公开(公告)号：US07797257B2

公开(公告)日：2010-09-14

申请号：US11926129

申请日：2007-10-29

申请人： Stephen Barnhill ,  Isabelle Guyon ,  Jason Weston

发明人： Stephen Barnhill ,  Isabelle Guyon ,  Jason Weston

IPC分类号： G06N3/00 ,  G06F15/18

CPC分类号： G06K9/623 ,  G06F19/20 ,  G06F19/24 ,  G06K9/6228 ,  G06K9/6231 ,  G06K9/6256 ,  G06K9/6269 ,  G06N99/005 ,  G06Q10/0637 ,  G06Q20/10 ,  G06Q40/06 ,  G06Q50/22 ,  G06T7/0012 ,  Y02A90/22 ,  Y02A90/26

摘要： A computer system for performing data analysis services using a support vector machine for analyzing data received from a remote source on a distributed network includes a server in communication with the distributed network for receiving a data set and a financial account identifier associated with the remote source. The server communicates over the distributed network with a financial institution to receive funds from a financial account identified by the financial account identifier. A processor receives one or more data sets from the remote source and pre-processes the data to enhance meaning within the data set. The pre-processed data is used to train and test a support vector machine for recognizing patterns within the data. Live data is processed using the trained and tested support vector machine to generate an output which is transmitted to the remote source after the server confirms that payment for the data processing service has been received.

摘要翻译： 用于使用支持向量机执行数据分析服务的计算机系统用于分析从分布式网络上的远程源接收的数据，包括与分布式网络通信的服务器，用于接收与远程源相关联的数据集和财务帐户标识符。 服务器通过分布式网络与金融机构进行通信，从金融账户标识符识别的金融账户接收资金。 处理器从远程源接收一个或多个数据集，并且预处理数据以增强数据集内的含义。 预处理数据用于训练和测试支持向量机，用于识别数据内的模式。 使用经过训练和测试的支持向量机处理实时数据，以产生在服务器确认已经接收到数据处理服务的支付之后被发送到远程源的输出。

公开(公告)号：US20100185659A1

公开(公告)日：2010-07-22

申请号：US12562840

申请日：2009-09-18

申请人： BING BAI ,  JASON WESTON ,  RONAN COLLORBERT ,  DAVID GRANGIER

发明人： BING BAI ,  JASON WESTON ,  RONAN COLLORBERT ,  DAVID GRANGIER

IPC分类号： G06F17/30

CPC分类号： G06F17/30663 ,  G06F17/30616

摘要： A system and method for determining a similarity between a document and a query includes providing a frequently used dictionary and an infrequently used dictionary in storage memory. For each word or gram in the infrequently used dictionary, n words or grams are correlated from the frequently used dictionary based on a first score. Features for a vector of the infrequently used words or grams are replaced with features from a vector of the correlated words or grams from the frequently used dictionary when the features from a vector of the correlated words or grams meet a threshold value. A similarity score is determined between weight vectors of a query and one or more documents in a corpus by employing the features from the vector of the correlated words or grams that met the threshold value.

摘要翻译： 用于确定文档和查询之间的相似性的系统和方法包括在存储存储器中提供频繁使用的字典和不经常使用的字典。 对于不经常使用的字典中的每个单词或克，n个词或克根据第一个分数与经常使用的词典相关联。 当相关词或克的向量的特征符合阈值时，不经常使用的单词或克的向量的特征将被来自经常使用的词典的相关词或克的向量的特征替换。 通过使用满足阈值的相关词或克的向量的特征，在查询的权重向量和语料库中的一个或多个文档之间确定相似性得分。

公开(公告)号：US20080097940A1

公开(公告)日：2008-04-24

申请号：US11929169

申请日：2007-10-30

申请人： Asa Ben-Hur ,  Andre Elisseeff ,  Olivier Chapelle ,  Jason Weston

发明人： Asa Ben-Hur ,  Andre Elisseeff ,  Olivier Chapelle ,  Jason Weston

IPC分类号： G06F15/18

CPC分类号： G06K9/6269 ,  G06K9/6215 ,  G06K9/6248

摘要： Support vector machines are used to classify data contained within a structured dataset such as a plurality of signals generated by a spectral analyzer. The signals are pre-processed to ensure alignment of peaks across the spectra. Similarity measures are constructed to provide a basis for comparison of pairs of samples of the signal. A support vector machine is trained to discriminate between different classes of the samples. to identify the most predictive features within the spectra. In a preferred embodiment feature selection is performed to reduce the number of features that must be considered.

