公开(公告)号：US10089390B2

公开(公告)日：2018-10-02

申请号：US12890060

申请日：2010-09-24

Applicant: Rema Ananthanarayanan ,  Anuradha Bhamidipaty ,  Krishna Kummamuru ,  Debdoot Mukherjee ,  Deepak S. Padmanabhan ,  Vibha Singhal Sinha ,  Biplav Srivastava

Inventor： Rema Ananthanarayanan ,  Anuradha Bhamidipaty ,  Krishna Kummamuru ,  Debdoot Mukherjee ,  Deepak S. Padmanabhan ,  Vibha Singhal Sinha ,  Biplav Srivastava

IPC: G06F17/30

Abstract: Systems and associated methods for automated and semi-automated building of domain models for documents are described. Embodiments provide an approach to discover an information model by mining documentation about a particular domain captured in the documents. Embodiments classify the documents into one or more types corresponding to concepts using indicative words, identify candidate model elements (concepts) for document types, identify relationships both within and across document types, and consolidate and learn a global model for the domain.

公开(公告)号：US08352414B2

公开(公告)日：2013-01-08

申请号：US12575294

申请日：2009-10-07

Applicant: Anuradha Bhamidipaty ,  Krishna Kummamuru ,  Shailabh Nagar ,  Ramendra Sahoo ,  Virendra K. Varshneya ,  Karthik Visweswariah

Inventor： Anuradha Bhamidipaty ,  Krishna Kummamuru ,  Shailabh Nagar ,  Ramendra Sahoo ,  Virendra K. Varshneya ,  Karthik Visweswariah

IPC: G06F7/00 ,  G06F17/00 ,  G06Q10/00

CPC classification number: G06Q10/06 ,  G06Q10/063

Abstract: A system for discovering business processes from noisy activities logs from various activities performed during the execution of the process. Activities are observed from the noisy activity logs that may include text from manually entered activity logs, chat scripts, emails, voice transcripts, desktop captures, and tool logs, wherein the noisy activity logs are received from multiple person/tool actors with each of the actors performing one or more activities related to one/more business tasks. Extracting information from the noisy activity logs to capture activity based information, and then analyzing similar activities and finding possible paths in the similar activities. The results are used to build a process graph based on the similar activities and the possible paths in the similar activities.

Abstract translation: 从执行过程中执行的各种活动中发现来自嘈杂活动日志的业务流程的系统。 从嘈杂的活动日志观察到活动，其中可能包括手动输入的活动日志，聊天脚本，电子邮件，语音记录，桌面捕获和工具日志的文本，其中从多个人/工具演员接收嘈杂活动日志，其中每个 执行与一个/多个业务任务相关的一个或多个活动的演员。 从嘈杂的活动日志中提取信息以捕获基于活动的信息，然后分析类似活动并在类似活动中查找可能的路径。 结果用于根据类似活动和类似活动中可能的路径构建流程图。

公开(公告)号：US20090112588A1

公开(公告)日：2009-04-30

申请号：US11931806

申请日：2007-10-31

Applicant: Krishna Kummamuru ,  Deepak S. Padmanabhan ,  Shourya Roy ,  L. Venkata Subramaniam

Inventor： Krishna Kummamuru ,  Deepak S. Padmanabhan ,  Shourya Roy ,  L. Venkata Subramaniam

IPC: G10L15/06

CPC classification number: G10L15/04 ,  G06F16/355

Abstract: A method is provided for forming discrete segment clusters of one or more sequential sentences from a corpus of communication transcripts of transactional communications that comprises dividing the communication transcripts of the corpus into a first set of sentences spoken by a caller and a second set of sentences spoken by a responder; generating a specified number of sentence clusters by grouping the first and second sets of sentences according to a measure of lexical similarity using an unsupervised partitional clustering method; generating a collection of sequences of sentence types by assigning a distinct sentence type to each sentence cluster and representing each sentence of each communication transcript of the corpus with the sentence type assigned to the sentence cluster into which the sentence is grouped; and generating a specified number of discrete segment clusters by successively merging sentence clusters according to a proximity-based measure between the sentence types assigned to the sentence clusters within sequences of the collection.

