公开(公告)号：US09054942B1

公开(公告)日：2015-06-09

申请号：US11960918

申请日：2007-12-20

Applicant: Pieter Joris De Temmerman ,  David R. Azari ,  Daniel Lee Osiecki ,  Ronald Kim Peterson

Inventor： Pieter Joris De Temmerman ,  David R. Azari ,  Daniel Lee Osiecki ,  Ronald Kim Peterson

IPC: G06F15/173 ,  H04L12/26

CPC classification number: H04L43/045 ,  G06F11/3006 ,  G06F11/3065 ,  G06F11/3089 ,  G06F11/323 ,  G06F11/3409 ,  G06F11/3476 ,  G06F17/40 ,  G06F2201/86 ,  H04L41/5009 ,  H04L41/5012 ,  H04L43/00 ,  H04L43/067 ,  H04L67/025 ,  H04L67/1097

Abstract: Various systems, methods, and programs embodied on a computer readable medium that facilitate monitoring of services and servers. In one embodiment, an amount of data is stored in at least one storage device, the data being generated by a plurality of services executed on a plurality of servers, and by the servers upon which the services are executed. A plurality of monitoring applications are executed in a monitoring server, the monitoring applications being configured to perform a plurality of monitoring functions with respect to at least a portion of the data to facilitate an assessment of an operating condition of the services and the servers. An interface layer surrounds the monitoring applications in the monitoring server. The interface layer defines a messaging format that is used by devices external to the interface layer to interact with the monitoring applications.

Abstract translation: 在计算机可读介质上体现的各种系统，方法和程序，便于监视服务和服务器。 在一个实施例中，数据量存储在至少一个存储设备中，数据由在多个服务器上执行的多个服务以及由其执行服务的服务器生成。 在监视服务器中执行多个监视应用，所述监视应用被配置为针对所述数据的至少一部分执行多个监视功能，以便于评估所述服务和所述服务器的操作状况。 界面层围绕监视服务器中的监视应用程序。 接口层定义了由接口层外部的设备用于与监视应用程序交互的消息格式。

公开(公告)号：US20090192966A1

公开(公告)日：2009-07-30

申请号：US12417959

申请日：2009-04-03

Applicant: Eric J. Horvitz ,  David R. Azari ,  Susan T. Dumais ,  Eric D. Brill

Inventor： Eric J. Horvitz ,  David R. Azari ,  Susan T. Dumais ,  Eric D. Brill

IPC: G06N5/02

CPC classification number: G06F17/30684 ,  G06F17/30687 ,  Y10S707/99933

Abstract: The present invention relates to a system and methodology to facilitate extraction of information from a large unstructured corpora such as from the World Wide Web and/or other unstructured sources. Information in the form of answers to questions can be automatically composed from such sources via probabilistic models and cost-benefit analyses to guide resource-intensive information-extraction procedures employed by a knowledge-based question answering system. The analyses can leverage predictions of the ultimate quality of answers generated by the system provided by Bayesian or other statistical models. Such predictions, when coupled with a utility model can provide the system with the ability to make decisions about the number of queries issued to a search engine (or engines), given the cost of queries and the expected value of query results in refining an ultimate answer. Given a preference model, information extraction actions can be taken with the highest expected utility. In this manner, the accuracy of answers to questions can be balanced with the cost of information extraction and analysis to compose the answers.

Abstract translation: 本发明涉及一种便利从诸如万维网和/或其他非结构化来源的大型非结构化语料库提取信息的系统和方法。 通过概率模型和成本效益分析，可以通过这些来源自动构成问题答案形式的信息，以指导基于知识的问答系统采用的资源密集型信息提取程序。 分析可以利用由贝叶斯或其他统计模型提供的系统生成的答案的最终质量的预测。 当与实用新型相结合时，这种预测可以为系统提供对发出给搜索引擎（或引擎）的查询数量的决定的能力，考虑到查询的成本和查询结果的期望值来提炼最终的 回答。 给定一个偏好模型，可以采用最高预期效用的信息提取动作。 以这种方式，可以将问题答案的准确性与信息提取和分析的成本进行平衡，以构成答案。

