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1. 发明授权

US08392436B2 Semantic search via role labeling 有权
标题翻译：通过角色标注进行语义搜索
公开(公告)号：US08392436B2
公开(公告)日：2013-03-05
申请号：US12364041
申请日：2009-02-02
申请人： Bing Bai , Jason Weston , Ronan Collobert
发明人： Bing Bai , Jason Weston , Ronan Collobert
IPC分类号： G06F7/00 , G06F17/00
CPC分类号： G06F17/30654
摘要： A method and system for searching for information contained in a database of documents each includes an offline part and an online part. The offline part includes predicting, in a first computer process, semantic data for sentences of the documents contained in the database and storing this data in a database. The online part includes querying the database for information with a semantically-sensitive query, predicting, in a real time computer process, semantic data for the query, and determining, in a second computer process, a matching score against all the documents in the database, which incorporates the semantic data for the sentences and the query.
摘要翻译：用于搜索包含在文档数据库中的信息的方法和系统各自包括离线部分和在线部分。离线部分包括在第一计算机进程中预测包含在数据库中的文档的句子的语义数据，并将该数据存储在数据库中。在线部分包括使用语义敏感的查询来查询数据库的信息，在实时计算机进程中预测用于查询的语义数据，以及在第二计算机进程中确定与数据库中的所有文档的匹配分数，其中包含句子和查询的语义数据。

2. 发明授权

US08341095B2 Supervised semantic indexing and its extensions 有权
标题翻译：监督语义索引及其扩展
公开(公告)号：US08341095B2
公开(公告)日：2012-12-25
申请号：US12562802
申请日：2009-09-18
申请人： Bing Bai , Jason Weston , Ronan Collobert , David Grangier
发明人： Bing Bai , Jason Weston , Ronan Collobert , David Grangier
IPC分类号： G06F15/18 , G06F7/00 , G06F3/00
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 building a weight vector for each of a plurality of documents in a corpus of documents stored in memory and building a weight vector for a query input into a document retrieval system. A weight matrix is generated which distinguishes between relevant documents and lower ranked documents by comparing document/query tuples using a gradient step approach. A similarity score is determined between weight vectors of the query and documents in a corpus by determining a product of a document weight vector, a query weight vector and the weight matrix.
摘要翻译：用于确定文档和查询之间的相似度的系统和方法包括为存储在存储器中的文档的语料库中的多个文档中的每个文档建立权重向量，并且建立用于向文档检索系统输入的查询的加权向量。生成权重矩阵，通过使用梯度步骤方法比较文档/查询元组来区分相关文档和较低排名的文档。通过确定文档权重向量，查询权重向量和权重矩阵的乘积，在查询的权重向量和语料库中的文档之间确定相似性得分。

3. 发明申请

US20090204605A1 Semantic Search Via Role Labeling 有权
标题翻译：语义搜索通过角色标签
公开(公告)号：US20090204605A1
公开(公告)日：2009-08-13
申请号：US12364041
申请日：2009-02-02
申请人： Bing Bai , Jason Weston , Ronan Collobert
发明人： Bing Bai , Jason Weston , Ronan Collobert
IPC分类号： G06F17/30 , G06F15/18 , G10L21/00
CPC分类号： G06F17/30654
摘要： A method and system for searching for information contained in a database of documents each includes an offline part and an online part. The offline part includes predicting, in a first computer process, semantic data for sentences of the documents contained in the database and storing this data in a database. The online part includes querying the database for information with a semantically-sensitive query, predicting, in a real time computer process, semantic data for the query, and determining, in a second computer process, a matching score against all the documents in the database, which incorporates the semantic data for the sentences and the query.
摘要翻译：用于搜索包含在文档数据库中的信息的方法和系统各自包括离线部分和在线部分。离线部分包括在第一计算机进程中预测包含在数据库中的文档的句子的语义数据，并将该数据存储在数据库中。在线部分包括使用语义敏感的查询来查询数据库的信息，在实时计算机进程中预测用于查询的语义数据，以及在第二计算机进程中确定与数据库中的所有文档的匹配分数，其中包含句子和查询的语义数据。

