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1. 发明授权

US07996440B2 Extraction of attributes and values from natural language documents 有权
标题翻译：从自然语言文件中提取属性和值
公开(公告)号：US07996440B2
公开(公告)日：2011-08-09
申请号：US11742215
申请日：2007-04-30
申请人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
发明人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
IPC分类号： G06F17/30
CPC分类号： G06F17/27 , G06F17/2745
摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.
摘要翻译：一个或多个分类算法被应用于至少一个自然语言文档，以便提取给定产品的属性和值。为此，可以采用监督分类算法，半监督分类算法，无监督分类算法或这种分类算法的组合。可以经由公共通信网络获得至少一个自然语言文档。如此识别的两个或多个属性（或两个或多个值）可以被合并以形成一个或多个属性短语或值短语。一旦以这种方式提取了属性和值，就可以执行关联或链接操作来建立描述产品的属性值对。在当前优选的实施例中，（无监督）算法用于生成种子属性和值，然后可以支持受监督或半监督分类算法。

2. 发明授权

US07970767B2 Extraction of attributes and values from natural language documents 有权
公开(公告)号：US07970767B2
公开(公告)日：2011-06-28
申请号：US11742244
申请日：2007-04-30
申请人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
发明人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
IPC分类号： G06F17/30
CPC分类号： G06F17/2715 , G06F17/241 , G06F17/30616
摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.

3. 发明授权

US08626801B2 Extraction of attributes and values from natural language documents 有权
标题翻译：从自然语言文件中提取属性和值
公开(公告)号：US08626801B2
公开(公告)日：2014-01-07
申请号：US13197906
申请日：2011-08-04
申请人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
发明人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
IPC分类号： G06F17/30
CPC分类号： G06F17/27 , G06F17/2745
摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.
摘要翻译：一个或多个分类算法被应用于至少一个自然语言文档，以便提取给定产品的属性和值。为此，可以采用监督分类算法，半监督分类算法，无监督分类算法或这种分类算法的组合。可以经由公共通信网络获得至少一个自然语言文档。如此识别的两个或多个属性（或两个或多个值）可以被合并以形成一个或多个属性短语或值短语。一旦以这种方式提取了属性和值，就可以执行关联或链接操作来建立描述产品的属性值对。在当前优选的实施例中，（无监督）算法用于生成种子属性和值，然后可以支持受监督或半监督分类算法。

4. 发明授权

US08521745B2 Extraction of attributes and values from natural language documents 有权
标题翻译：从自然语言文件中提取属性和值
公开(公告)号：US08521745B2
公开(公告)日：2013-08-27
申请号：US13158678
申请日：2011-06-13
申请人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
发明人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
IPC分类号： G06F17/30
CPC分类号： G06F17/2715 , G06F17/241 , G06F17/30616
摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.
摘要翻译：一个或多个分类算法被应用于至少一个自然语言文档，以便提取给定产品的属性和值。为此，可以采用监督分类算法，半监督分类算法，无监督分类算法或这种分类算法的组合。可以经由公共通信网络获得至少一个自然语言文档。如此识别的两个或多个属性（或两个或多个值）可以被合并以形成一个或多个属性短语或值短语。一旦以这种方式提取了属性和值，就可以执行关联或链接操作来建立描述产品的属性值对。在当前优选的实施例中，（无监督）算法用于生成种子属性和值，然后可以支持受监督或半监督分类算法。

5. 发明申请

US20120036100A1 EXTRACTION OF ATTRIBUTES AND VALUES FROM NATURAL LANGUAGE DOCUMENTS 有权
标题翻译：从自然语言文件中提取属性和价值
公开(公告)号：US20120036100A1
公开(公告)日：2012-02-09
申请号：US13197906
申请日：2011-08-04
申请人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
发明人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
IPC分类号： G06N5/02
CPC分类号： G06F17/27 , G06F17/2745
摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.
摘要翻译：一个或多个分类算法被应用于至少一个自然语言文档，以便提取给定产品的属性和值。为此，可以采用监督分类算法，半监督分类算法，无监督分类算法或这种分类算法的组合。可以经由公共通信网络获得至少一个自然语言文档。如此识别的两个或多个属性（或两个或多个值）可以被合并以形成一个或多个属性短语或值短语。一旦以这种方式提取了属性和值，就可以执行关联或链接操作来建立描述产品的属性值对。在当前优选的实施例中，（无监督）算法用于生成种子属性和值，然后可以支持受监督或半监督分类算法。

6. 发明申请

US20070282892A1 EXTRACTION OF ATTRIBUTES AND VALUES FROM NATURAL LANGUAGE DOCUMENTS 有权
公开(公告)号：US20070282892A1
公开(公告)日：2007-12-06
申请号：US11742215
申请日：2007-04-30
申请人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
发明人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
IPC分类号： G06F17/30
CPC分类号： G06F17/27 , G06F17/2745
摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.

