公开(公告)号：US07382933B2

公开(公告)日：2008-06-03

申请号：US11210305

申请日：2005-08-24

申请人： Chitra Dorai ,  Ying Li ,  Youngja Park

发明人： Chitra Dorai ,  Ying Li ,  Youngja Park

IPC分类号： G06K9/36

CPC分类号： G06F17/30787 ,  G06F17/30796

摘要： System and method for partitioning a video into a series of semantic units where each semantic unit relates to a generally complete thematic topic. A computer implemented method for partitioning a video into a series of semantic units wherein each semantic unit relates to a theme or a topic, comprises dividing a video into a plurality of homogeneous segments, analyzing audio and visual content of the video, extracting a plurality of keywords from the speech content of each of the plurality of homogeneous segments of the video, and detecting and merging a plurality of groups of semantically related and temporally adjacent homogeneous segments into a series of semantic units in accordance with the results of both the audio and visual analysis and the keyword extraction. The present invention can be applied to generate important table-of-contents as well as index tables for videos to facilitate efficient video topic searching and browsing.

摘要翻译： 将视频分割成一系列语义单元的系统和方法，其中每个语义单元涉及一般完整的主题。 一种用于将视频分割成一系列语义单元的计算机实现的方法，其中每个语义单元涉及主题或主题，包括将视频划分为多个同构段，分析视频的音频和视觉内容，提取多个 根据视频的多个同构段的每个的语音内容的关键字，以及根据音频和视频的结果检测和合并多个语义相关和时间上相邻的同构段的组成一系列语义单元 分析和关键词提取。 本发明可以应用于产生重要的内容表以及用于视频的索引表，以便于有效的视频主题搜索和浏览。

公开(公告)号：US08983877B2

公开(公告)日：2015-03-17

申请号：US13411174

申请日：2012-03-02

申请人： Suresh N. Chari ,  Ian Michael Molloy ,  Youngja Park

发明人： Suresh N. Chari ,  Ian Michael Molloy ,  Youngja Park

IPC分类号： G06N5/00 ,  G06F1/00 ,  G06N99/00 ,  G06F21/60

CPC分类号： G06N99/005 ,  G06F21/604

摘要： Applications of machine learning techniques such as Latent Dirichlet Allocation (LDA) and author-topic models (ATM) to the problems of mining of user roles to specify access control policies from entitlement as well as logs which contain record of the usage of these entitlements are provided. In one aspect, a method for performing role mining given a plurality of users and a plurality of permissions is provided. The method includes the following steps. At least one generative machine learning technique, e.g., LDA, is used to obtain a probability distribution θ for user-to-role assignments and a probability distribution β for role-to-permission assignments. The probability distribution θ for user-to-role assignments and the probability distribution β for role-to-permission assignments are used to produce a final set of roles, including user-to-role assignments and role-to-permission assignments.

摘要翻译： 潜在的Dirichlet分配（LDA）和作者主题模型（ATM）等机器学习技术的应用对于用户角色的挖掘问题，从授权中指定访问控制策略以及包含这些权利使用记录的日志的应用是 提供。 在一个方面，提供了赋予多个用户和多个权限的用于执行角色挖掘的方法。 该方法包括以下步骤。 使用至少一种生成机器学习技术，例如LDA来获得概率分布; 用于角色角色分配和概率分布＆bgr; 用于角色到权限分配。 概率分布与概念; 用于角色角色分配和概率分布; 角色到权限分配用于生成一组最终角色，包括用户角色分配和角色到权限分配。

公开(公告)号：US20100274618A1

公开(公告)日：2010-10-28

申请号：US12428987

申请日：2009-04-23

申请人： Roy J. Byrd ,  Keh-Shin F. Cheng ,  Stephen Carl Gates ,  Mary S. Neff ,  Youngja Park ,  Wilfried Teiken

发明人： Roy J. Byrd ,  Keh-Shin F. Cheng ,  Stephen Carl Gates ,  Mary S. Neff ,  Youngja Park ,  Wilfried Teiken

IPC分类号： G06Q10/00 ,  G06Q50/00 ,  G10L11/00

CPC分类号： G06Q10/10 ,  H04M3/51 ,  H04M2203/357

摘要： A real-time method and system are described for automatically extracting text from the customer-agent interaction at a contact center, analyzing the extracted text to automatically identify one or more customer issues, and performing processing by contact-center agent buddies (CABs) to generate at least one response to the customer issues.

摘要翻译： 描述了一种实时方法和系统，用于在联络中心从客户代理交互中自动提取文本，分析提取的文本以自动识别一个或多个客户问题，以及由联络中心代理伙伴（CAB）执行处理 对客户问题产生至少一个响应。

公开(公告)号：US20080066136A1

公开(公告)日：2008-03-13

申请号：US11509250

申请日：2006-08-24

申请人： Chitra Dorai ,  Robert G. Farrell ,  Ying Li ,  Youngja Park

发明人： Chitra Dorai ,  Robert G. Farrell ,  Ying Li ,  Youngja Park

IPC分类号： G06F3/00 ,  G06F13/00 ,  H04N7/16 ,  H04N5/445

CPC分类号： H04N5/147 ,  G06F16/7834 ,  G06F16/7844

摘要： Computer implemented method, system and computer usable program code for detecting topic shift boundaries in a multimedia stream. A computer implemented method for detecting topic shift boundaries in a multimedia stream includes receiving a multimedia stream, and performing multimodal analysis on the multimedia stream to locate a plurality of temporal positions within the multimedia stream at which topic changes have an increased likelihood of occurring to provide a sequence of multimedia portions. Characteristics for a sliding window for each multimedia portion in the sequence of multimedia portions are automatically determined, and topic shift boundaries are detected in each multimedia portion by applying a text-based topic shift detector over the media stream's text transcript using a sliding window, wherein the sliding window used with each multimedia portion has the characteristics determined from its respective multimedia portion.

