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21. 发明授权

US06496816B1 Collaborative filtering with mixtures of bayesian networks 有权
标题翻译：使用贝叶斯网络混合进行协同过滤
公开(公告)号：US06496816B1
公开(公告)日：2002-12-17
申请号：US09220199
申请日：1998-12-23
申请人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
发明人： Bo Thiesson , Christopher A. Meek , David Maxwell Chickering , David Earl Heckerman
IPC分类号： G06N302
CPC分类号： G06K9/6296 , G06N5/025 , Y10S707/99945 , Y10S707/99948
摘要： One aspect of the invention is the construction of mixtures of Bayesian networks. Another aspect of the invention is the use of such mixtures of Bayesian networks to perform inferencing. A mixture of Bayesian networks (MBN) consists of plural hypothesis-specific Bayesian networks (HSBNs) having possibly hidden and observed variables. A common external hidden variable is associated with the MBN, but is not included in any of the HSBNs. The number of HSBNs in the MBN corresponds to the number of states of the common external hidden variable, and each HSBN is based upon the hypothesis that the common external hidden variable is in a corresponding one of those states. In one mode of the invention, the MBN having the highest MBN score is selected for use in performing inferencing. In another mode of the invention, some or all of the MBNs are retained as a collection of MBNs which perform inferencing in parallel, their outputs being weighted in accordance with the corresponding MBN scores and the MBN collection output being the weighted sum of all the MBN outputs. In one application of the invention, collaborative filtering may be performed by defining the observed variables to be choices made among a sample of users and the hidden variables to be the preferences of those users.
摘要翻译：本发明的一个方面是构建贝叶斯网络的混合物。本发明的另一方面是使用贝叶斯网络的这种混合来执行推理。贝叶斯网络（MBN）的混合由多个具有隐藏和观察变量的假设特定贝叶斯网络（HSBN）组成。常见的外部隐藏变量与MBN相关联，但不包括在任何HSBN中。 MBN中的HSBN的数量对应于公共外部隐藏变量的状态数，并且每个HSBN基于公共外部隐藏变量在这些状态中的相应一个状态中的假设。在本发明的一种模式中，选择具有最高MBN分数的MBN用于执行推定。在本发明的另一模式中，一些或所有MBN被保留为并行执行推论的MBN的集合，其输出根据相应的MBN分数加权，并且MBN收集输出是所有MBN的加权和输出。在本发明的一个应用中，可以通过将观察到的变量定义为在用户样本中作出的选择和作为这些用户的偏好的隐藏变量来执行协同过滤。

22. 发明授权

US08504491B2 Variational EM algorithm for mixture modeling with component-dependent partitions 有权
标题翻译：用于组件依赖分区的混合建模的变分EM算法
公开(公告)号：US08504491B2
公开(公告)日：2013-08-06
申请号：US12787308
申请日：2010-05-25
申请人： Bo Thiesson , Chong Wang
发明人： Bo Thiesson , Chong Wang
IPC分类号： G06F15/18 , G06K9/62
CPC分类号： G06K9/6226
摘要： Described are variational Expectation Maximization (EM) embodiments for learning a mixture model using component-dependent data partitions, where the E-step is sub-linear in sample size while the algorithm still maintains provable convergence guarantees. Component-dependent data partitions into blocks of data items are constructed according to a hierarchical data structure comprised of nodes, where each node corresponds to one of the blocks and stores statistics computed from the data items in the corresponding block. A modified variational EM algorithm computes the mixture model from initial component-dependent data partitions and a variational R-step updates the partitions. This process is repeated until convergence. Component membership probabilities computed in the E-step are constrained such that all data items belonging to a particular block in a particular component-dependent partition behave in the same way. The E-step can therefore consider the blocks or chunks of data items via their representative statistics, rather than considering individual data items.
摘要翻译：描述了使用组件依赖数据分区学习混合模型的变化期望最大化（EM）实施例，其中E阶在样本大小中是亚线性的，而算法仍然保持可证明的收敛保证。根据由节点组成的分层数据结构构建与数据项块相关的分量相关数据分区，其中每个节点对应于一个块，并存储从相应块中的数据项计算出的统计。改进的变分EM算法从初始的分量依赖数据分区计算混合模型，变分R步更新分区。这个过程重复直到收敛。在E步骤中计算的组件成员概率被约束，使得属于特定组件依赖分区中的特定块的所有数据项以相同的方式表现。因此，电子步骤可以通过其代表性统计数据来考虑数据项的块或块，而不是考虑单个数据项。