摘要翻译： 支持向量机用于对包含在结构化数据集中的数据进行分类，例如由频谱分析仪产生的多个信号。 信号被预处理，以确保谱峰的峰对准。 构建相似性度量以提供用于比较信号样本对的基础。 训练支持向量机以区分不同类别的样本。 以识别光谱中最具预测性的特征。 在优选实施例中，执行特征选择以减少必须考虑的特征的数量。

公开(公告)号：US09235853B2

公开(公告)日：2016-01-12

申请号：US13610715

申请日：2012-09-11

申请人： Jason Weston ,  Adam Berenzweig ,  Ron Weiss

发明人： Jason Weston ,  Adam Berenzweig ,  Ron Weiss

IPC分类号： G06F17/00 ,  G06Q30/02

CPC分类号： G06Q30/0282

摘要： Methods, systems, and computer programs are presented for recommending music entities to a user. One method includes defining a set of labels with each label identifying a music concept and constructing at least vector for each of a plurality of entities based on source data. Each vector includes the set of define labels and each label is assigned with a label score. Two vectors respectively associated with two of the plurality of entities are compared. The method further includes generating a recommendation action based on comparison result of the two vectors and transmitting the data for the recommendation action to a device of the user. In one example, the comparisons can be pre-computed and used for the recommendation action.

摘要翻译： 呈现用于向用户推荐音乐实体的方法，系统和计算机程序。 一种方法包括定义一组标签，其中每个标签识别音乐概念，并且基于源数据为至少多个实体中的每一个构造至少矢量。 每个向量包括一组定义标签，每个标签都有一个标签分数。 比较分别与多个实体中的两个实体相关联的两个向量。 该方法还包括基于两个向量的比较结果生成推荐动作，并将用于推荐动作的数据发送给用户的设备。 在一个示例中，可以预先计算比较并将其用于推荐操作。

公开(公告)号：US20150066649A1

公开(公告)日：2015-03-05

申请号：US12768101

申请日：2010-04-27

申请人： Sanjiv Kumar ,  Jason Weston

发明人： Sanjiv Kumar ,  Jason Weston

IPC分类号： G01C21/00 ,  G06Q30/00

CPC分类号： G06Q50/14 ,  G01C21/3476 ,  G06Q30/02

摘要： Systems and methods provide touristic routes to users. For example, a user at a client device may request a touristic route between an initial and a final destination. A server uses the initial and final destinations to determine a shortest route. The server then defines an envelope around the route in order to identify points of interest. The identified points of interest are ranked and filtered, in order to select the most relevant points of interest. Once the points of interest are selected, the server determines a final route between the initial destination, the points of interest, and the final route. This information is then transmitted to the client device and displayed to the user. The server may also identify and transmit content associated with the final route and/or the points of interest, including, but not limited to, photos, videos, hyperlinks, and advertisements.

摘要翻译： 系统和方法为用户提供旅游路线。 例如，客户端设备上的用户可以请求在初始和最终目的地之间的旅游路由。 服务器使用初始和最终目的地来确定最短路由。 然后，服务器在路线周围定义一个信封，以便识别感兴趣的点。 对所识别的兴趣点进行排序和筛选，以便选择最相关的兴趣点。 一旦选择兴趣点，服务器确定初始目的地，兴趣点和最终路线之间的最终路线。 然后将该信息发送到客户端设备并显示给用户。 服务器还可以识别和发送与最终路线和/或兴趣点相关联的内容，包括但不限于照片，视频，超链接和广告。

公开(公告)号：US20090204558A1

公开(公告)日：2009-08-13

申请号：US12367278

申请日：2009-02-06

申请人： Jason Weston ,  Ronan Collobert

发明人： Jason Weston ,  Ronan Collobert

IPC分类号： G06F15/18

CPC分类号： G06N3/08 ,  G06K9/6251

摘要： A method for training a learning machine having a deep network with a plurality of layers, includes applying a regularizer to one or more of the layers of the deep network; training the regularizer with unlabeled data; and training the deep network with labeled data. Also, an apparatus for use in discriminative classification and regression, including an input device for inputting unlabeled and labeled data associated with a phenomenon of interest; a processor; and a memory communicating with the processor. The memory includes instructions executable by the processor for implementing a learning machine having a deep network structure and training the learning machine by applying a regularizer to one or more of the layers of the deep network; training the regularizer with unlabeled data; and training the deep network with labeled data.

