技术领域technical field
本发明涉及数据关联，尤其是一种面向政务的多重数据关联验证。The invention relates to data association, in particular to government affairs-oriented multiple data association verification.
背景技术Background technique
政务系统中有时需要进行跨业务或跨部门的数据关联，例如在进行一个人的综合信用评估时，需要从公安系统调出该人的户籍信息，从纳税系统中调出该人的纳税信息，从教育系统中调出该人的教育信息，从车管系统调出该人的行车信息等，通过关联从各系统中调取出的信息来评估此人的综合信用等级。但是如何确保从各系统中调出的信息为同一个人的信息，这就需要进行跨业务跨部门的多重数据关联验证。从各部门各系统中提取出的信息类别杂多，数量较大，这给多重数据项的关联验证带来了很大的挑战。In the government affairs system, cross-business or cross-departmental data association is sometimes required. For example, when conducting a comprehensive credit evaluation of a person, it is necessary to transfer the person’s household registration information from the public security system and the person’s tax payment information from the tax payment system. The education information of the person is transferred from the education system, the driving information of the person is transferred from the vehicle management system, etc., and the comprehensive credit rating of the person is evaluated by correlating the information transferred from each system. However, how to ensure that the information retrieved from each system is the information of the same person requires cross-business and cross-department multiple data association verification. The types of information extracted from various departments and systems are diverse and large in quantity, which brings great challenges to the verification of the association of multiple data items.
发明内容Contents of the invention
本发明所要解决的技术问题是：针对上述存在的问题，提供一种验证结果可靠、验证方法简单的面向政务的多重数据关联验证方法。The technical problem to be solved by the present invention is to provide a multi-data association verification method for government affairs with reliable verification results and simple verification method in view of the above existing problems.
本发明采用的技术方案如下：The technical scheme that the present invention adopts is as follows:
一种面向政务的多重数据项关联验证方法，具体包括步骤：A government-oriented multi-data item association verification method, specifically including the steps of:
(1)提取各数据项的字段表；(1) Extract the field table of each data item;
(2)提取各字段表中的身份信息字段；(2) Extract the identity information field in each field table;
(3)判断各身份信息字段中的身份信息是否指向同一个体，是则判断多重数据项关联合理，否则判断多重数据项关联不合理。(3) Judging whether the identity information in each identity information field points to the same individual, if so, it is judged that the association of multiple data items is reasonable, otherwise it is judged that the association of multiple data items is unreasonable.
进一步地，所述身份信息字段为能够唯一表征个体身份的字段。Further, the identity information field is a field capable of uniquely representing an individual identity.
进一步地，步骤(3)中各身份信息字段类别相同且身份信息相同时判断多重数据项关联合理，各身份信息字段类别相同但身份信息不同时判断多重数据项关联不合理。Further, in step (3), when the identity information fields have the same category and the same identity information, it is judged that the association of multiple data items is reasonable, and when the types of identity information fields are the same but the identity information is different, it is judged that the association of multiple data items is unreasonable.
进一步地，步骤(3)中各身份信息字段类别不完全相同时，将类别不同的身份信息字段按对应关系转换为其余类别相同的身份信息字段，通过比较转换后各相同类别身份信息字段的身份信息是否相同来判断多重数据项关联是否合理。Further, when the categories of the identity information fields in step (3) are not exactly the same, the identity information fields of different categories are converted into the identity information fields of the same category according to the corresponding relationship, and the identity information fields of the same categories of identity information fields are compared and converted. Whether the information is the same is used to judge whether the association of multiple data items is reasonable.
进一步地，步骤(3)中各身份信息字段类别完全不相同时，选择其中一个身份信息字段为主字段，将其他身份信息字段按对应关系转换为主字段类型的身份信息字段，通过比较转换后各相同类别身份信息字段的身份信息是否相同来判断多重数据项关联是否合理。Further, when the categories of the identity information fields in step (3) are completely different, one of the identity information fields is selected as the main field, and the other identity information fields are converted into the identity information fields of the main field type according to the corresponding relationship. Whether the identity information of each identity information field of the same category is the same is used to determine whether the association of multiple data items is reasonable.
进一步地，可在步骤(1)前通过比较数据项类型及各数据项包含字段的数量来进行初步关联验证。Further, preliminary association verification can be performed by comparing the types of data items and the number of fields contained in each data item before step (1).