公开(公告)号：US08799236B1

公开(公告)日：2014-08-05

申请号：US13524155

申请日：2012-06-15

Applicant: David R. Azari ,  Denis V. Batalov ,  Tanvi M. Bhadbhade ,  Lee M. Miller ,  Alan Kipust ,  Theresa M. Hollis

Inventor： David R. Azari ,  Denis V. Batalov ,  Tanvi M. Bhadbhade ,  Lee M. Miller ,  Alan Kipust ,  Theresa M. Hollis

IPC: G06F7/00 ,  G06F17/00

CPC classification number: G06F17/30156

Abstract: When a digital item is submitted for publication, an automated system may determine whether the digital item includes content from other digital items. In some implementations, when the digital item is an electronic book (eBook), the automated system may select sets of words from the eBook and compute hash codes, such that each hash code corresponds to a set of words. The automated system may compare the computed hash codes with retained hash codes associated with other electronic books to determine whether the digital item includes duplicate content.

Abstract translation: 当数字项目被提交出版时，自动化系统可以确定数字项目是否包括来自其他数字项目的内容。 在一些实现中，当数字项目是电子书（eBook）时，自动化系统可以从电子书中选择一组单词并且计算散列码，使得每个散列码对应于一组单词。 自动化系统可以将所计算的散列码与与其他电子书相关联的保留哈希码进行比较，以确定数字项是否包括重复的内容。

公开(公告)号：US08381039B1

公开(公告)日：2013-02-19

申请号：US12493558

申请日：2009-06-29

Applicant: Daniel L. Osiecki ,  Prashant L. Sarma ,  Monty Vanderbilt ,  David R. Azari ,  Caitlyn R. Schmidt

Inventor： Daniel L. Osiecki ,  Prashant L. Sarma ,  Monty Vanderbilt ,  David R. Azari ,  Caitlyn R. Schmidt

IPC: G06F11/34 ,  G06F11/30

CPC classification number: G06F11/34 ,  G06F11/3006 ,  G06F11/3072 ,  G06F17/30533 ,  H04L43/02 ,  H04L43/04 ,  H04L67/10

Abstract: Disclosed in various embodiments are systems and methods providing for storage of mass data such as metrics. A plurality of data models are generated in the server from a stream of metrics describing a state of a system. Each of the metrics is associated with one of a plurality of consecutive periods of time, and each data model represents the metrics associated with a corresponding one of the consecutive periods of time. The data models are stored in a data store and each of the metrics is discarded after use in generating at least one of the data models.

Abstract translation: 在各种实施例中公开的是提供诸如度量的大量数据的存储的系统和方法。 从描述系统状态的度量流在服务器中生成多个数据模型。 每个度量与多个连续时间段中的一个相关联，并且每个数据模型表示与连续时间段中相应的一个相关联的度量。 数据模型存储在数据存储中，并且在使用之后，每个度量被丢弃以生成至少一个数据模型。

公开(公告)号：US08032797B1

公开(公告)日：2011-10-04

申请号：US12493586

申请日：2009-06-29

Applicant: Monty Vanderbilt ,  Prashant L. Sarma ,  David R. Azari ,  Brian Dennehy

Inventor： Monty Vanderbilt ,  Prashant L. Sarma ,  David R. Azari ,  Brian Dennehy

IPC: G06F11/00

CPC classification number: G06F11/3476 ,  G06F2201/875

Abstract: A plurality of data models are generated in a server from a stream of metrics describing a state of at least one system. Each of the data models represents a time grouping of a subset of the metrics. One or more dimensions are associated with each of the metrics. The data models are stored in association with respective ones of the dimensions in a memory. The dimensions with which the data models are associated in the memory are increased based upon an appearance of at least one previously non-existing dimension associated with a metric in the stream.