4. 发明申请

US20110301942A1 Method and Apparatus for Full Natural Language Parsing 有权
标题翻译：全自然语言分析的方法和装置
公开(公告)号：US20110301942A1
公开(公告)日：2011-12-08
申请号：US13150898
申请日：2011-06-01
申请人： Ronan Collobert , Bing Bai
发明人： Ronan Collobert , Bing Bai
IPC分类号： G06F17/27
CPC分类号： G06F17/271 , G06F17/2775
摘要： The method and apparatus for discriminative natural language parsing, uses a deep convolutional neural network adapted for text and a structured tag inference in a graph. In the method and apparatus, a trained recursive convolutional graph transformer network, formed by the deep convolutional neural network and the graph, predicts “levels” of a parse tree based on predictions of previous levels.
摘要翻译：用于辨别自然语言解析的方法和装置，使用适于文本的深卷积神经网络和图中的结构化标签推理。在该方法和装置中，通过深卷积神经网络和图形形成的经过训练的递归卷积变换网络基于先前水平的预测来预测解析树的“水平”。

5. 发明授权

US08874434B2 Method and apparatus for full natural language parsing 有权
标题翻译：全自然语言解析的方法和装置
公开(公告)号：US08874434B2
公开(公告)日：2014-10-28
申请号：US13150898
申请日：2011-06-01
申请人： Ronan Collobert , Bing Bai
发明人： Ronan Collobert , Bing Bai
IPC分类号： G06F17/20 , G06F17/27 , G06G7/00
CPC分类号： G06F17/271 , G06F17/2775
摘要： The method and apparatus for discriminative natural language parsing, uses a deep convolutional neural network adapted for text and a structured tag inference in a graph. In the method and apparatus, a trained recursive convolutional graph transformer network, formed by the deep convolutional neural network and the graph, predicts “levels” of a parse tree based on predictions of previous levels.
摘要翻译：用于辨别自然语言解析的方法和装置，使用适于文本的深卷积神经网络和图中的结构化标签推理。在该方法和装置中，通过深卷积神经网络和图形形成的经过训练的递归卷积变换网络基于先前水平的预测来预测解析树的“水平”。

6. 发明授权

US08359282B2 Supervised semantic indexing and its extensions 有权
标题翻译：监督语义索引及其扩展
公开(公告)号：US08359282B2
公开(公告)日：2013-01-22
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： G06F15/18 , G06F7/00
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。

7. 发明授权

US08738547B2 System and methods for finding hidden topics of documents and preference ranking documents 有权
标题翻译：查找文档隐藏主题和偏好排序文件的系统和方法
公开(公告)号：US08738547B2
公开(公告)日：2014-05-27
申请号：US13083391
申请日：2011-04-08
申请人： Xi Chen , Yanjun Qi , Bing Bai
发明人： Xi Chen , Yanjun Qi , Bing Bai
IPC分类号： G06N99/00
CPC分类号： G06N99/005 , G06F17/30705
摘要： Systems and methods are disclosed to perform preference learning on a set of documents includes receiving raw input features from the set of documents stored on a data storage device; generating polynomial combinations from the raw input features; generating one or more parameters; applying the parameters to one or more classifiers to generate outputs; determining a loss function and parameter gradients and updating parameters determining one or more sparse regularizing terms and updating the parameters; and expressing that one document is preferred over another in a search query and retrieving one or more documents responsive to the search query.
摘要翻译：公开了系统和方法来对一组文件执行偏好学习，包括从存储在数据存储设备上的文档集接收原始输入特征; 从原始输入特征生成多项式组合; 产生一个或多个参数; 将参数应用于一个或多个分类器以产生输出; 确定损失函数和参数梯度以及更新确定一个或多个稀疏规则化条件并更新参数的参数; 并且在搜索查询中表达一个文档优于另一个文档，并且响应于搜索查询来检索一个或多个文档。

8. 发明申请

US20120191632A1 SYSTEM AND METHODS FOR FINDING HIDDEN TOPICS OF DOCUMENTS AND PREFERENCE RANKING DOCUMENTS 有权
公开(公告)号：US20120191632A1
公开(公告)日：2012-07-26
申请号：US13083391
申请日：2011-04-08
申请人： Xi Chen , Yanjun Qi , Bing Bai
发明人： Xi Chen , Yanjun Qi , Bing Bai
IPC分类号： G06F15/18
CPC分类号： G06N99/005 , G06F17/30705
摘要： Systems and methods are disclosed to perform preference learning on a set of documents includes receiving raw input features from the set of documents stored on a data storage device; generating polynomial combinations from the raw input features; generating one or more parameters; applying the parameters to one or more classifiers to generate outputs; determining a loss function and parameter gradients and updating parameters determining one or more sparse regularizing terms and updating the parameters; and expressing that one document is preferred over another in a search query and retrieving one or more documents responsive to the search query.

