公开(公告)号：US09348816B2

公开(公告)日：2016-05-24

申请号：US12579251

申请日：2009-10-14

Applicant: Rakesh Gupta ,  Lev-Arie Ratinov

Inventor： Rakesh Gupta ,  Lev-Arie Ratinov

IPC: G01L15/00 ,  G06F17/27

CPC classification number: G06F17/279

Abstract: The present invention provides a method for identifying a turn, such as a sentence or phrase, for addition to a platform dialog comprising a plurality of turns. Lexical features of each of a set of candidate turns relative to one or more turns in the platform dialog are determined. Semantic features associated with each candidate turn and associated with the platform dialog are determined to identify one or more topics associated with each candidate turn and with the platform dialog. Lexical features of each candidate turn are compared to lexical features of the platform dialog and semantic features associated with each candidate turn are compared to semantic features of the platform dialog to rank the candidate turns based on similarity of lexical features and semantic features of each candidate turn to lexical features and semantic features of the platform dialog.

Abstract translation: 本发明提供了一种用于识别转弯的方法，例如句子或短语，用于添加到包括多个匝数的平台对话。 确定相对于平台对话中的一个或多个转弯的一组候选转弯中每一个的词汇特征。 确定与每个候选转弯相关联并与平台对话相关联的语义特征以识别与每个候选转弯相关联的一个或多个主题以及与平台对话。 将每个候选回合的词汇特征与平台对话的词汇特征进行比较，并将与每个候选轮次相关联的语义特征与平台对话的语义特征进行比较，以基于词汇特征和每个候选转弯的语义特征的相似性对候选轮次进行排名 到平台对话的词汇特征和语义特征。

公开(公告)号：US08712935B2

公开(公告)日：2014-04-29

申请号：US13143420

申请日：2009-12-23

Applicant: Narayan Behera ,  Shruti Sinha ,  Rakesh Gupta ,  Ann Geoncy ,  Nevenka Dimitrova

Inventor： Narayan Behera ,  Shruti Sinha ,  Rakesh Gupta ,  Ann Geoncy ,  Nevenka Dimitrova

IPC: G06N5/00

CPC classification number: G06F19/24 ,  G06F19/18 ,  G06F19/20

Abstract: The invention relates to selecting a set of candidate genes from a pool of genes. The method comprising receiving a set of gene data; arranging the set of gene data into a set of clusters with similar profiles by use of a clustering algorithm; and inputting the set of clusters into a genetic algorithm to select a set of candidate genes from the set of clusters. The method thus relates to hybrid between selection by clustering computation and selection by evolutionary computation. This hybrid is also referred to as an evolutionary clustering algorithm (ECA).

Abstract translation: 本发明涉及从一组基因中选择一组候选基因。 该方法包括接收一组基因数据; 通过使用聚类算法将该组基因数据排列成具有相似特征的集合; 以及将所述集合集合输入到遗传算法中以从所述集合集合中选择一组候选基因。 因此，该方法涉及通过聚类计算和通过进化计算进行选择的选择之间的混合。 该混合也称为进化聚类算法（ECA）。

公开(公告)号：US08625539B2

公开(公告)日：2014-01-07

申请号：US12575958

申请日：2009-10-08

Applicant: Rakesh Gupta ,  Asif Hossain

Inventor： Rakesh Gupta ,  Asif Hossain

IPC: H04W52/02 ,  H04W52/46 ,  H04W36/30 ,  H04W36/24

CPC classification number: H04W72/0426 ,  H04B17/21 ,  H04W28/22 ,  H04W52/08 ,  H04W52/267 ,  H04W52/50

Abstract: A method and system for obtaining reverse channel resources for a mobile device, the method filtering a closed loop correction power value; calculating a data rate utilizing the filtered closed loop correction power value; and sending a supplemental channel request message, including the calculated data rate, to a base station transceiver system.

