first character rating is calculated using the plurality of preference coefficients and the first set of attribute values. A second character rating of the second character is calculated using the plurality of preference coefficients with the second set of attribute values. A media rating is calculated based on the first and second salience values and the first and second character ratings. A media is recommended based on the media rating.

摘要翻译： 描述介质介质的技术。 访问包括多个偏好系数的字符偏好函数。 第一字符模型包括用于第一字符的多个属性的第一组属性值。 第一和第二个字符分别与第一和第二显着值相关联。 第二字符模型包括多个字符的第二个字符的多个属性的第二组属性值。 使用多个偏好系数和第一组属性值来计算第一字符等级。 使用具有第二组属性值的多个偏好系数来计算第二字符的第二字符等级。 基于第一和第二显着值以及第一和第二字符等级来计算媒体评级。 根据媒体评级推荐媒体。

公开(公告)号：US20150186771A1

公开(公告)日：2015-07-02

申请号：US14644092

申请日：2015-03-10

申请人： FEM, INC.

发明人： Meghana BHATT ,  Rachel PAYNE

IPC分类号： G06N3/02 ,  G06F17/16

CPC分类号： G06N3/02 ,  G06F17/16 ,  G06N99/005

摘要： A system for prospectively identifying media characteristics for inclusion in media content is disclosed. A neural network database including media characteristic information and feature information may associate relationships among the media characteristic information and feature information. Personal characteristic information associated with target media consumers may be used to select a subset of the neural network database. A first set of nodes, representing selected feature information, may be activated. The node interactions may be calculated to detect the activation of a second set of nodes, the second set of nodes representing media characteristic information. Generally, a node is activated when an activation value of the node exceeds a threshold value. Media characteristic information may be identified for inclusion in media content based on the second set of nodes.

摘要翻译： 公开了一种用于前瞻性地识别媒体内容的媒体特征的系统。 包括媒体特征信息和特征信息的神经网络数据库可以关联媒体特征信息和特征信息之间的关系。 可以使用与目标媒体消费者相关联的个人特征信息来选择神经网络数据库的子集。 可以激活表示所选特征信息的第一组节点。 可以计算节点交互以检测第二组节点的激活，第二组节点表示媒体特征信息。 通常，当节点的激活值超过阈值时，节点被激活。 可以基于第二组节点来识别媒体特征信息以包含在媒体内容中。

公开(公告)号：US20140372373A1

公开(公告)日：2014-12-18

申请号：US14466882

申请日：2014-08-22

申请人： FEM, INC.

发明人： Rachel PAYNE ,  Meghana BHATT ,  Natasha MOHANTY

IPC分类号： G06F17/30

CPC分类号： G06F17/30029 ,  G06F17/30023 ,  G06F17/30038 ,  G06F17/30058 ,  G06F17/3053 ,  G06F17/30663 ,  G06F17/30749 ,  G06F17/30817 ,  G06F17/3082

摘要： Techniques for recommending media are described. A character preference function comprising a plurality of preference coefficients is accessed. A first character model comprises a first set of attribute values for the plurality of attributes of a first character. The first and second characters are associated with a first and second salience value, respectively. A second character model comprises a second set of attribute values for the plurality of attributes of a second character of the plurality of characters. A first character rating is calculated using the plurality of preference coefficients and the first set of attribute values. A second character rating of the second character is calculated using the plurality of preference coefficients with the second set of attribute values. A media rating is calculated based on the first and second salience values and the first and second character ratings. A media is recommended based on the media rating.

摘要翻译： 描述介质介质的技术。 访问包括多个偏好系数的字符偏好函数。 第一字符模型包括用于第一字符的多个属性的第一组属性值。 第一和第二个字符分别与第一和第二显着值相关联。 第二字符模型包括多个字符的第二个字符的多个属性的第二组属性值。 使用多个偏好系数和第一组属性值来计算第一字符等级。 使用具有第二组属性值的多个偏好系数来计算第二字符的第二字符等级。 基于第一和第二显着值以及第一和第二字符等级来计算媒体评级。 根据媒体评级推荐媒体。