9. 发明申请

US20150363948A1 Direct Patlak Estimation from List-Mode PET Data 有权
标题翻译：从列表模式PET数据直接Patlak估计
公开(公告)号：US20150363948A1
公开(公告)日：2015-12-17
申请号：US14739929
申请日：2015-06-15
申请人： Richard M. Leahy , Wentao Zhu , Quanzheng Li , Bing Bai , Peter Stephen Conti
发明人： Richard M. Leahy , Wentao Zhu , Quanzheng Li , Bing Bai , Peter Stephen Conti
IPC分类号： G06T11/00 , A61B6/00 , A61B6/04 , G06T7/00 , A61B6/03
CPC分类号： A61B6/5205 , A61B6/037 , A61B6/0457 , A61B6/4258 , A61B6/4275 , A61B6/504 , A61B6/507 , G06T11/006 , G06T2207/10104 , G06T2211/412 , G06T2211/424
摘要： A medical imaging system for reconstructing quantitative dynamic nuclear medicine images of a subject may include a three dimensional positron emission tomography (3D PET) scanner and a data processing system. The three dimensional positron emission tomography (3D PET) scanner may: perform scans of the subject at each of multiple bed positions, each scan being of only a sub-portion of the subject that is within an axial length covered by the scanner; and generate dynamic list-mode PET data that: represents a total number of photon pairs arriving at each of multiple detector pairs in the 3D PET scanner; and is organized in a list of elements, each element in the list including a detector pair index and an arrival time for each detected photon pair; and acquires PET data using a dynamic PET protocol with at least two scans at each of the multiple bed positions. The data processing system may: reconstruct Patlak slope and intercept images of the subject over an axial length of the subject that exceeds the axial length of each scan of the subject by optimizing a likelihood or penalized likelihood function using the list-mode PET data from at least two scans of the subject at each of the multiple bed positions; and store the reconstructed image in a storage device or displays the reconstructed image on a display system.
摘要翻译：用于重建受试者的定量动态核医学图像的医学成像系统可以包括三维正电子发射断层摄影（3D PET）扫描仪和数据处理系统。三维正电子发射断层摄影（3D PET）扫描器可以：在多个床位置的每一个位置执行被检体的扫描，每个扫描仅是被扫描仪所覆盖的轴向长度内的被检体的子部分; 并生成动态列表模式PET数据，其表示到达3D PET扫描仪中的多个检测器对中的每一个的光子对的总数; 并且被组织在元素列表中，列表中的每个元素包括每个检测到的光子对的检测器对索引和到达时间; 并且使用动态PET协议在多个床位置的每一个处进行至少两次扫描来获取PET数据。数据处理系统可以：通过使用来自对象的列表模式PET数据优化似然或惩罚似然函数来重建Patlak斜率并且通过超过受试者的每次扫描的轴向长度的主体的轴向长度截取受试者的图像在多个床位置的每个位置处对象的至少两次扫描; 并将重建的图像存储在存储装置中，或者将重建的图像显示在显示系统上。

10. 发明授权

US08874432B2 Systems and methods for semi-supervised relationship extraction 有权
标题翻译：半监督关系提取的系统和方法
公开(公告)号：US08874432B2
公开(公告)日：2014-10-28
申请号：US13078985
申请日：2011-04-03
申请人： Yanjun Qi , Bing Bai , Xia Ning , Pavel Kuksa
发明人： Yanjun Qi , Bing Bai , Xia Ning , Pavel Kuksa
IPC分类号： G06F17/27 , G06F17/30
CPC分类号： G06F17/2785 , G06F17/271 , G06F17/30684
摘要： Systems and methods are disclosed to perform relation extraction in text by applying a convolution strategy to determine a kernel between sentences; applying one or more semi-supervised strategies to the kernel to encode syntactic and semantic information to recover a relational pattern of interest; and applying a classifier to the kernel to identify the relational pattern of interest in the text in response to a query.
摘要翻译：公开了系统和方法，通过应用卷积策略来确定句子之间的内核来执行文本中的关系提取; 对内核应用一个或多个半监督策略来编码句法和语义信息以恢复关注模式; 以及将分类器应用于内核以在响应于查询的情况下识别文本中感兴趣的关系模式。

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