Abstract translation: 一种用于获取移动设备的反向信道资源的方法和系统，该方法对闭环校正功率值进行滤波; 使用滤波的闭环校正功率值计算数据速率; 以及向基站收发机系统发送包括所计算的数据速率的补充信道请求消息。

公开(公告)号：US08359204B2

公开(公告)日：2013-01-22

申请号：US12259196

申请日：2008-10-27

Applicant: Rakesh Gupta

Inventor： Rakesh Gupta

IPC: G10L21/00

CPC classification number: G06F3/167 ,  B60R16/0373 ,  G01C21/3608 ,  G10L15/1815 ,  G10L2015/223 ,  G10L2015/228

Abstract: The present invention provides a system and method associating the freeform speech commands with one or more predefined commands from a set of predefined commands. The set of predefined commands are stored and alternate forms associated with each predefined command are retrieved from an external data source. The external data source receives the alternate forms associated with each predefined command from multiple sources so the alternate forms represent paraphrases of the predefined command. A representation including words from the predefined command and the alternate forms of the predefined command, such as a vector representation, is generated for each predefined command. A similarity value between received speech data and each representation of a predefined command is computed and the speech data is classified as the predefined command whose representation has the highest similarity value to the speech data.

Abstract translation: 本发明提供一种将自由形式语音命令与来自一组预定义命令的一个或多个预定义命令相关联的系统和方法。 存储一组预定义的命令，并从外部数据源检索与每个预定义命令相关联的替代形式。 外部数据源从多个源接收与每个预定义命令相关联的替代形式，因此替代形式表示预定义命令的释义。 为每个预定义的命令生成包括来自预定义命令的字和表示预定义命令的替代形式的表示，例如向量表示。 计算接收到的语音数据与预定义命令的每个表示之间的相似度值，并将语音数据分类为表示与语音数据具有最高相似度值的预定义命令。

公开(公告)号：US08103671B2

公开(公告)日：2012-01-24

申请号：US12249809

申请日：2008-10-10

Applicant: Rakesh Gupta ,  Lev Ratinov

Inventor： Rakesh Gupta ,  Lev Ratinov

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30705

Abstract: The present invention provides a method for incorporating features from heterogeneous auxiliary datasets into input text data for use in classification. Heterogeneous auxiliary datasets, such as labeled datasets and unlabeled datasets, are accessed after receiving input text data. Features are extracted from each of the heterogeneous auxiliary datasets. The features are combined with the input text data to generate a set of features which may potentially be used to classify the input text data. Classification features are then extracted from the set of features and used to classify the input text data. In one embodiment, the classification features are extracted by calculating a mutual information value associated with each feature in the set of features and identifying features having a mutual information value exceeding a threshold value.

Abstract translation: 本发明提供了一种将来自异构辅助数据集的特征结合到用于分类的输入文本数据中的方法。 在接收到输入的文本数据之后，访问异构辅助数据集，如标记的数据集和未标记的数据集。 从各种异构辅助数据集中提取特征。 这些特征与输入文本数据组合以产生可能用于对输入文本数据进行分类的一组特征。 然后从特征集中提取分类特征，并用于对输入文本数据进行分类。 在一个实施例中，通过计算与特征集合中的每个特征相关联的互信息值并且识别具有超过阈值的互信息值的特征来提取分类特征。

公开(公告)号：US20120016826A1

公开(公告)日：2012-01-19

申请号：US13143420

申请日：2009-12-23

Applicant: Narayan Behera ,  Shruti Sinha ,  Rakesh Gupta ,  Ann Geoncy ,  Nevenka Dimitrova

Inventor： Narayan Behera ,  Shruti Sinha ,  Rakesh Gupta ,  Ann Geoncy ,  Nevenka Dimitrova

IPC: G06N3/12

CPC classification number: G06F19/24 ,  G06F19/18 ,  G06F19/20

Abstract: The invention relates to selecting a set of candidate genes from a pool of genes. The method comprising receiving a set of gene data; arranging the set of gene data into a set of clusters with similar profiles by use of a clustering algorithm; and inputting the set of clusters into a genetic algorithm to select a set of candidate genes from the set of clusters. The method thus relates to hybrid between selection by clustering computation and selection by evolutionary computation. This hybrid is also referred to as an evolutionary clustering algorithm (ECA).