Abstract translation: 提供了一种用于从事务通信的通信转录语料库形成一个或多个顺序句子的离散段聚类的方法，其包括将语料库的通信记录分成由呼叫者说出的第一组句子和第二组句子 由答复者 通过使用无监督分数聚类方法，根据词汇相似度的度量，对第一和第二组句子进行分组，从而产生指定数目的句子群; 通过为每个句子集分配不同的句子类型并以分配给句子分组的句子集合的句子类型表示语料库的每个通信录音的每个句子来生成句子序列的集合; 以及通过根据在集合的序列内分配给句子集群的句子类型之间的基于邻近度的度量连续地合并语句集群来生成指定数量的离散分段集群。

公开(公告)号：US06381444B1

公开(公告)日：2002-04-30

申请号：US09614420

申请日：2000-07-12

Applicant: Alok Aggarwal ,  Rema Ananthanaratanan ,  Vipul Bansal ,  Krishna Kummamuru ,  Parul A Mittal ,  Natwar Modani ,  Sreerama K Murthy ,  Atrayee Roychowdhury ,  Satuloori Sridhar

Inventor： Alok Aggarwal ,  Rema Ananthanaratanan ,  Vipul Bansal ,  Krishna Kummamuru ,  Parul A Mittal ,  Natwar Modani ,  Sreerama K Murthy ,  Atrayee Roychowdhury ,  Satuloori Sridhar

IPC: G09B300

CPC classification number: G09B5/02

Abstract: A system for implementing a virtual class and distance education via a computer network is disclosed. The process carried out by the system involves receiving signals from one or more instructor entities, the signals including lesson material designated as belonging to one or more interest groups. The lesson material is sent in advance to student entities listed in one or more of the interest groups to which the lesson material is designated as belonging. Signals from one or more student entities are received requesting admission to a particular class and instructions are sent to student entities to control the display and execution of the lesson material. Interaction amongst student entities, or between student entities and instructor entities, are facilitated and moderated.

Abstract translation: 公开了一种通过计算机网络实现虚拟类和远程教育的系统。 由系统执行的过程涉及从一个或多个指导者实体接收信号，该信号包括被指定为属于一个或多个兴趣组的课材。 课程材料预先发送给在课程材料被指定为属于的一个或多个兴趣组中列出的学生实体。 来自一个或多个学生实体的信号被请求进入特定类别，并且向学生实体发送指令以控制课程材料的显示和执行。 促进和协调学生实体之间或学生实体与教师实体之间的互动。

公开(公告)号：US20170039293A1

公开(公告)日：2017-02-09

申请号：US14817534

申请日：2015-08-04

Applicant: Krishna Kummamuru ,  Abhishek Shivkumar

Inventor： Krishna Kummamuru ,  Abhishek Shivkumar

IPC: G06F17/30

CPC classification number: G06N5/04 ,  G06F16/3329

Abstract: A question is received. The question is in a natural language. The question is mapped to a data mining model. A query associated with the question is determined. The query is related to the data mining model. The query is executed on a dataset of structure data.

Abstract translation: 收到一个问题。 问题是用自然语言。 该问题被映射到数据挖掘模型。 确定与该问题相关联的查询。 查询与数据挖掘模型有关。 查询在结构数据的数据集上执行。

公开(公告)号：US08140523B2

公开(公告)日：2012-03-20

申请号：US12247291

申请日：2008-10-08

Applicant: Sameh A. Fakhouri ,  William F. Jerome ,  Krishna Kummamuru ,  Vijay K. Naik ,  John A. Pershing, Jr. ,  Ajay Raina ,  Pradeep Varma ,  Peter B. Badovinatz ,  Vijay Kumar

Inventor： Sameh A. Fakhouri ,  William F. Jerome ,  Krishna Kummamuru ,  Vijay K. Naik ,  John A. Pershing, Jr. ,  Ajay Raina ,  Pradeep Varma ,  Peter B. Badovinatz ,  Vijay Kumar