综上所述，由于采用了上述技术方案，本发明的有益效果是通过判断各数据项身份信息字段中的身份信息是否指向同一个体来判断多重数据项的关联是否合理，验证方法简单，验证结果可靠，能够确保多重数据项间进行合理关联。In summary, due to the adoption of the above technical solution, the beneficial effect of the present invention is to determine whether the association of multiple data items is reasonable by judging whether the identity information in the identity information field of each data item points to the same individual, the verification method is simple, and the verification result Reliable, capable of ensuring reasonable association between multiple data items.
附图说明Description of drawings
本发明将通过例子并参照附图的方式说明，其中：The invention will be illustrated by way of example with reference to the accompanying drawings, in which:
图1为本发明实施例提供的面向政务多重数据项关联验证方法流程图。Fig. 1 is a flow chart of a method for verifying the association of multiple data items for government affairs provided by an embodiment of the present invention.
具体实施方式Detailed ways
本说明书中公开的所有特征，或公开的所有方法或过程中的步骤，除了互相排斥的特征和/或步骤以外，均可以以任何方式组合。All features disclosed in this specification, or steps in all methods or processes disclosed, may be combined in any manner, except for mutually exclusive features and/or steps.
本说明书中公开的任一特征，除非特别叙述，均可被其他等效或具有类似目的的替代特征加以替换。即，除非特别叙述，每个特征只是一系列等效或类似特征中的一个例子而已。Any feature disclosed in this specification, unless specifically stated, can be replaced by other alternative features that are equivalent or have similar purposes. That is, unless expressly stated otherwise, each feature is one example only of a series of equivalent or similar features.
图1提供了本发明实施例提供的面向政务多重数据项关联验证方法流程图，如图1所示，一种面向政务的多重数据项关联验证方法，具体包括步骤：Fig. 1 provides the flow chart of the multi-data item association verification method for government affairs provided by the embodiment of the present invention. As shown in Fig. 1, a multi-data item association verification method for government affairs specifically includes steps:
(1)提取各数据项的字段表；(1) Extract the field table of each data item;
(2)提取各字段表中的身份信息字段；(2) Extract the identity information field in each field table;
(3)判断各身份信息字段中的身份信息是否指向同一个体，是则判断多重数据项关联合理，否则判断多重数据项关联不合理。(3) Judging whether the identity information in each identity information field points to the same individual, if so, it is judged that the association of multiple data items is reasonable, otherwise it is judged that the association of multiple data items is unreasonable.
所述身份信息字段为能够唯一表征个体身份的字段，例如居民身份证号字段、社保号字段、纳税编号字段、车牌号字段等。The identity information field is a field that can uniquely represent an individual's identity, such as a resident ID number field, a social security number field, a tax payment number field, a license plate number field, and the like.
步骤(3)中各身份信息字段类别相同且身份信息相同时判断多重数据项关联合理，各身份信息字段类别相同但身份信息不同时判断多重数据项关联不合理。作为实施例，从户籍系统、纳税系统、车管系统、教育系统中提取出的数据项的身份信息字段类别均包括用户身份证号码字段，则只需比较从各系统提取出的数据项的身份证号码是否相同来判断多重数据项关联是否合理。In step (3), it is judged that the association of multiple data items is reasonable when the categories of the identity information fields are the same and the identity information is the same, and it is judged that the association of multiple data items is unreasonable when the categories of the identity information fields are the same but the identity information is different. As an embodiment, the identity information field categories of the data items extracted from the household registration system, taxation system, vehicle management system, and education system all include the user ID card number field, and then only need to compare the identity of the data items extracted from each system Whether the certificate number is the same to judge whether the association of multiple data items is reasonable.
步骤(3)中各身份信息字段类别不完全相同时，将类别不同的身份信息字段按对应关系转换为其余类别相同的身份信息字段，通过比较转换后各相同类别身份信息字段的身份信息是否相同来判断多重数据项关联是否合理。作为实施例，从户籍系统、纳税系统、车管系统中提取出的数据项的身份信息字段类别均包含用户身份证号字段，从教育系统中提取出的数据项的身份信息字段为学号字段，则根据学号与身份证号码的对应关系将学号字段转换为身份证号码字段，比较从各系统提取出的数据项的身份证号码是否相同来判断多重数据项关联是否合理。When the categories of the identity information fields in step (3) are not exactly the same, convert the identity information fields of different categories into the same identity information fields of the remaining categories according to the corresponding relationship, and compare whether the identity information of the identity information fields of the same category after conversion are the same To judge whether the association of multiple data items is reasonable. As an example, the identity information field categories of the data items extracted from the household registration system, the tax system, and the vehicle management system all include the user ID number field, and the identity information fields of the data items extracted from the education system are student number fields , then convert the student number field into the ID number field according to the corresponding relationship between the student number and the ID number, and compare whether the ID numbers of the data items extracted from each system are the same to determine whether the association of multiple data items is reasonable.