Abstract translation: 本发明涉及从一组基因中选择一组候选基因。 该方法包括接收一组基因数据; 通过使用聚类算法将该组基因数据排列成具有相似特征的集合; 以及将所述集合集合输入到遗传算法中以从所述集合集合中选择一组候选基因。 因此，该方法涉及通过聚类计算和通过进化计算进行选择的选择之间的混合。 该混合也称为进化聚类算法（ECA）。

公开(公告)号：US08019713B2

公开(公告)日：2011-09-13

申请号：US11378063

申请日：2006-03-16

Applicant: Rakesh Gupta ,  Ken Hennacy

Inventor： Rakesh Gupta ,  Ken Hennacy

IPC: G06N5/02

CPC classification number: G06N5/00

Abstract: A system and method enable an autonomous machine such as an indoor humanoid robot to systematically process user commands and respond to situations. The method captures distributed knowledge from human volunteers, referred to as “commonsense knowledge.” The commonsense knowledge comprises classes such as steps for tasks, responses to situations, and locations and uses of objects. Filtering refines the commonsense knowledge into useful class rules. A second level of rules referred to as meta-rules performs reasoning by responding to user commands or observed situations, orchestrating the class rules and generating a sequence of task steps. A task sequencer processes the generated task steps and drives the mechanical systems of the autonomous machine.

Abstract translation: 系统和方法使得诸如室内人形机器人的自主机器能够系统地处理用户命令并对情况做出响应。 该方法捕获来自人类志愿者的分布式知识，被称为“常识知识”。常识知识包括诸如任务步骤，对情境的反应以及对象的位置和用途等类。 过滤将常识知识细化为有用的类规则。 称为元规则的第二级规则通过响应用户命令或观察到的情况来执行推理，协调类规则并生成一系列任务步骤。 任务排序器处理生成的任务步骤并驱动自主机器的机械系统。

公开(公告)号：US07939585B2

公开(公告)日：2011-05-10

申请号：US12346012

申请日：2008-12-30

Applicant: Satish Kumar Gaggar ,  Tze Wei Liu ,  Rakesh Gupta ,  Sushant Agarwal ,  Adam Al-Mulla

Inventor： Satish Kumar Gaggar ,  Tze Wei Liu ,  Rakesh Gupta ,  Sushant Agarwal ,  Adam Al-Mulla

IPC: C09K21/04 ,  C08K3/28 ,  C08K3/32 ,  C08L1/00

CPC classification number: C09K21/04 ,  C08K3/32 ,  C08K2003/323 ,  C08L1/02 ,  C08L25/12 ,  C08L51/04 ,  C08L53/02 ,  C08L55/02 ,  C08L97/02 ,  C08L2205/02 ,  C08L2205/03 ,  C09K21/12 ,  C08L2666/26 ,  C08L2666/02

Abstract: Disclosed is a flame-retardant composition comprising (i) 40-66 wt. % alkenyl aromatic resin, (ii) 9-33 wt. % ammonium polyphosphate and (iii) 14-40 wt. % cellulosic material, wherein all weights are based on the total weight of the composition and wherein ammonium polyphosphate and cellulosic material are present in a weight % ratio effective to provide molded articles exhibiting at least V-1 flame rating as determined according to the UL-94 protocol. A process to prepare the composition and articles comprising a composition of the invention and/or made by the process of the invention described herein are also disclosed.

