A method for searching associated data with different credibility, terminal device and storage medium

Abstract

The present invention relates to a method for searching related data with different credibility, a terminal device and a storage medium, wherein the method comprises: S1: collecting related data from multiple data sources according to the types of master data and slave data in the related data to be searched, and grading the data source level of each data according to the credibility of the data source, and marking the source time of each related data; S2: pre-processing the data to eliminate invalid data; S3: setting the correlation level of each slave data according to the number of times each slave data appears in all data corresponding to the same data source level; S4: according to the correlation level and source time of the slave data, in databases of different levels arranged from large to small according to credibility, storing the related data and downgrading the database; S5: searching the slave data corresponding to the master data from the database of the corresponding level according to the required correlation level. The present invention has the characteristics of being able to be updated regularly and having a fast computing speed.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a method for searching associated data with different credibility, a terminal device and a storage medium. Background Art

[0002] In an era of increasing network informatization, the number of Internet users has increased dramatically, 5G technology has been gradually commercialized, the application of mobile terminals, Internet networks, the Internet of Things, sensors and microprocessors has become popular, and the degree of socialization of personal virtual and real information has continued to increase, but data resources are still independent of each other. At the same time, in the process of data collection and judgment, due to manual collection, human errors, outdated data, and errors in the data itself, uncertain data is ultimately generated. The fusion of multivariate data and data trust analysis have become key links in big data analysis and processing. Based on this, new strong trust relationship calculation methods are becoming increasingly important. Summary of the invention

[0003] In order to solve the above problem, the present invention proposes a method for searching associated data with different credibility, a terminal device and a storage medium.

[0004] The specific plan is as follows:

[0005] A method for searching associated data with different credibility includes the following steps:

[0006] S1: According to the types of master data and slave data in the related data to be found, related data is collected from multiple data sources, and the data source level of each data is graded according to the credibility of the data source, and the source time of each related data is marked;

[0007] S2: pre-process the data and remove invalid data;

[0008] S3: setting the association level of each slave data according to the number of times each slave data appears in all data corresponding to the same data source level;

[0009] S4: According to the relevance level and source time of the data, the related data is stored in the database and the database is downgraded in the databases of different levels arranged in descending order of credibility;

[0010] S5: Searching for the slave data corresponding to the master data from the database of the corresponding level according to the required association level.

[0011] Furthermore, the specific method for setting the association level is: determine whether the same master data contains at least two different slave data under the same data source level. If so, set the association level of the associated data corresponding to the master data under the data source level to level n, where n is the maximum association level. Otherwise, set the data level of the associated data equal to the data source level.

[0012] Furthermore, the warehousing rules are as follows: the source time level is set to 1-n levels according to the order of time from small to large; if the association level of the data is i, when its source time is less than the i-level source time, it is stored in the i-level database; when its source time is greater than or equal to the i-level source time, if its source time is between the i+a-level source time and the i+b-level source time, it is stored in the i+b-level database, b>a≥0.

[0013] Furthermore, the database downgrade rules are specifically as follows: setting the maximum data volume corresponding to databases of different levels; determining whether the number of data in the i-th level database is greater than the maximum data volume corresponding to the database of that level; if so, arranging all the data in the i-th level database in ascending order of source time, and cutting the data whose sequence number after sorting exceeds the maximum data volume corresponding to the database of that level to the i+1-th level database.

[0014] A terminal device for searching associated data with different credibility comprises a processor, a memory and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method described above in the embodiment of the present invention are implemented.

[0015] A computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method described above in an embodiment of the present invention are implemented.

[0016] The present invention adopts the above technical solution, based on the strongly associated data of two objects that directly contain or need to calculate a trusted association relationship, and utilizes business attribute thinking to classify them one by one according to time and data source source, and performs multi-dimensional fusion trusted calculation on the graded data that has completed intelligent association to confirm the strongly associated trusted relationship between the two objects. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 Shown is a flow chart of Embodiment 1 of the present invention. DETAILED DESCRIPTION

[0018] To further illustrate various embodiments, the present invention provides drawings. These drawings are part of the disclosure of the present invention, which are mainly used to illustrate the embodiments and can be used in conjunction with the relevant descriptions in the specification to explain the operating principles of the embodiments. With reference to these contents, ordinary technicians in this field should be able to understand other possible implementations and advantages of the present invention.

[0019] The present invention will now be further described with reference to the accompanying drawings and specific implementation methods.

[0020] Embodiment 1:

[0021] The embodiment of the present invention provides a method for searching associated data with different credibility. Figure 1 As shown, the method comprises the following steps:

[0022] S1: According to the types of master data and slave data in the associated data to be found, the associated data is collected from multiple data sources, and the data source level of each data is graded according to the credibility of the data source, and the source time of each associated data is marked.

