Method and Apparatus for Determining a Group Preference in a Social Network
    1.
    发明申请
    Method and Apparatus for Determining a Group Preference in a Social Network 有权
    用于确定社会网络中的组偏好的方法和装置

    公开(公告)号:US20090132652A1

    公开(公告)日:2009-05-21

    申请号:US11942537

    申请日:2007-11-19

    IPC分类号: G06F15/16 G06F7/00

    摘要: A method (100) of electronically determining a group preference in a social network from multiple individual preferences of members of the social network is provided. One embodiment of the method (100) uses a combination of an individual's importance to a social network and a social network's importance to the individual as weighting factors when combining the individual preferences to generate a shared set of preferences. This group preference may be used to select content for broadcast to the network, including audio content and video content. A social network group preference determination apparatus (401) can determine the individual's importance to the social network by interrogating or monitoring the communication activity of portable electronic communication devices (402) belonging to the members of the social network.

    摘要翻译: 提供了一种从社交网络的成员的多个个人偏好电子地确定社交网络中的群组偏好的方法(100)。 方法(100)的一个实施例使用个人对社交网络的重要性和社会网络对个人的重要性的组合作为组合个人偏好以产生共享的偏好集合的加权因子。 该组偏好可以用于选择用于广播到网络的内容,包括音频内容和视频内容。 社交网络组偏好确定设备(401)可以通过询问或监视属于社交网络的成员的便携式电子通信设备(402)的通信活动来确定个人对社交网络的重要性。

    Method and apparatus for determining a group preference in a social network
    2.
    发明授权
    Method and apparatus for determining a group preference in a social network 有权
    用于确定社交网络中的组偏好的方法和装置

    公开(公告)号:US08620996B2

    公开(公告)日:2013-12-31

    申请号:US11942537

    申请日:2007-11-19

    IPC分类号: G06F15/16 G06Q99/00

    摘要: A method (100) of electronically determining a group preference in a social network from multiple individual preferences of members of the social network is provided. One embodiment of the method (100) uses a combination of an individual's importance to a social network and a social network's importance to the individual as weighting factors when combining the individual preferences to generate a shared set of preferences. This group preference may be used to select content for broadcast to the network, including audio content and video content. A social network group preference determination apparatus (401) can determine the individual's importance to the social network by interrogating or monitoring the communication activity of portable electronic communication devices (402) belonging to the members of the social network.

    摘要翻译: 提供了一种从社交网络的成员的多个个人偏好电子地确定社交网络中的群组偏好的方法(100)。 方法(100)的一个实施例使用个人对社交网络的重要性和社会网络对个人的重要性的组合作为组合个人偏好以产生共享的偏好集合的加权因子。 该组偏好可以用于选择用于广播到网络的内容,包括音频内容和视频内容。 社交网络组偏好确定设备(401)可以通过询问或监视属于社交网络的成员的便携式电子通信设备(402)的通信活动来确定个人对社交网络的重要性。

    Low bandwidth speech communication using default and personal phoneme tables
    4.
    发明授权
    Low bandwidth speech communication using default and personal phoneme tables 有权
    使用默认和个人音素表的低带宽语音通信

    公开(公告)号:US07136811B2

    公开(公告)日:2006-11-14

    申请号:US10128929

    申请日:2002-04-24

    CPC分类号: G10L19/0018

    摘要: A voice coding and decoding system 300 and method uses a personal phoneme table (320, 344) associated with a voice signature identifier (348) to permit encoding of true sounding voice by personalizing the phoneme table used for encoding and decoding. A default phoneme table (364) is used for encoding and decoding until a personal phoneme table (320, 344) is constructed. A MIDI decoder (360) is used to create the reconstructed speech from a string of phoneme identifiers transmitted from the sending side (302) to the receiving side (304).

    摘要翻译: 语音编码和解码系统300和方法使用与语音签名标识符(348)相关联的个人音素表(320,344)来允许通过个性化用于编码和解码的音素表来对真实的声音进行编码。 默认音素表(364)用于编码和解码,直到构建个人音素表(320,344)。 MIDI解码器(360)用于从从发送侧(302)发送到接收侧(304)的一串音素标识符创建重构语音。

    Gene expression programming algorithm

    公开(公告)号:US07127436B2

    公开(公告)日:2006-10-24

    申请号:US10101814

    申请日:2002-03-18

    IPC分类号: G06F15/18 G06N3/00 G06N3/12

    CPC分类号: G06N3/126

    摘要: A gene expression programming genetic algorithm for performing symbolic regression is provided. The algorithm avoids expression bloating and over fitting by employing a fitness function that depends inversely on the mathematical expression complexity. Members of a population that are evolved by the algorithm are represented as a set arrays (e.g., in the form of a matrix) of indexes that reference operands and operators, thus facilitating selection, mutation, and cross over operations conducted in the course of evolving the population. The algorithm comprises a syntax checking part that may be applied to population members without their having to be converted to executable programs first. An object-oriented programming language data structure is providing for encapsulating basic data for each codon (e.g., operand, operator) used by the algorithm.