7. 发明申请

US20070282872A1 EXTRACTION OF ATTRIBUTES AND VALUES FROM NATURAL LANGUAGE DOCUMENTS 有权
标题翻译：从自然语言文件中提取属性和价值
公开(公告)号：US20070282872A1
公开(公告)日：2007-12-06
申请号：US11742244
申请日：2007-04-30
申请人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
发明人： Katharina Probst , Rayid Ghani , Andrew E. Fano , Marko Krema , Yan Liu
IPC分类号： G06F17/00
CPC分类号： G06F17/2715 , G06F17/241 , G06F17/30616
摘要： One or more classification algorithms are applied to at least one natural language document in order to extract both attributes and values of a given product. Supervised classification algorithms, semi-supervised classification algorithms, unsupervised classification algorithms or combinations of such classification algorithms may be employed for this purpose. The at least one natural language document may be obtained via a public communication network. Two or more attributes (or two or more values) thus identified may be merged to form one or more attribute phrases or value phrases. Once attributes and values have been extracted in this manner, association or linking operations may be performed to establish attribute-value pairs that are descriptive of the product. In a presently preferred embodiment, an (unsupervised) algorithm is used to generate seed attributes and values which can then support a supervised or semi-supervised classification algorithm.
摘要翻译：一个或多个分类算法被应用于至少一个自然语言文档，以便提取给定产品的属性和值。为此，可以采用监督分类算法，半监督分类算法，无监督分类算法或这种分类算法的组合。可以经由公共通信网络获得至少一个自然语言文档。如此识别的两个或多个属性（或两个或多个值）可以被合并以形成一个或多个属性短语或值短语。一旦以这种方式提取了属性和值，就可以执行关联或链接操作来建立描述产品的属性值对。在当前优选的实施例中，（无监督）算法用于生成种子属性和值，然后可以支持受监督或半监督分类算法。

8. 发明授权

US09060322B2 Method and system for preventing loops in mesh networks 有权
标题翻译：用于防止网状网络环路的方法和系统
公开(公告)号：US09060322B2
公开(公告)日：2015-06-16
申请号：US13281072
申请日：2011-10-25
申请人： Xu Zou , Kangchang Huang , Yan Liu
发明人： Xu Zou , Kangchang Huang , Yan Liu
IPC分类号： H04L12/28 , H04W4/00 , H04W40/02 , H04L12/705 , H04L12/715 , H04L12/707
CPC分类号： H04W40/02 , H04L45/04 , H04L45/18 , H04L45/24
摘要： The present disclosure discloses a network device and/or method for preventing loops in routing paths of network frames in a wireless digital network. The disclosed network device at a network node receives a frame from a wired network. The frame includes a site identifier uniquely corresponding to the wired network, a source physical address, and a destination physical address. If the network node is selected as a representative portal node, the network device forwards the frame. Otherwise, if another network node is selected as the representative portal node, the network device drops the received frame to prevent forming a loop in a routing path corresponding to the frame. If not other network is selected as the representative portal node, the network device floods the frame to other network nodes in the wireless network.
摘要翻译：本公开公开了一种用于防止无线数字网络中的网络帧的路由路径中的环路的网络设备和/或方法。在网络节点处公开的网络设备从有线网络接收帧。帧包括与有线网络唯一对应的站点标识符，源物理地址和目的地物理地址。如果选择网络节点作为代表性门户节点，则网络设备转发该帧。否则，如果选择另一网络节点作为代表门户节点，则网络设备丢弃所接收的帧，以防止在对应于该帧的路由路径中形成环路。如果不选择其他网络作为代表门户网站节点，则网络设备会将该帧洪泛到无线网络中的其他网络节点。

9. 发明申请

US20150150843A1 CARDIOPROTECTIVE COMPOUNDS, THEIR USE WITH CHEMOTHERAPY, AND METHODS FOR IDENTIFYING THEM 审中-公开
标题翻译：保护性化合物，其与化疗有关的使用方法及其鉴定方法
公开(公告)号：US20150150843A1
公开(公告)日：2015-06-04
申请号：US14402512
申请日：2013-05-16
申请人： Randall T. Peterson , Yan Liu
发明人： Randall T. Peterson , Yan Liu
IPC分类号： A61K31/352 , A61K49/00
CPC分类号： A61K31/352 , A61K31/17 , A61K31/37 , A61K31/496 , A61K31/704 , A61K49/0008 , A61K2300/00
摘要： The invention provides a method of reducing anthracycline-induced cardiotoxicity by administering a toxicity-reducing compound, such as a compound of Formulas (I), (II) or (III) or a combination thereof, and/or diphenyl urea (DPU), dexrazoxane (DEX), to a patient receiving an anthracycline. The invention also provides a method of identifying toxicity-reducing compounds.
摘要翻译：本发明提供了通过施用毒性降低化合物，例如式（I），（II）或（III）的化合物或其组合和/或二苯基脲（DPU），降低蒽环类诱导的心脏毒性的方法，右美沙芬（DEX）给予接受蒽环类抗生素的患者。本发明还提供鉴定毒性降低化合物的方法。

10. 发明授权

US08895302B2 Directed differentiation of primate pluripotent stem cells into functional basal forebrain cholinergic neurons (BFCNs) and medium spiny gabaergic projection neurons 有权
标题翻译：灵长类多能干细胞定向分化为功能性基底前脑胆碱能神经元（BFCNs）和中度多刺的神经元投射神经元
公开(公告)号：US08895302B2
公开(公告)日：2014-11-25
申请号：US13207202
申请日：2011-08-10
申请人： Su-Chun Zhang , Yan Liu , Lixiang Ma
发明人： Su-Chun Zhang , Yan Liu , Lixiang Ma
IPC分类号： C12N5/02 , C12N5/0793 , G01N33/50
CPC分类号： C12N5/0619 , C12N2501/01 , C12N2501/105 , C12N2501/115 , C12N2501/13 , C12N2501/15 , C12N2501/155 , C12N2501/392 , C12N2501/41 , C12N2502/086 , C12N2506/02 , C12N2506/45 , C12N2533/52 , G01N33/5058 , G01N2500/10
摘要： Methods of efficiently converting primate pluripotent stem cells to GABA neurons or cholinergic neurons, as well as applications thereof, are disclosed.
摘要翻译：公开了将灵长类多能干细胞有效转化为GABA神经元或胆碱能神经元的方法及其应用。

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