DATA CUBE GENERATION
    21.
    发明申请
    DATA CUBE GENERATION 有权
    数据库生成

    公开(公告)号:US20170046370A1

    公开(公告)日:2017-02-16

    申请号:US14825132

    申请日:2015-08-12

    CPC classification number: G06F17/30333 G06F17/30572

    Abstract: Disclosed are a computer-implemented method for generating a data cube from data, a system and a computer program product. The method comprises selecting a candidate granularity from a plurality of candidate granularities determined for a dimension of the data cube, where a data distribution obtained in the selected candidate granularity satisfies a predetermined condition; and generating the data cube based on the selected candidate granularity for the dimension.

    Abstract translation: 公开了一种用于从数据,系统和计算机程序产品生成数据立方体的计算机实现的方法。 该方法包括从为数据立方体的维度确定的多个候选粒度中选择候选粒度,其中以所选候选粒度获得的数据分布满足预定条件; 以及基于所选尺寸的候选粒度来生成数据立方体。

    DETERMINING A LOCATION OF A MOBILE DEVICE
    22.
    发明申请
    DETERMINING A LOCATION OF A MOBILE DEVICE 审中-公开
    确定移动设备的位置

    公开(公告)号:US20170013522A1

    公开(公告)日:2017-01-12

    申请号:US15273751

    申请日:2016-09-23

    Abstract: A method and an apparatus for determining a location of a mobile device. The location of a mobile device is determined accurately according to information which includes call data records of the mobile device. By employing a partial ellipse integral model, two physical world factors are taken into consideration in reducing the location uncertainty in call data records. The factors include: spatiotemporal constraints of the device's movement in the physical world and the telecommunication cell area's geometry information, which increase the accuracy of determining the location of a mobile device.

    Abstract translation: 一种用于确定移动设备的位置的方法和装置。 根据包括移动设备的呼叫数据记录的信息,准确地确定移动设备的位置。 通过采用部分椭圆积分模型,在减少呼叫数据记录中的位置不确定性时考虑了两个物理世界因素。 这些因素包括:物理世界中设备移动的时空约束和电信单元区域的几何信息,这增加了确定移动设备位置的准确性。

    Biased Users Detection
    24.
    发明申请
    Biased Users Detection 审中-公开
    偏差用户检测

    公开(公告)号:US20160124965A1

    公开(公告)日:2016-05-05

    申请号:US14886426

    申请日:2015-10-19

    Abstract: Biased users detection. The present invention includes a computer implemented method for detecting biased users and a corresponding apparatus, the computer implemented method including: obtaining comments on a given topic by standard users and users to be detected; calculating respectively scores in attribute dimensions for the given topic by the standard users and the users to be detected according to the comments on the given topic by the standard users and the users to be detected, so as to map respectively the standard users and the users to be detected into a multi-dimensional space formed by a plurality of attribute dimensions, wherein the attribute dimensions reflect aspects of the given topic; and determining whether the users to be detected are biased users according to the similarity of distribution of the users to be detected and that of the standard users in the multi-dimensional space.

    Abstract translation: 偏好用户检测。 本发明包括一种用于检测偏好的用户的计算机实现的方法和相应的装置,所述计算机实现的方法包括:由标准用户和要检测的用户获取关于给定主题的注释; 根据标准用户和要检测的用户对给定主题的评论,由标准用户和要检测的用户分别计算给定主题的属性维度的分数,以分别映射标准用户和用户 被检测成由多个属性维度形成的多维空间,其中属性维度反映给定主题的方面; 以及根据要检测的用户的分布与多维空间中的标准用户的分布的相似度来确定要检测的用户是否是偏向用户。

    Method and apparatus of determining air quality
    25.
    发明授权
    Method and apparatus of determining air quality 有权
    确定空气质量的方法和装置

    公开(公告)号:US09317732B2

    公开(公告)日:2016-04-19

    申请号:US14527132

    申请日:2014-10-29

    CPC classification number: G06K9/66 G01J1/42 G01N33/0062 G06K9/00 G06K9/6256

    Abstract: The present invention discloses a method and apparatus of determining air quality. The method comprising: determining at least one key area; acquiring a reference clear image, a training image under poor air quality and corresponding actual air quality index in at least one location of the key area; and training an air quality model of the key area based on feature extracted from the reference clear image and the training image and based on the actual air quality index. With the method and apparatus of the invention, air quality can be determined based on image.