23. 发明授权

US08484253B2 Variational mode seeking 有权
标题翻译：变化模式寻求
公开(公告)号：US08484253B2
公开(公告)日：2013-07-09
申请号：US12982915
申请日：2010-12-31
申请人： Bo Thiesson , Jingu Kim
发明人： Bo Thiesson , Jingu Kim
IPC分类号： G06F17/30 , G06K9/62
CPC分类号： G06F17/30705 , G06K9/6226
摘要： A mode-seeking clustering mechanism identifies clusters within a data set based on the location of individual data point according to modes in a kernel density estimate. For large-scale applications the clustering mechanism may utilize rough hierarchical kernel and data partitions in a computationally efficient manner. A variational approach to the clustering mechanism may take into account variational probabilities, which are restricted in certain ways according to hierarchical kernel and data partition trees, and the mechanism may store certain statistics within these trees in order to compute the variational probabilities in a computational efficient way. The clustering mechanism may use a two-step variational expectation and maximization algorithm and generalizations hereof, where the maximization step may be performed in different ways in order to accommodate different mode-seeking algorithms, such as the mean shift, mediod shift, and quick shift algorithms.
摘要翻译：寻找模式的聚类机制根据核密度估计中的模式，根据各个数据点的位置来识别数据集内的簇。对于大规模应用，聚类机制可以以计算有效的方式利用粗略的分级内核和数据分区。聚类机制的变分方法可以考虑到根据分层内核和数据分区树在某些方面受到限制的变分概率，并且该机制可以在这些树中存储某些统计量，以便计算有效率的变分概率办法。聚类机制可以使用两步变化期望和最大化算法及其概括，其中最大化步骤可以以不同的方式执行，以便适应不同的寻呼算法，例如平均偏移，中间偏移和快速移位算法。

24. 发明申请

US20120323537A1 DETECTING IMPACT OF EXTRINSIC EVENTS ON A TIME SERIES 有权
标题翻译：检测超级事件对时间序列的影响
公开(公告)号：US20120323537A1
公开(公告)日：2012-12-20
申请号：US13162927
申请日：2011-06-17
申请人： Alex Bocharov , Christopher A. Meek , Bo Thiesson
发明人： Alex Bocharov , Christopher A. Meek , Bo Thiesson
IPC分类号： G06F17/10
CPC分类号： G06F17/18
摘要： In one embodiment, an event impact signature detector may analyze a time series with external events. A data interface 250 may receive a data set 310 representing the time series with external events. A processor 220 may fit the data set 310 into a baseline time series model 330. The processor 220 may iteratively determine each event location 352 for multiple external events 350 affecting the baseline time series model 330. The processor 220 may iteratively solve for each event impact 354 of the multiple external events 350 factoring in interactions between the multiple external events 350.
摘要翻译：在一个实施例中，事件影响签名检测器可以分析具有外部事件的时间序列。数据接口250可以接收表示具有外部事件的时间序列的数据集310。处理器220可以将数据集310拟合到基线时间序列模型330中。处理器220可以迭代地确定影响基线时间序列模型330的多个外部事件350的每个事件位置352.处理器220可以迭代地解决每个事件的影响多个外部事件350之间的354个因素导致多个外部事件之间的交互350。

25. 发明授权

US08090738B2 Multi-modal search wildcards 有权
标题翻译：多模式搜索通配符
公开(公告)号：US08090738B2
公开(公告)日：2012-01-03
申请号：US12200625
申请日：2008-08-28
申请人： Timothy Seung Yoon Paek , Bo Thiesson , Yun-Cheng Ju , Bongshin Lee , Christopher A. Meek
发明人： Timothy Seung Yoon Paek , Bo Thiesson , Yun-Cheng Ju , Bongshin Lee , Christopher A. Meek
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/3064 , G10L15/26
摘要： A multi-modal search system (and corresponding methodology) that employs wildcards is provided. Wildcards can be employed in the search query either initiated by the user or inferred by the system. These wildcards can represent uncertainty conveyed by a user in a multi-modal search query input. In examples, the words “something” or “whatchamacallit” can be used to convey uncertainty and partial knowledge about portions of the query and to dynamically trigger wildcard generation.
摘要翻译：提供了采用通配符的多模态搜索系统（以及相应的方法）。通配符可以由用户发起或由系统推断的搜索查询中使用。这些通配符可以表示用户在多模态搜索查询输入中传达的不确定性。在例子中，单词“something”或“whatchamacallit”可用于传达有关部分查询的不确定性和部分知识，并动态触发通配符生成。