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06Q10/04 ,  G06Q10/06

Abstract: A decision support system called Mounties that is designed for managing applications and resources using rule-based constraints in scalable mission-critical clustering environments. Mounties consists of four active service components: (1) a repository of resource proxy objects for modeling and manipulating the cluster configuration; (2) an event notification mechanism for monitoring and controlling interdependent and distributed resources; (3) a rule evaluation and decision processing mechanism; and (4) a global optimization service for providing decision making capabilities. The focus of this paper is on the design of the first three services that together connect and coordinate the distributed resources with the decision making component.

Abstract translation: 一种称为Mounties的决策支持系统，其设计用于在可扩展的任务关键型集群环境中使用基于规则的约束来管理应用程序和资源。 Mounties由四个主动服务组件组成：（1）用于建模和操纵集群配置的资源代理对象的存储库; （2）监测和控制相互依赖和分配的资源的事件通知机制; （3）规则评估和决策处理机制; （4）提供决策能力的全球优化服务。 本文的重点是设计前三个服务，将决策组件连接和协调分布式资源。

公开(公告)号：US07912714B2

公开(公告)日：2011-03-22

申请号：US12060469

申请日：2008-04-01

Applicant: Krishna Kummamuru ,  Deepak S. Padmanaban ,  Shourya Roy ,  L. Venkata Subramaniam

Inventor： Krishna Kummamuru ,  Deepak S. Padmanaban ,  Shourya Roy ,  L. Venkata Subramaniam

IPC: G10L15/06

CPC classification number: G06F17/3071 ,  G10L15/04

Abstract: A method is provided for forming discrete segment clusters of one or more sequential sentences from a corpus of communication transcripts of transactional communications that comprises dividing the communication transcripts of the corpus into a first set of sentences spoken by a caller and a second set of sentences spoken by a responder; generating a set of sentence clusters by grouping the first and second sets of sentences according to a measure of lexical similarity using an unsupervised partitional clustering method; generating a collection of sequences of sentence types by assigning a distinct sentence type to each sentence cluster and representing each sentence of each communication transcript of the corpus with the sentence type assigned to the sentence cluster into which the sentence is grouped; and generating a specified number of discrete segment clusters by successively merging sentence clusters according to a proximity-based measure between the sentence types assigned to the sentence clusters within sequences of the collection.

Abstract translation: 提供了一种用于从事务通信的通信转录语料库形成一个或多个顺序句子的离散段聚类的方法，其包括将语料库的通信记录分成由呼叫者说出的第一组句子和第二组句子 由答复者 通过使用无监督分数聚类方法，根据词汇相似度的度量，对第一和第二组句子进行分组，从而生成一组句子群; 通过为每个句子集分配不同的句子类型并以分配给句子分组的句子集合的句子类型表示语料库的每个通信录音的每个句子来生成句子序列的集合; 以及通过根据在集合的序列内分配给句子集群的句子类型之间的基于邻近度的度量连续地合并语句集群来生成指定数量的离散分段集群。

公开(公告)号：US06925460B2

公开(公告)日：2005-08-02

申请号：US09815616

申请日：2001-03-23

Applicant: Krishna Kummamuru ,  Raghuram Krishnapuram ,  Pradeep Kumar Dubey

Inventor： Krishna Kummamuru ,  Raghuram Krishnapuram ,  Pradeep Kumar Dubey

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30719 ,  G06F17/3071 ,  Y10S707/99933 ,  Y10S707/99935

Abstract: The present invention relates to a method, system and computer program product for clustering data points and its application to text summarization, customer profiling for web personalization and product cataloging.The method for clustering data points with defined quantified relationships between them comprises the steps of obtaining lead value for each data point either by deriving from said quantified relationships or as given input, ranking each data point in a lead value sequence list in descending order of lead value, assigning the first data point in said lead value sequence list as the leader of the first cluster, and considering each subsequent data point in said lead value sequence list as a leader of a new cluster if its relationship with the leaders of each of the previous clusters is less than a defined threshold value or as a member of one or more clusters where its relationship with the cluster leader is more than or equal to said threshold value. The said relationships between data points are symmetric or asymmetric. Similarly, system and computer program product have also been claimed.