Abstract translation: 公开了一种阻燃组合物，其包含（i）40-66wt。 ％烯基芳族树脂，（ii）9-33重量％ ％聚磷酸铵和（iii）14-40重量％ ％纤维素材料，其中所有重量均基于组合物的总重量，并且其中多磷酸铵和纤维素材料以重量％的比例存在，有效地提供显示至少V-1阻燃等级的模制品，根据UL- 94协议。 还公开了制备包含本发明组合物和/或通过本文所述的本发明方法制备的组合物和制品的方法。

公开(公告)号：US07711717B2

公开(公告)日：2010-05-04

申请号：US11688312

申请日：2007-03-20

Applicant: Rakesh Gupta ,  David Koronthaly ,  Burra Gopal ,  Rolando Jimenez Salgado ,  Shyam Sundar Jayshankar ,  Satish Kumar Chittamuru ,  Himesh Shah ,  Arvind Kumar Krishnan ,  Sushil Kumar ,  Sai Shankar ,  Ashish Kumar Singhal ,  Jagdish Singh

Inventor： Rakesh Gupta ,  David Koronthaly ,  Burra Gopal ,  Rolando Jimenez Salgado ,  Shyam Sundar Jayshankar ,  Satish Kumar Chittamuru ,  Himesh Shah ,  Arvind Kumar Krishnan ,  Sushil Kumar ,  Sai Shankar ,  Ashish Kumar Singhal ,  Jagdish Singh

IPC: G06F17/44

CPC classification number: G06Q10/109

Abstract: Recurring appointment items in a calendaring application are synchronized and recorded in a backend Line Of Business (LOB) service. Items marked in the calendaring application for time recording are used to create a recurring bound item with extended properties. A sweeper module scans on every run the mailbox for such recurring bound items. Occurrences of bound recurring appointments, which occur between the last scan and the current scan, are determined and detached from the corresponding recurring series, such that standalone bound items, are created for such occurrences that can be recognized by an LOB application. Entries for bound items are retrieved from a client data store and synchronized it with the backend LOB service through a create, update, or delete operation request.

Abstract translation: 日历应用程序中的重复预约项目将同步并记录在后端业务线（LOB）服务中。 用于时间记录的日历应用程序中标记的项目用于创建具有扩展属性的循环绑定项。 扫描器模块在每次运行邮箱时扫描此类重复绑定的项目。 确定在最后一次扫描和当前扫描之间出现的绑定循环约会的出现，并从相应的循环序列中分离出来，以便为可由LOB应用程序识别的出现创建独立的绑定项。 从客户端数据存储中检索绑定项的条目，并通过创建，更新或删除操作请求与后端LOB服务进行同步。

公开(公告)号：US20090287762A1

公开(公告)日：2009-11-19

申请号：US12119504

申请日：2008-05-13

Applicant: Burra Gopal ,  Chris Keyser ,  Rolando Jimenez Salgado ,  Rakesh Gupta ,  Manish Soni ,  David Koronthaly ,  Anton Kirillov

Inventor： Burra Gopal ,  Chris Keyser ,  Rolando Jimenez Salgado ,  Rakesh Gupta ,  Manish Soni ,  David Koronthaly ,  Anton Kirillov

IPC: G06F15/16

CPC classification number: H04L67/1095 ,  G06F17/30351 ,  G06F17/30371 ,  G06F17/30578 ,  G06F17/30581

Abstract: Architecture that maintains the user experience as close as possible to the user experience when dealing with the usual/regular forms and data provided in an office application when dealing with hybrid forms and hybrid data. Synchronization of the hybrid data to single-master and multi-masters systems is accomplished when the associated hybrid client goes offline, changes are made to the hybrid data, and then the client comes back online. For example, where the single-master system is a line-of-business (LOB) server system and the multi-master system is an officer server that employs collaboration capability, the architecture allows office users to access, manipulate, and share LOB entity information using collaborative means, while at the same time, ensuring data and business process consistency for the LOB entity in the LOB system.

Abstract translation: 在处理混合形式和混合数据时处理办公应用程序中提供的常规/常规表单和数据时，维护用户体验尽可能接近用户体验的体系结构。 将混合数据同步到单主站和多主站系统时，当相关联的混合客户端脱机时进行，对混合数据进行更改，然后客户端重新联机。 例如，单主系统是业务线（LOB）服务器系统，多主系统是采用协作能力的高级服务器，架构允许办公用户访问，操纵和共享LOB实体 信息使用协同手段，同时确保LOB系统中的LOB实体的数据和业务流程一致性。