26. 发明申请

US20090313573A1 TERM COMPLETE 有权
标题翻译：期限完成
公开(公告)号：US20090313573A1
公开(公告)日：2009-12-17
申请号：US12140280
申请日：2008-06-17
申请人： Timothy S. Paek , Bongshin Lee , Bo Thiesson
发明人： Timothy S. Paek , Bongshin Lee , Bo Thiesson
IPC分类号： G06F3/048 , G06F17/00
CPC分类号： G06F17/30401 , G06F3/0482 , G06F17/3064
摘要： Real-time query expansion (RTQE) is a process of supplementing an original query with additional terms or expansion choices that are ranked according to some figure of merit and presented while users are still formulating their queries. As disclosed herein, individual terms may be combined and submitted as a phrase into a query. By building the phase term-by-term, users can compositionally formulate queries while maintaining the same benefits that other RTQE interfaces offer. To promote greater flexibility in its working environment, the number of terms that are presented on a display may be reduced. In place of some terms, placeholders may be used and expanded by the user when necessary. This allows phrases to be readily presented on small displays (e.g., hand-held devices).
摘要翻译：实时查询扩展（RTQE）是一个补充原始查询的过程，附加条款或扩展选项根据某些品质因素进行排名，并在用户仍在制定查询时呈现。如本文所公开的，可以将各个术语组合并作为短语提交到查询中。通过逐步构建阶段，用户可以组合制定查询，同时保持与其他RTQE接口相同的优势。为了提高其工作环境的灵活性，可以减少在显示器上呈现的术语数量。代替某些术语，必要时可以由用户使用和扩展占位符。这允许在小显示器（例如，手持设备）上容易地呈现短语。

27. 发明申请

US20090287681A1 MULTI-MODAL SEARCH WILDCARDS 有权
标题翻译：多模式搜索WILDCARDS
公开(公告)号：US20090287681A1
公开(公告)日：2009-11-19
申请号：US12200625
申请日：2008-08-28
申请人： Timothy Seung Yoon Paek , Bo Thiesson , Yun-Cheng Ju , Bongshin Lee , Christopher A. Meek
发明人： Timothy Seung Yoon Paek , Bo Thiesson , Yun-Cheng Ju , Bongshin Lee , Christopher A. Meek
IPC分类号： G06F17/30 , G10L15/06
CPC分类号： G06F17/3064 , G10L15/26
摘要： A multi-modal search system (and corresponding methodology) that employs wildcards is provided. Wildcards can be employed in the search query either initiated by the user or inferred by the system. These wildcards can represent uncertainty conveyed by a user in a multi-modal search query input. In examples, the words “something” or “whatchamacallit” can be used to convey uncertainty and partial knowledge about portions of the query and to dynamically trigger wildcard generation.
摘要翻译：提供了采用通配符的多模态搜索系统（以及相应的方法）。通配符可以由用户发起或由系统推断的搜索查询中使用。这些通配符可以表示用户在多模态搜索查询输入中传达的不确定性。在例子中，单词“something”或“whatchamacallit”可用于传达有关部分查询的不确定性和部分知识，并动态触发通配符生成。