摘要翻译： 用于检测多媒体流中的主题移位边界的计算机实现的方法，系统和计算机可用程序代码。 一种用于检测多媒体流中的主题移位边界的计算机实现方法，包括：接收多媒体流，以及对所述多媒体流执行多模态分析，以定位所述多媒体流内的多个时间位置，在该多媒体流中，主题变化具有增加的发生可能性以提供 多媒体部分的序列。 自动确定多媒体部分序列中的每个多媒体部分的滑动窗口的特征，并且通过使用滑动窗口在媒体流的文本转录本上应用基于文本的主题移位检测器，在每个多媒体部分中检测主题移位边界，其中 与每个多媒体部分一起使用的滑动窗口具有从其各自的多媒体部分确定的特征。

公开(公告)号：US20080059522A1

公开(公告)日：2008-03-06

申请号：US11511816

申请日：2006-08-29

申请人： Ying Li ,  Youngja Park

发明人： Ying Li ,  Youngja Park

IPC分类号： G06F17/00

CPC分类号： G06K9/00973 ,  G06F16/784 ,  G06F16/7844 ,  G06K9/00335

摘要： A system, method and computer program product for generating personal profiles for subjects appearing in a video media source. The method includes extracting audiovisual-related personal information related to a subject appearing in the video media source; extracting text-related personal information that are related to the subject in the video source; correlating the extracted audiovisual-related personal information and the extracted text-related personal information related to the subject; and assembling a personal profile data structure for the subject, the personal profile data structure comprising the text-related personal information and audiovisual-related personal information related to the subject. The text-related personal information forms the name identity of the subject, while the audiovisual-related personal information includes audiovisual-related features including information forming one or more of: a visual identity, a kinematic identity and, a voice identity of the subject. In an alternate embodiment, in an iterative manner, the correlated extracted audiovisual-related personal information and extracted text-related personal information may be fed back and utilized for performing an additional search from external information sources, via a search engine, to obtain additional texts relating to the subject or obtain additional video media sources having the subject. There is further enabled the updating of an assembled personal profile of a subject as a new video media source having said subject becomes available.

摘要翻译： 一种用于生成出现在视频媒体源中的对象的个人简档的系统，方法和计算机程序产品。 该方法包括提取与视频媒体源中出现的对象相关的与视听有关的个人信息; 提取与视频源中的主题相关的文本相关个人信息; 将所提取的与视听有关的个人信息与所提取的与被摄体有关的文本相关个人信息相关联; 以及组合个体简档数据结构，该个人简档数据结构包括与该对象相关的文本相关个人信息和与视听相关的个人信息。 与文本相关的个人信息形成主题的姓名身份，而与视听相关的个人信息包括视听相关特征，包括形成以下中的一个或多个的信息：视觉身份，运动身份和主体的语音身份。 在替代实施例中，以迭代方式，相关联的提取的与视听有关的个人信息和提取的与文本相关的个人信息可以被反馈并用于经由搜索引擎从外部信息源执行附加搜索以获得附加文本 涉及该主题或获得具有该主题的附加视频媒体源。 此外，当具有所述对象的新的视频媒体源变得可用时，还能够更新被摄体的组合个人简档。

公开(公告)号：US20070185857A1

公开(公告)日：2007-08-09

申请号：US11337371

申请日：2006-01-23

申请人： Martin Kienzle ,  Ying Li ,  Youngja Park

发明人： Martin Kienzle ,  Ying Li ,  Youngja Park

IPC分类号： G06F17/30

CPC分类号： G06F16/5846 ,  G06F16/78 ,  G06F16/7844

摘要： Computer implemented method, system and computer program product for extracting salient keywords for videos. A computer implemented method for extracting salient keywords for videos includes extracting a set of candidate keywords from a text source of a video, assigning a salience value to each candidate keyword based on statistical information to provide a set of statistically significant keywords, exploiting additional cues that are available to the video and that can be used to further measure the significance of existing keywords or to extract new keywords, and selecting a set of salient keywords for the video based on the set of statistically significant keywords and the additional cues.

摘要翻译： 计算机实现方法，系统和计算机程序产品，用于提取视频的关键词。 用于提取视频的关键词的计算机实现方法包括从视频的文本源提取一组候选关键字，基于统计信息为每个候选关键字分配突出值，以提供一组统计上显着的关键字，利用附加线索 可用于视频，可用于进一步测量现有关键字的重要性或提取新关键字，以及基于一组统计学上重要的关键字和其他线索为视频选择一组显着的关键字。