Centroid detection for clustering

    公开(公告)号:US09727633B1

    公开(公告)日:2017-08-08

    申请号:US15048904

    申请日:2016-02-19

    CPC classification number: G06F17/30598

    Abstract: A method of categorizing data points is described which, when combined with a clustering algorithm, provides groupings of data points that have an improved confidence interval. The method can be used to find an optimal number of groupings for a dataset, which in turn allows a user to categorize a group of data points for processing. In some examples, a dataset containing a number of data points may be accessed. Additionally, in some aspects, groupings of data points within the dataset may be grouped based at least in part on similarities between the data. Further, a number of groupings of data points may be adjusted so that the distance between the data points within one or more groupings of data points may fit within a confidence level.

    Remote messaging protocol
    2.
    发明授权
    Remote messaging protocol 有权
    远程消息协议

    公开(公告)号:US09491261B1

    公开(公告)日:2016-11-08

    申请号:US13953081

    申请日:2013-07-29

    CPC classification number: H04L67/40 H04L69/16 H04L69/22

    Abstract: Processes and systems are disclosed for a remote messaging protocol that combines application data and reliability information into a three-packet handshake exchange. Each packet may comprise message information indicating an initial packet, or an acknowledgement packet, along with a unique identifier for identifying responses to the initial message. Time-to-live and retransmission timers may be used in order to increase reliability of the protocol.

    Abstract translation: 公开了将应用数据和可靠性信息组合成三包握手交换的远程消息协议的过程和系统。 每个分组可以包括指示初始分组的消息信息或确认分组,以及用于识别对初始消息的响应的唯一标识符。 可以使用生存时间和重传定时器来提高协议的可靠性。

    Centralized management of computing resources across service provider networks

    公开(公告)号:US11032213B1

    公开(公告)日:2021-06-08

    申请号:US16220682

    申请日:2018-12-14

    Abstract: This disclosure describes techniques for centralizing the management of computing resources that are provisioned across multiple service provider networks by infrastructure modeling services. A service provider network may host or provide a centralized management service that supports an open source framework that provides users, or developers, with a unified development interface to manage computing resources that are provisioned in different service provider networks. The unified development interface of the host service provider network may provide users with a meta schema or language format to create infrastructure schemas for modeling, provisioning, and operating computing resources across service provider networks that are managed by different service providers. Additionally, the host service provider network may provide an open provider registry where developers of infrastructure schemas may store and publish infrastructure schemas for the different service provider networks to share computing resource types with other developers or users of cloud-based services.

    Centroid detection for clustering
    5.
    发明授权
    Centroid detection for clustering 有权
    聚类的质心检测

    公开(公告)号:US09280593B1

    公开(公告)日:2016-03-08

    申请号:US13949526

    申请日:2013-07-24

    CPC classification number: G06F17/30598

    Abstract: A method of categorizing data points is described which, when combined with a clustering algorithm, provides groupings of data points that have an improved confidence interval. The method can be used to find an optimal number of groupings for a dataset, which in turn allows a user to categorize a group of data points for processing. In some examples, a dataset containing a number of data points may be accessed. Additionally, in some aspects, groupings of data points within the dataset may be grouped based at least in part on similarities between the data. Further, a number of groupings of data points may be adjusted so that the distance between the data points within one or more groupings of data points may fit within a confidence level.

    Abstract translation: 描述了对数据点进行分类的方法,当与聚类算法组合时,提供具有改进的置信区间的数据点的分组。 该方法可用于找到数据集的最佳分组数,这又允许用户对一组数据点进行分类以进行处理。 在一些示例中,可以访问包含多个数据点的数据集。 另外,在一些方面,可以至少部分地基于数据之间的相似性来对数据集内的数据点进行分组。 此外,可以调整多个数据分组,使得一个或多个数据点分组之间的数据点之间的距离可以适合置信水平。

    UNIFIED PUBLICATION SEARCH AND CONSUMPTION INTERFACE

    公开(公告)号:US20170206275A1

    公开(公告)日:2017-07-20

    申请号:US15478081

    申请日:2017-04-03

    Abstract: A user device sends a search query for an item to a first data store associated with a first entity, wherein the item comprises at least one of an electronic version or a physical version, determines a format to be used by search queries to the second data store and generates a first modified search query for the second data store that is different than the search query and corresponds to the format. The user device sends the first modified search query to the second data store, receives item search results from the first data store and item search results from the second data store, the item search results indicating at least one of: the electronic version is available from an electronic location, the physical version is available at a physical location, or the physical location at which the physical version is available, and causes presentation of at least a portion of the item search results from the first data store together with at least a portion of the item search results from the second data store.

    Machine generated service cache
    10.
    发明授权
    Machine generated service cache 有权
    机器生成的服务缓存

    公开(公告)号:US09245232B1

    公开(公告)日:2016-01-26

    申请号:US13774767

    申请日:2013-02-22

    CPC classification number: G06N99/005 G06F17/30902

    Abstract: A machine generated service cache that utilizes one or more machine learning classifiers is trained using service requests directed to a human-generated service and service responses generated by the human-generated service in response to the service requests. Once the machine generated service cache has been trained to a predetermined level of performance, the machine generated service cache can be utilized to process actual service requests directed to the human-generated service. The machine generated service cache might be utilized to process service requests for which it is not essential that the returned service response be identical to a response that would be generated by the human-generated service.

    Abstract translation: 利用一个或多个机器学习分类器的机器生成的服务高速缓冲存储器是使用针对人类产生的服务的服务请求和由人类生成的服务响应于服务请求生成的服务响应进行训练的。 一旦机器生成的服务高速缓存已经被训练到预定的性能水平,则机器产生的服务高速缓存可以用于处理针对人造服务的实际服务请求。 机器生成的服务高速缓存可以用于处理服务请求,其中所返回的服务响应与由人为生成的服务生成的响应相同并不是必需的。

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