Abstract translation: 从描述至少一个系统的状态的度量流在服务器中生成多个数据模型。 每个数据模型表示度量的子集的时间分组。 一个或多个维与每个度量相关联。 数据模型与存储器中的相应尺寸相关联地存储。 基于与流中的度量相关联的至少一个先前不存在的维度的外观来增加数据模型在存储器中相关联的维度。

公开(公告)号：US07739215B2

公开(公告)日：2010-06-15

申请号：US12417959

申请日：2009-04-03

Applicant: Eric J. Horvitz ,  David R. Azari ,  Susan T. Dumais ,  Eric D. Brill

Inventor： Eric J. Horvitz ,  David R. Azari ,  Susan T. Dumais ,  Eric D. Brill

IPC: G06F17/00 ,  G06N5/02

CPC classification number: G06F17/30684 ,  G06F17/30687 ,  Y10S707/99933

Abstract: The present invention relates to a system and methodology to facilitate extraction of information from a large unstructured corpora such as from the World Wide Web and/or other unstructured sources. Information in the form of answers to questions can be automatically composed from such sources via probabilistic models and cost-benefit analyses to guide resource-intensive information-extraction procedures employed by a knowledge-based question answering system. The analyses can leverage predictions of the ultimate quality of answers generated by the system provided by Bayesian or other statistical models. Such predictions, when coupled with a utility model can provide the system with the ability to make decisions about the number of queries issued to a search engine (or engines), given the cost of queries and the expected value of query results in refining an ultimate answer. Given a preference model, information extraction actions can be taken with the highest expected utility. In this manner, the accuracy of answers to questions can be balanced with the cost of information extraction and analysis to compose the answers.

Abstract translation: 本发明涉及一种便利从诸如万维网和/或其他非结构化来源的大型非结构化语料库提取信息的系统和方法。 通过概率模型和成本效益分析，可以通过这些来源自动构成问题答案形式的信息，以指导基于知识的问答系统采用的资源密集型信息提取程序。 分析可以利用由贝叶斯或其他统计模型提供的系统生成的答案的最终质量的预测。 当与实用新型相结合时，这种预测可以为系统提供对发出给搜索引擎（或引擎）的查询数量的决定的能力，考虑到查询的成本和查询结果的期望值来提炼最终的 回答。 给定一个偏好模型，可以采用最高预期效用的信息提取动作。 以这种方式，可以将问题答案的准确性与信息提取和分析的成本进行平衡，以构成答案。

公开(公告)号：US07516113B2

公开(公告)日：2009-04-07

申请号：US11469136

申请日：2006-08-31

Applicant: Eric J. Horvitz ,  David R. Azari ,  Susan T. Dumais ,  Eric D. Brill

Inventor： Eric J. Horvitz ,  David R. Azari ,  Susan T. Dumais ,  Eric D. Brill

IPC: G06F17/00 ,  G06N5/02

CPC classification number: G06F17/30684 ,  G06F17/30687 ,  Y10S707/99933

Abstract: The present invention relates to a system and methodology to facilitate extraction of information from a large unstructured corpora such as from the World Wide Web and/or other unstructured sources. Information in the form of answers to questions can be automatically composed from such sources via probabilistic models and cost-benefit analyses to guide resource-intensive information-extraction procedures employed by a knowledge-based question answering system. The analyses can leverage predictions of the ultimate quality of answers generated by the system provided by Bayesian or other statistical models. Such predictions, when coupled with a utility model can provide the system with the ability to make decisions about the number of queries issued to a search engine (or engines), given the cost of queries and the expected value of query results in refining an ultimate answer. Given a preference model, information extraction actions can be taken with the highest expected utility. In this manner, the accuracy of answers to questions can be balanced with the cost of information extraction and analysis to compose the answers.