步骤(3)中各身份信息字段类别完全不相同时，选择其中一个身份信息字段为主字段，将其他身份信息字段按对应关系转换为主字段类型的身份信息字段，通过比较转换后各相同类别身份信息字段的身份信息是否相同来判断多重数据项关联是否合理。作为实施例，从户籍系统中提取出的数据项的身份信息字段为身份证号码字段，从纳税系统中提取出的数据项的身份信息字段为纳税编号字段，从教育系统中提取出的数据项的身份信息字段为学号字段，从车管系统中提取出的数据项的身份信息字段为车牌号字段，选择身份证号码字段为主字段，根据纳税编号、学号、车牌号与身份证号的对应关系，将纳税编号字段、学号字段、车牌号字段均转换为身份证号码字段，比较从各系统提取出的数据项的身份证号码是否相同来判断多重数据项关联是否合理。When the categories of the identity information fields in step (3) are completely different, select one of the identity information fields as the main field, convert the other identity information fields into the identity information fields of the main field type according to the corresponding relationship, and compare and convert the same categories Whether the identity information in the identity information field is the same is used to determine whether the association of multiple data items is reasonable. As an example, the identity information field of the data item extracted from the household registration system is an ID card number field, the identity information field of the data item extracted from the tax system is a tax payment number field, and the data item extracted from the education system The identity information field is the student number field, the identity information field of the data item extracted from the vehicle management system is the license plate number field, and the ID number field is selected as the main field, according to the tax number, student number, license plate number and ID number Corresponding relationship, the tax number field, student number field, and license plate number field are all converted into ID number fields, and the ID numbers of the data items extracted from each system are compared to determine whether the association of multiple data items is reasonable.
当数据项字段表中不包括身份信息字段时，如用户姓名字段、家庭住址字段、学历字段等不能唯一表征个体身份的字段，则无法进行多重数据项关联的验证。When the data item field table does not include the identity information field, such as the user name field, home address field, education field and other fields that cannot uniquely represent the identity of the individual, the verification of multiple data item associations cannot be performed.
优化地，可在步骤(1)前通过比较各数据项类型及数据项包含字段的数量来进行初步关联验证。作为实施例，从户籍系统提取出的某人的个人信息数据项关联了从车管系统中提取出的该市车辆信息数据项，两个数据项类型不同且不相关，则可初步判定数据项的关联不合理；从户籍系统提取出的某人的个人信息数据项关联了从纳税系统中提取出的该市18万人口的纳税信息，两数据项包含字段的数量差距很大，则可初步判定数据项的关联不合理。Optimally, preliminary association verification can be performed by comparing the types of each data item and the number of fields contained in the data item before step (1). As an example, a person's personal information data item extracted from the household registration system is associated with the city's vehicle information data item extracted from the vehicle management system. If the two data items are of different types and are not related, the data item can be initially determined The association is unreasonable; the personal information data item of a person extracted from the household registration system is associated with the tax payment information of the city’s 180,000 population extracted from the tax system, and the number of fields contained in the two data items is very different. It is determined that the association of data items is not reasonable.
本发明并不局限于前述的具体实施方式。本发明扩展到任何在本说明书中披露的新特征或任何新的组合，以及披露的任一新的方法或过程的步骤或任何新的组合。The present invention is not limited to the foregoing specific embodiments. The present invention extends to any new feature or any new combination disclosed in this specification, and any new method or process step or any new combination disclosed.
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710521780.8ACN108257061B (en) | 2017-06-30 | 2017-06-30 | Government affair-oriented multiple data item association verification method |
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710521780.8ACN108257061B (en) | 2017-06-30 | 2017-06-30 | Government affair-oriented multiple data item association verification method |
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| CN108257061Atrue CN108257061A (en) | 2018-07-06 |
| CN108257061B CN108257061B (en) | 2023-04-25 |
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| CN201710521780.8AActiveCN108257061B (en) | 2017-06-30 | 2017-06-30 | Government affair-oriented multiple data item association verification method |
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