Abstract translation: 本发明涉及用于聚类数据点的方法，系统和计算机程序产品及其应用于文本摘要，用于web个性化和产品编目的客户分析。 用于对其中具有定义的量化关系的数据点进行聚类的方法包括以下步骤：通过从所述量化关系导出或作为给定输入来获取每个数据点的引导值，以引导值序列表中的每个数据点按铅的降序排列 将所述引导值序列列表中的第一数据点分配为第一簇的引导符，并且如果其与每个的引导者的关系，则将所述引导值序列列表中的每个后续数据点视为新簇的引导者 先前的簇小于定义的阈值，或作为其与簇首的关系大于或等于所述阈值的一个或多个簇的成员。 数据点之间的关系是对称的或不对称的。 类似地，系统和计算机程序产品也被要求。

公开(公告)号：US20120124592A1

公开(公告)日：2012-05-17

申请号：US12944935

申请日：2010-11-12

Applicant: Krishna Kummamuru

Inventor： Krishna Kummamuru

IPC: G06F9/50

CPC classification number: G06F9/5055 ,  G06Q10/06311 ,  H04L67/327

Abstract: Methods and arrangements for more efficiently enhancing the personalization and customization of services while avoiding an undue overburdening of personnel, infrastructure or resources. An input service component comprising a plurality of tasks is assimilated, similarity among the tasks is determined, and output service components are routed to resources based on similarity among the tasks, the service components each comprising a subgroup of similar tasks.

Abstract translation: 更有效地增强服务个性化和定制化的方法和安排，同时避免人员，基础设施或资源过度负担过重。 包括多个任务的输入服务组件被同化，确定任务之间的相似性，并且基于任务之间的相似性将输出服务组件路由到资源，每个服务组件包括类似任务的子组。

公开(公告)号：US20090112571A1

公开(公告)日：2009-04-30

申请号：US12060469

申请日：2008-04-01

Applicant: Krishna Kummamuru ,  Deepak S. Padmanabhan ,  Shourya Roy ,  L. Venkata Subramaniam

Inventor： Krishna Kummamuru ,  Deepak S. Padmanabhan ,  Shourya Roy ,  L. Venkata Subramaniam

IPC: G06F17/20

CPC classification number: G06F17/3071 ,  G10L15/04

Abstract: A method is provided for forming discrete segment clusters of one or more sequential sentences from a corpus of communication transcripts of transactional communications that comprises dividing the communication transcripts of the corpus into a first set of sentences spoken by a caller and a second set of sentences spoken by a responder; generating a set of sentence clusters by grouping the first and second sets of sentences according to a measure of lexical similarity using an unsupervised partitional clustering method; generating a collection of sequences of sentence types by assigning a distinct sentence type to each sentence cluster and representing each sentence of each communication transcript of the corpus with the sentence type assigned to the sentence cluster into which the sentence is grouped; and generating a specified number of discrete segment clusters by successively merging sentence clusters according to a proximity-based measure between the sentence types assigned to the sentence clusters within sequences of the collection.

Abstract translation: 提供了一种用于从事务通信的通信转录语料库形成一个或多个顺序句子的离散段聚类的方法，其包括将语料库的通信记录分成由呼叫者说出的第一组句子和第二组句子 由答复者 通过使用无监督分数聚类方法，根据词汇相似度的度量，对第一和第二组句子进行分组，从而生成一组句子群; 通过为每个句子集分配不同的句子类型并以分配给句子分组的句子集合的句子类型表示语料库的每个通信录音的每个句子来生成句子序列的集合; 以及通过根据在集合的序列内分配给句子集群的句子类型之间的基于邻近度的度量连续地合并语句集群来生成指定数量的离散分段集群。