Abstract translation: 本发明涉及一种便利从诸如万维网和/或其他非结构化来源的大型非结构化语料库提取信息的系统和方法。 通过概率模型和成本效益分析，可以通过这些来源自动构成问题答案形式的信息，以指导基于知识的问答系统采用的资源密集型信息提取程序。 分析可以利用由贝叶斯或其他统计模型提供的系统生成的答案的最终质量的预测。 当与实用新型相结合时，这种预测可以为系统提供对发出到搜索引擎（或引擎）的查询数量的决定的能力，考虑到查询的成本和查询结果的期望值来提炼最终的 回答。 给定一个偏好模型，可以采用最高预期效用的信息提取动作。 以这种方式，可以将问题答案的准确性与信息提取和分析的成本进行平衡，以构成答案。

公开(公告)号：US09361377B1

公开(公告)日：2016-06-07

申请号：US13345525

申请日：2012-01-06

Applicant: David R. Azari ,  Tanvi M. Bhadbhade ,  Lee M. Miller ,  Alan Kipust ,  Cynthia A. Prentice

Inventor： David R. Azari ,  Tanvi M. Bhadbhade ,  Lee M. Miller ,  Alan Kipust ,  Cynthia A. Prentice

IPC: G06F7/00 ,  G06F17/30

CPC classification number: G06F17/30864 ,  G06F17/30029 ,  G06F17/30256 ,  G06F17/30699 ,  G06F17/30707 ,  G06F17/30796

Abstract: Systems, devices, and processes for classifying a digital item are described. In some examples, a first classifier determines whether a digital item, such as an electronic book (eBook), includes content of a first category that is acceptable for publication by a publisher. A second classifier determines whether the digital item includes content of a second category that is acceptable for publication by a publisher. In response to determining that the digital item includes content of the first category or content of the second category, a third classifier may determine whether the digital item includes a phrase that is indicative of content of a third category that is unacceptable for publication.

Abstract translation: 描述用于分类数字项目的系统，设备和过程。 在一些示例中，第一分类器确定诸如电子书（eBook）的数字项目是否包括可由出版商公布的第一类别的内容。 第二分类器确定数字项目是否包括可由发布者发布的第二类别的内容。 响应于确定数字项目包括第一类别的内容或第二类别的内容，第三分类器可以确定数字项目是否包括指示不可接受发布的第三类别的内容的短语。

公开(公告)号：US07454393B2

公开(公告)日：2008-11-18

申请号：US10635274

申请日：2003-08-06

Applicant: Eric J. Horvitz ,  David R. Azari ,  Susan T. Dumais ,  Eric D. Brill

Inventor： Eric J. Horvitz ,  David R. Azari ,  Susan T. Dumais ,  Eric D. Brill

IPC: G06F17/00 ,  G06F17/30 ,  G06N5/02

CPC classification number: G06F17/30684 ,  G06F17/30687 ,  Y10S707/99933

Abstract: The present invention relates to a system and methodology to facilitate extraction of information from a large unstructured corpora such as from the World Wide Web and/or other unstructured sources. Information in the form of answers to questions can be automatically composed from such sources via probabilistic models and cost-benefit analyses to guide resource-intensive information-extraction procedures employed by a knowledge-based question answering system. The analyses can leverage predictions of the ultimate quality of answers generated by the system provided by Bayesian or other statistical models. Such predictions, when coupled with a utility model can provide the system with the ability to make decisions about the number of queries issued to a search engine (or engines), given the cost of queries and the expected value of query results in refining an ultimate answer. Given a preference model, information extraction actions can be taken with the highest expected utility. In this manner, the accuracy of answers to questions can be balanced with the cost of information extraction and analysis to compose the answers.

Abstract translation: 本发明涉及一种便利从诸如万维网和/或其他非结构化来源的大型非结构化语料库提取信息的系统和方法。 通过概率模型和成本效益分析，可以通过这些来源自动构成问题答案形式的信息，以指导基于知识的问答系统采用的资源密集型信息提取程序。 分析可以利用由贝叶斯或其他统计模型提供的系统生成的答案的最终质量的预测。 当与实用新型相结合时，这种预测可以为系统提供对发出给搜索引擎（或引擎）的查询数量的决定的能力，考虑到查询的成本和查询结果的期望值来提炼最终的 回答。 给定一个偏好模型，可以采用最高预期效用的信息提取动作。 以这种方式，可以将问题答案的准确性与信息提取和分析的成本进行平衡，以构成答案。