28. 发明授权

US07409371B1 Efficient determination of sample size to facilitate building a statistical model 有权
标题翻译：有效确定样本量以便建立统计模型
公开(公告)号：US07409371B1
公开(公告)日：2008-08-05
申请号：US09873719
申请日：2001-06-04
申请人： David E. Heckerman , Christopher A. Meek , Bo Thiesson
发明人： David E. Heckerman , Christopher A. Meek , Bo Thiesson
IPC分类号： G06N5/00
CPC分类号： G06N99/005
摘要： A model is constructed for an initial subset of the data using a first parameter estimation algorithm. The model may be evaluated, for example, by applying the model to a holdout data set of the data. If the model is not acceptable, additional data is added to the data subset and the first parameter estimation algorithm is repeated for the aggregate data subset. An appropriate subset of the data exists when the first parameter estimation algorithm produces an acceptable model. The appropriate subset of the data may then be employed by a second parameter estimation algorithm, which may be a more accurate version of the first algorithm or a different algorithm altogether, to build a statistical model to characterize the data.
摘要翻译：使用第一参数估计算法为数据的初始子集构建模型。可以例如通过将模型应用于数据的保持数据集来评估该模型。如果模型不可接受，则向数据子集添加附加数据，并且针对聚合数据子集重复第一参数估计算法。当第一参数估计算法产生可接受的模型时，存在数据的适当子集。然后可以通过第二参数估计算法来采用数据的适当子集，第二参数估计算法可以是第一算法的更准确的版本或者完全不同的算法，以构建用于表征数据的统计模型。

29. 发明申请

US20070127818A1 SYSTEMS AND METHODS FOR ADAPTIVE HANDWRITING RECOGNITION 失效
标题翻译：用于自适应手写识别的系统和方法
公开(公告)号：US20070127818A1
公开(公告)日：2007-06-07
申请号：US11672458
申请日：2007-02-07
申请人： Bo Thiesson , Christopher Meek
发明人： Bo Thiesson , Christopher Meek
IPC分类号： G06K9/18
CPC分类号： G06K9/6292 , G06K9/222
摘要： The present invention utilizes generic and user-specific features of handwriting samples to provide adaptive handwriting recognition with a minimum level of user-specific enrollment data. By allowing generic and user-specific classifiers to facilitate in a recognition process, the features of a specific user's handwriting can be exploited to quickly ascertain characteristics of handwriting characters not yet entered by the user. Thus, new characters can be recognized without requiring a user to first enter that character as enrollment or “training” data. In one instance of the present invention, processing of generic features is accomplished by a generic classifier trained on multiple users. In another instance of the present invention, a user-specific classifier is employed to modify a generic classifier's classification as required to provide user-specific handwriting recognition.
摘要翻译：本发明利用手写样本的通用和用户特定的特征来提供具有最低级别的用户特定注册数据的自适应手写识别。通过允许通用和用户特定的分类器便于识别过程，可以利用特定用户手写的特征来快速确定用户尚未输入的手写字符的特征。因此，可以识别新的字符，而不需要用户首先将该字符输入作为注册或“训练”数据。在本发明的一个实例中，通用特征的处理由对多个用户进行训练的通用分类器来完成。在本发明的另一个实例中，使用用户特定的分类器根据需要修改通用分类器的分类以提供用户特定的手写识别。

30. 发明授权

US07184591B2 Systems and methods for adaptive handwriting recognition 有权
标题翻译：自适应手写识别的系统和方法
公开(公告)号：US07184591B2
公开(公告)日：2007-02-27
申请号：US10442547
申请日：2003-05-21
申请人： Bo Thiesson , Christopher A. Meek
发明人： Bo Thiesson , Christopher A. Meek
IPC分类号： G06K9/18
CPC分类号： G06K9/6292 , G06K9/222
摘要： The present invention utilizes generic and user-specific features of handwriting samples to provide adaptive handwriting recognition with a minimum level of user-specific enrollment data. By allowing generic and user-specific classifiers to facilitate in a recognition process, the features of a specific user's handwriting can be exploited to quickly ascertain characteristics of handwriting characters not yet entered by the user. Thus, new characters can be recognized without requiring a user to first enter that character as enrollment or “training” data. In one instance of the present invention, processing of generic features is accomplished by a generic classifier trained on multiple users. In another instance of the present invention, a user-specific classifier is employed to modify a generic classifier's classification as required to provide user-specific handwriting recognition.
摘要翻译：本发明利用手写样本的通用和用户特定的特征来提供具有最低级别的用户特定注册数据的自适应手写识别。通过允许通用和用户特定的分类器便于识别过程，可以利用特定用户手写的特征来快速确定用户尚未输入的手写字符的特征。因此，可以识别新的字符，而不需要用户首先将该字符输入作为注册或“训练”数据。在本发明的一个实例中，通用特征的处理由对多个用户进行训练的通用分类器来完成。在本发明的另一个实例中，使用用户特定的分类器根据需要修改通用分类器的分类以提供用户特定的手写识别。

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