摘要翻译： 一种用于训练具有多个层的深度网络的学习机的方法，包括：对所述深层网络的一个或多个层应用正则化; 训练正规者与未标记的数据; 并用标签数据训练深层网络。 另外，一种用于鉴别分类和回归的装置，包括输入装置，用于输入与感兴趣的现象相关联的未标记和标记的数据; 处理器 以及与处理器通信的存储器。 存储器包括可由处理器执行的用于实现具有深度网络结构的学习机器的指令，并且通过将深度网络的一个或多个层应用校正器来训练学习机器; 训练正规者与未标记的数据; 并用标签数据训练深层网络。

公开(公告)号：US07542959B2

公开(公告)日：2009-06-02

申请号：US11842934

申请日：2007-08-21

申请人： Stephen Barnhill ,  Isabelle Guyon ,  Jason Weston

发明人： Stephen Barnhill ,  Isabelle Guyon ,  Jason Weston

IPC分类号： G06N3/08 ,  G06K9/62

CPC分类号： G06K9/623 ,  G06F19/20 ,  G06F19/24 ,  G06K9/6228 ,  G06K9/6231 ,  G06K9/6256 ,  G06K9/6269 ,  G06N99/005 ,  G06Q10/0637 ,  G06Q20/10 ,  G06Q40/06 ,  G06Q50/22 ,  G06T7/0012 ,  Y02A90/22 ,  Y02A90/26

摘要： Identification of a determinative subset of features from within a large set of features is performed by training a support vector machine to rank the features according to classifier weights, where features are removed to determine how their removal affects the value of the classifier weights. The features having the smallest weight values are removed and a new support vector machine is trained with the remaining weights. The process is repeated until a relatively small subset of features remain that is capable of accurately separating the data into different patterns or classes. The method is applied for selecting the smallest number of genes that are capable of accurately distinguishing between medical conditions such as cancer and non-cancer.

摘要翻译： 通过训练支持向量机来根据分类器权重来对特征的确定性子集进行识别，其中去除特征以确定它们的去除如何影响分类器权重的值。 去除具有最小权重值的特征，并用剩余权重训练新的支持向量机。 重复该过程直到相对较小的特征子集保持能够将数据精确地分离成不同的模式或类别。 该方法适用于选择能够准确区分癌症和非癌症等医学病症的最小数量的基因。

公开(公告)号：US20080097939A1

公开(公告)日：2008-04-24

申请号：US11928641

申请日：2007-10-30

申请人： Isabelle Guyon ,  Edward Reiss ,  Rene Doursat ,  Jason Weston ,  David Lewis

发明人： Isabelle Guyon ,  Edward Reiss ,  Rene Doursat ,  Jason Weston ,  David Lewis

IPC分类号： G06F15/18

CPC分类号： G06F19/28 ,  G06F19/20 ,  G06F19/24 ,  G06F19/26 ,  G06K9/623 ,  G06K9/6231 ,  G06K9/6269 ,  G06N99/005 ,  Y10S707/99936

摘要： The data mining platform comprises a plurality of system modules, each formed from a plurality of components. Each module has an input data component, a data analysis engine for processing the input data, an output data component for outputting the results of the data analysis, and a web server to access and monitor the other modules within the unit and to provide communication to other units. Each module processes a different type of data, for example, a first module processes microarray (gene expression) data while a second module processes biomedical literature on the Internet for information supporting relationships between genes and diseases and gene functionality. In the preferred embodiment, the data analysis engine is a kernel-based learning machine, and in particular, one or more support vector machines (SVMs). The data analysis engine includes a pre-processing function for feature selection, for reducing the amount of data to be processed by selecting the optimum number of attributes, or “features”, relevant to the information to be discovered.