    Abstract translation: 本发明公开了一种确定空气质量的方法和装置。 该方法包括:确定至少一个关键区域; 在关键区域的至少一个位置获取参考清晰图像,空气质量差的对应实际空气质量指标的训练图像; 并根据参考清晰图像和训练图像提取的特征,并根据实际空气质量指标,对关键区域的空气质量模型进行训练。 利用本发明的方法和装置,可以基于图像确定空气质量。

    IDENTIFYING SUBSURFACE MATERIAL LAYER
    26.
    发明申请
    IDENTIFYING SUBSURFACE MATERIAL LAYER 审中-公开
    识别表面材料层

    公开(公告)号:US20150120195A1

    公开(公告)日:2015-04-30

    申请号:US14527272

    申请日:2014-10-29

    CPC classification number: G01V99/00 G01V2210/62 G01V2210/66

    Abstract: In an approach for identifying subsurface material layers, a computer processor: acquires a well log of a location to be explored, the log comprising data corresponding to multiple geophysical parameters, the data of each parameter comprising measurement values of the parameter at different depths underground; matches a reference data of each parameter corresponding to each of multiple layer transition types with the data of that parameter in the well log at depths underground, wherein each layer transition type indicates an upper material layer and a lower material layer, and the reference data is used to represent a variation trend of the parameter in a transitional zone conforming with the layer transition type; and according to the matching result, determines a layer transition type at the location to be explored and a depth of an interface between the upper material layer and the lower indicated by the layer transition type.

    Abstract translation: 在一种用于识别地下物质层的方法中,计算机处理器:获取要探索的位置的测井记录,所述对数包括对应于多个地球物理参数的数据,每个参数的数据包括在地下不同深度的参数的测量值; 将与多层转移类型中的每一个对应的每个参数的参考数据与地下深井中的该对数据中的该参数的数据进行匹配,其中每个层转换类型表示上层材料层和下层材料层,参考数据为 用于表示符合层过渡类型的过渡区域中参数的变化趋势; 并且根据匹配结果确定要探索的位置处的层转变类型以及由层过渡类型指示的上层材料层和下层之间的界面的深度。

    Transaction data analysis
    27.
    发明授权

    公开(公告)号:US11157820B2

    公开(公告)日:2021-10-26

    申请号:US14954651

    申请日:2015-11-30

    Abstract: Embodiments include predicting transactions by an entity and identifying promotions to offer the entity. Aspects include parsing a plurality of event records corresponding to a plurality of entities respectively. Aspects also include identifying a sequence of events corresponding to the entity and discretizing time intervals and event values of the sequence of events into discrete symbolic values. Aspects further include generating a temporal pattern of events in the sequence of events, the temporal pattern including a sequence of transaction-symbols representative of the time interval and the event value of the events in the sequence of events of the entity and predicting a next transaction based on the temporal pattern.

    Prediction of inhalable particles concentration

    公开(公告)号:US10796036B2

    公开(公告)日:2020-10-06

    申请号:US15230799

    申请日:2016-08-08

    Abstract: In an embodiment of the present disclosure, a method for modeling prediction of inhalable particles concentration is disclosed. In the method, at least one dispersal event is identified, and at least one accumulation event is identified based on the identified at least one dispersal event. Then a dispersal prediction model is generated based on the identified at least one dispersal event. Then at least one accumulation level of inhalable particles concentration is obtained for the at least one accumulation event. A change prediction model for the accumulation level is generated. Then a plurality of accumulation prediction models is generated.

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