公开(公告)号：US10482093B2

公开(公告)日：2019-11-19

申请号：US15100533

申请日：2014-12-10

Applicant: CHINA UNIONPAY CO., LTD.

Inventor： Jun Wang ,  Hongchao Yang

IPC: G06F16/2458 ,  G06F16/28 ,  G06K9/62

Abstract: The present invention proposes a method for data mining, the method comprising: making statistics of the feature vectors of each target object according to the records in a target data set so as to constitute a rough data set, each of the feature vectors including the value of at least one attribute data of the target objects corresponding thereto; screening the feature vectors which correspond to all known the first type of target objects from the rough data set, and performing a filter operation onto the screened feature vectors to obtain samples; and building a regression model based on the samples, and then using the built regression model to determine whether each of all known the second type of target objects potentially belongs to the first type of target objects. The method for data mining disclosed in the present invention is capable of mining and classifying the target objects according to the comprehensive features of the target objects.

公开(公告)号：US20170372331A1

公开(公告)日：2017-12-28

申请号：US15535969

申请日：2015-12-04

Applicant: CHINA UNIONPAY CO., LTD.

Inventor： Hongchao Yang ,  Jianbin Zheng ,  Jun Wang

IPC: G06Q30/02 ,  G06F17/30

CPC classification number: G06Q30/0201 ,  G06F16/29 ,  G06Q30/00 ,  G06Q30/0205 ,  G06Q30/0206

Abstract: The present invention relates to specifying commercial district information of merchants, and it pertains to the technical field of data processing. The method for specifying commercial district information of merchants according to the present invention includes the steps of: mining and calculating association rules of consumption and transaction data of consumers so as to obtain information of association between merchants; calculating rates of subordination of merchants whose commercial district information has not been specified to several commercial districts based on the association information and specified commercial district information of at least some of the merchants; and specifying the commercial district information for each of said merchants based on their rates of subordination. The present invention can realize automatic specification of commercial district information of merchants, and the specification of commercial district information is accurate and efficient.

公开(公告)号：US20160314174A1

公开(公告)日：2016-10-27

申请号：US15100533

申请日：2014-12-10

Applicant: CHINA UNIONPAY CO., LTD.

Inventor： Jun Wang ,  Hongchao Yang

IPC: G06F17/30

CPC classification number: G06F16/2465 ,  G06F16/2462 ,  G06F16/285 ,  G06K9/6267 ,  G06K9/6278 ,  G06K9/6284

Abstract: The present invention proposes a method for data mining, the method comprising: making statistics of the feature vectors of each target object according to the records in a target data set so as to constitute a rough data set, each of the feature vectors including the value of at least one attribute data of the target objects corresponding thereto; screening the feature vectors which correspond to all known the first type of target objects from the rough data set, and performing a filter operation onto the screened feature vectors to obtain samples; and building a regression model based on the samples, and then using the built regression model to determine whether each of all known the second type of target objects potentially belongs to the first type of target objects. The method for data mining disclosed in the present invention is capable of mining and classifying the target objects according to the comprehensive features of the target objects.

Abstract translation: 本发明提出了一种数据挖掘方法，该方法包括：根据目标数据集中的记录，对每个目标对象的特征向量进行统计，构成粗略数据集，每个特征向量包括值 与其对应的目标对象的至少一个属性数据; 从粗略数据集筛选与所有已知的第一类型的目标对象相对应的特征向量，并对筛选的特征向量执行滤波操作以获得样本; 并基于样本建立回归模型，然后使用内建的回归模型来确定所有已知的第二类型的目标对象中的每一个是否潜在地属于第一类型的目标对象。 本发明公开的数据挖掘方法能够根据目标对象的综合特征对目标对象进行挖掘和分类。