公开(公告)号：US20080097938A1

公开(公告)日：2008-04-24

申请号：US11928606

申请日：2007-10-30

申请人： Isabelle Guyon ,  Edward Reiss ,  Rene Doursat ,  Jason Weston ,  David Lewis

发明人： Isabelle Guyon ,  Edward Reiss ,  Rene Doursat ,  Jason Weston ,  David Lewis

IPC分类号： G06F15/18

CPC分类号： G06F19/24 ,  G06F19/20 ,  G06F19/28 ,  G06K9/6231 ,  G06K9/6269 ,  G06N99/005

摘要： The data mining platform comprises a plurality of system modules, each formed from a plurality of components. Each module has an input data component, a data analysis engine for processing the input data, an output data component for outputting the results of the data analysis, and a web server to access and monitor the other modules within the unit and to provide communication to other units. Each module processes a different type of data, for example, a first module processes microarray (gene expression) data while a second module processes biomedical literature on the Internet for information supporting relationships between genes and diseases and gene functionality. In the preferred embodiment, the data analysis engine is a kernel-based learning machine, and in particular, one or more support vector machines (SVMs). The data analysis engine includes a pre-processing function for feature selection, for reducing the amount of data to be processed by selecting the optimum number of attributes, or “features”, relevant to the information to be discovered.

摘要翻译： 数据挖掘平台包括由多个部件形成的多个系统模块。 每个模块具有输入数据组件，用于处理输入数据的数据分析引擎，用于输出数据分析结果的输出数据组件和用于访问和监视该单元内的其它模块的web服务器，并提供通信 其他单位。 每个模块处理不同类型的数据，例如，第一模块处理微阵列（基因表达）数据，而第二模块处理因特网上的生物医学文献以获得支持基因与疾病和基因功能之间关系的信息。 在优选实施例中，数据分析引擎是基于内核的学习机器，特别是一个或多个支持向量机（SVM）。 数据分析引擎包括用于特征选择的预处理功能，用于通过选择与要发现的信息相关的属性的最佳数量或“特征”来减少要处理的数据量。

公开(公告)号：US20080059392A1

公开(公告)日：2008-03-06

申请号：US11926129

申请日：2007-10-29

申请人： Stephen Barnhill ,  Isabelle Guyon ,  Jason Weston

发明人： Stephen Barnhill ,  Isabelle Guyon ,  Jason Weston

IPC分类号： G06N3/00

CPC分类号： G06K9/623 ,  G06F19/20 ,  G06F19/24 ,  G06K9/6228 ,  G06K9/6231 ,  G06K9/6256 ,  G06K9/6269 ,  G06N99/005 ,  G06Q10/0637 ,  G06Q20/10 ,  G06Q40/06 ,  G06Q50/22 ,  G06T7/0012 ,  Y02A90/22 ,  Y02A90/26

摘要： A computer system for performing data analysis services using a support vector machine for analyzing data received from a remote source on a distributed network includes a server in communication with the distributed network for receiving a data set and a financial account identifier associated with the remote source. The server communicates over the distributed network with a financial institution to receive funds from a financial account identified by the financial account identifier. A processor receives one or more data sets from the remote source and pre-processes the data to enhance meaning within the data set. The pre-processed data is used to train and test a support vector machine for recognizing patterns within the data. Live data is processed using the trained and tested support vector machine to generate an output which is transmitted to the remote source after the server confirms that payment for the data processing service has been received.

摘要翻译： 用于使用支持向量机执行数据分析服务的计算机系统用于分析从分布式网络上的远程源接收的数据，包括与分布式网络通信的服务器，用于接收与远程源相关联的数据集和财务帐户标识符。 服务器通过分布式网络与金融机构进行通信，从金融账户标识符识别的金融账户接收资金。 处理器从远程源接收一个或多个数据集，并且预处理数据以增强数据集内的含义。 预处理数据用于训练和测试支持向量机，用于识别数据内的模式。 使用经过训练和测试的支持向量机处理实时数据，以产生在服务器确认已经接收到数据处理服务的支付之后被发送到远程源的输出。