Foreign organization name matching

    公开(公告)号:US09836532B2

    公开(公告)日:2017-12-05

    申请号:US14969345

    申请日:2015-12-15

    IPC分类号: G06F17/30 G06F17/28

    摘要: Embodiments include a system, method, and computer program product for foreign organization name matching. Aspects include receiving a first entity name from a first database configured in a first language and receiving a second database, wherein the second database includes a plurality of entity names in a second language, wherein the first and second languages are different. Aspects also include performing an Internet search based on the first entity name, wherein a language setting of the Internet search is configured to the second language and identifying a list of candidate names based on a set of results from the Internet search. Another aspect includes filtering the list to obtain a resulting candidate name and determining whether the resulting candidate name matches one of the entity names in the second database. Aspects include associating the first entity name and a matching entity name in the second database based on the determination.

    Method and apparatus for evaluating predictive model

    公开(公告)号:US09684634B2

    公开(公告)日:2017-06-20

    申请号:US14314308

    申请日:2014-06-25

    IPC分类号: G06F17/18 G06Q10/06 G06K9/62

    摘要: In an approach for evaluating a predictive model, a computer identifies features of training samples in a set of training samples and selects at least one evaluation metric from a set of evaluation metrics as one or more available metrics based on the identified features. The computer applies a predictive model created based on the set of training samples to a set of test samples so as to calculate values of the one or more available metrics and evaluates the predictive model by using the one or more available metrics and the values of the available metrics. With the technical solutions described with respect to the embodiments of the present invention, one or more evaluation metrics that are applicable to specific training sample features may be determined from several evaluation metrics, so that users can precisely evaluate predictive models by using the determined evaluation metrics.

    FOREIGN ORGANIZATION NAME MATCHING

    公开(公告)号:US20170124186A1

    公开(公告)日:2017-05-04

    申请号:US15131281

    申请日:2016-04-18

    IPC分类号: G06F17/30

    摘要: Embodiments include a system, method, and computer program product for foreign organization name matching. Aspects include receiving a first entity name from a first database configured in a first language and receiving a second database, wherein the second database includes a plurality of entity names in a second language, wherein the first and second languages are different. Aspects also include performing an Internet search based on the first entity name, wherein a language setting of the Internet search is configured to the second language and identifying a list of candidate names based on a set of results from the Internet search. Another aspect includes filtering the list to obtain a resulting candidate name and determining whether the resulting candidate name matches one of the entity names in the second database. Aspects include associating the first entity name and a matching entity name in the second database based on the determination.

    FOREIGN ORGANIZATION NAME MATCHING

    公开(公告)号:US20170124185A1

    公开(公告)日:2017-05-04

    申请号:US14926200

    申请日:2015-10-29

    IPC分类号: G06F17/30 G06F17/28

    摘要: Embodiments include a system, method, and computer program product for foreign organization name matching. Aspects include receiving a first entity name from a first database configured in a first language and receiving a second database, wherein the second database includes a plurality of entity names in a second language, wherein the first and second languages are different. Aspects also include performing an Internet search based on the first entity name, wherein a language setting of the Internet search is configured to the second language and identifying a list of candidate names based on a set of results from the Internet search. Another aspect includes filtering the list to obtain a resulting candidate name and determining whether the resulting candidate name matches one of the entity names in the second database. Aspects include associating the first entity name and a matching entity name in the second database based on the determination.

    MONITORING INTERESTING SUBJECTS
    7.
    发明申请
    MONITORING INTERESTING SUBJECTS 有权
    监督有关事宜

    公开(公告)号:US20150006634A1

    公开(公告)日:2015-01-01

    申请号:US14297770

    申请日:2014-06-06

    IPC分类号: H04L12/26 H04L29/08

    摘要: Methods and systems for monitoring interesting subjects. A method including: selecting, based on a first collection of interesting subjects, a set of critical nodes including at least one critical node which participates in one or more interesting subjects in the first collection; and monitoring contents posted by the one or more critical nodes in the set so as to find a second collection of interesting subjects. The set of critical nodes which participate in one or more interesting subjects in the first collection of interesting subjects is selected based on the first collection, as objects to be monitored, thereby reducing the number of contents posted by the nodes to be monitored as compared with monitoring all the user nodes, so that interesting subjects such as hot news or hot events can be found in real time with high efficiency and low cost.

    摘要翻译: 监测有趣科目的方法和系统。 一种方法,包括:基于感兴趣对象的第一集合来选择一组关键节点,所述关键节点包括参与第一集合中的一个或多个感兴趣对象的至少一个关键节点; 以及监视由集合中的一个或多个关键节点发布的内容,以便找到有趣主体的第二集合。 基于作为要监视的对象的第一集合来选择参与感兴趣对象的第一集合中的一个或多个感兴趣对象的关键节点的集合,从而减少要被监视的节点发布的内容的数量, 监控所有用户节点,从而可以实时,高效率,低成本地查找热点新闻或热点事件等有趣的主题。

    METHOD AND APPARATUS OF ESTIMATING WAVE VELOCITY OF NEGATIVE PRESSURE WAVE IN A FLUID TRANSPORTATION PIPELINE
    8.
    发明申请
    METHOD AND APPARATUS OF ESTIMATING WAVE VELOCITY OF NEGATIVE PRESSURE WAVE IN A FLUID TRANSPORTATION PIPELINE 有权
    估计流体输送管道中负压波浪波速的方法和装置

    公开(公告)号:US20140142870A1

    公开(公告)日:2014-05-22

    申请号:US14050698

    申请日:2013-10-10

    IPC分类号: G01F9/00

    CPC分类号: G01M3/2815

    摘要: A method and apparatus for estimating a wave velocity of negative pressure wave in a fluid transportation pipeline. The method including: receiving a plurality of pressure signals from a plurality of sensors; determining time differences produced by the negative pressure wave reaching the adjacent sensors based on the received pressure signals; determining a wave source sensor segment where a wave source of the negative pressure wave is located; and estimating the wave velocities of the negative pressure wave in a non-wave source sensor segment and the wave source sensor segment.

    摘要翻译: 一种用于估计流体输送管线中的负压波的波速的方法和装置。 该方法包括:从多个传感器接收多个压力信号; 基于接收到的压力信号确定由负压波到达相邻传感器产生的时间差; 确定负压波的波源所在的波源传感器段; 并估计非波源传感器段和波源传感器段中负压波的波速。

    Genome compression and decompression

    公开(公告)号:US10679727B2

    公开(公告)日:2020-06-09

    申请号:US15101946

    申请日:2014-10-11

    摘要: The present invention relates to a method and apparatus for genome compression and decompression. In one embodiment of the present invention, there is a method for genome compression, including: selecting from a reference database a reference genome that matches the genome; building an index based on positions of the reference genome's multiple segments in the reference genome; aligning the genome with the reference genome based on the multiple segments so as to identify difference data between the genome and the reference genome; and generating a compressed genome, the compressed genome including at least the index and the difference data. In other embodiments, there is provided an apparatus for genome compression. Further, there is a method and apparatus for decompressing the genome that has been compressed using the above method and apparatus.

    Multi-layer information fusing for prediction

    公开(公告)号:US10679143B2

    公开(公告)日:2020-06-09

    申请号:US15200509

    申请日:2016-07-01

    IPC分类号: G06N20/00

    摘要: A method of generating a predictor to classify data includes: training each of a plurality of first classifiers arranged in a first level on current training data; operating each classifier of the first level on the training data to generate a plurality of predictions; combining the current training data with the predictions to generated new training data; and training each of a plurality of second classifiers arranged in a second level on the new training data. The first classifiers are classifiers of different classifier types, respectively and the second classifiers are classifiers of the different classifier types, respectively.