[0023] Related data is two types of data with an associated relationship, such as a person's ID number and mobile phone number. In this embodiment, the known condition of the two types of data in the related data is set as the primary data, and the condition to be searched is the secondary data, such as searching for the associated secondary data mobile phone number based on the primary data ID number.

[0024] In this embodiment, the data source level is divided into 4 levels in order of credibility from high to low, among which level 1 has the highest credibility and level 4 has the lowest credibility. For example, the data source of level 1 is health code data, the data source of level 2 is express delivery data, and so on.

[0025] The source time of the data is the recording time of the data in the corresponding data source, such as the generation time of the health code data, the mailing time of the express delivery, etc.

[0026] S2: Preprocess the data and remove invalid data.

[0027] Since there may be a lot of invalid data in the collected related data, it is also necessary to clean these invalid data, such as verifying the data bits of multiple ID card numbers.

[0028] S3: setting the association level of each associated data according to the number of different subordinate data contained in the same master data in all associated data corresponding to the same data source level.

[0029] The specific method for setting the association level in this embodiment is: determine whether the same master data contains at least two different slave data under the same data source level. If so, set the association level of the associated data corresponding to the master data under the data source level to level n; otherwise, set the data level of the associated data to be equal to the data source level.

[0030] n is the maximum association level, and the number of association levels is the same as the number of data source levels. In this embodiment, n is set to 4.

[0031] S4: According to the association level and source time of the associated data, the associated data is stored in the database and the database is downgraded in the databases of different levels arranged in descending order of credibility.

[0032] The specific rules for storage are as follows: set the source time level to 1-n levels in order from small to large; if the data is at an associated level of i, when its source time is less than the i-level source time, store it in the i-level database; when its source time is greater than or equal to the i-level source time, if its source time is between the i+a-level source time and the i+b-level source time, store it in the i+b-level database, b>a≥0. i is a positive integer, indicating a sequence number.

[0033] The specific database downgrade rules are as follows: set the maximum data volume corresponding to databases of different levels; determine whether the number of data in the i-th level database is greater than the maximum data volume corresponding to the database of that level. If so, arrange all the data in the i-th level database in ascending order of source time, and cut the data whose sequence number after sorting exceeds the maximum data volume corresponding to the database of that level to the i+1-th level database.

[0034] In this embodiment, the maximum data amounts corresponding to the 1st to 4th level databases are set to be 2, 3, 4, and 5, respectively.

[0035] S5: Searching for the slave data corresponding to the master data from the database of the corresponding level according to the required association level.

[0036] If the required association level is level 2, the mobile phone number corresponding to the ID number is searched from the level 2 database.

[0037] The embodiment of the present invention is based on the strongly associated data of two objects that directly contain or need to calculate a trusted association relationship, and uses business attribute thinking to classify them one by one according to time and data source source, and performs multi-integrated trusted calculation on the graded data that has completed intelligent association to confirm the strongly associated trusted relationship between the two objects. This embodiment can be implemented by creating regular offline tasks to execute, and has the characteristics of regular updates and fast calculation speed.

[0038] Embodiment 2:

[0039] The present invention also provides a terminal device for searching associated data of different credibility, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the above method embodiment of embodiment 1 of the present invention when executing the computer program.

[0040] Further, as an executable solution, the terminal device for searching for associated data with different credibility can be a computing device such as a desktop computer, a notebook, a PDA, and a cloud server. The terminal device for searching for associated data with different credibility can include, but is not limited to, a processor and a memory. Those skilled in the art can understand that the composition structure of the terminal device for searching for associated data with different credibility is only an example of the terminal device for searching for associated data with different credibility, and does not constitute a limitation on the terminal device for searching for associated data with different credibility. It can include more or less components than the above, or a combination of certain components, or different components. For example, the terminal device for searching for associated data with different credibility can also include input and output devices, network access devices, buses, etc., and the embodiment of the present invention does not limit this.

[0041] Further, as an executable solution, the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the different credibility association data search terminal device, and uses various interfaces and lines to connect the various parts of the entire different credibility association data search terminal device.

[0042] The memory can be used to store the computer program and / or module, and the processor realizes various functions of the terminal device for searching for data associated with different credibility by running or executing the computer program and / or module stored in the memory, and calling the data stored in the memory. The memory can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system and at least one application required for a function; the data storage area can store data created according to the use of the mobile phone, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0043] The present invention also provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above method in the embodiment of the present invention are implemented.

[0044] If the module / unit integrated in the terminal device for searching for associated data of different credibility is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the present invention implements all or part of the processes in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium, and the computer program can implement the steps of the above-mentioned various method embodiments when executed by the processor. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, U disk, mobile hard disk, disk, optical disk, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory) and software distribution medium, etc.

[0045] Although the present invention has been specifically shown and described in conjunction with the preferred embodiments, it should be understood by those skilled in the art that various changes may be made to the present invention in form and details without departing from the spirit and scope of the present invention as defined by the appended claims, all of which are within the scope of protection of the present invention.

Claims

1. A method for searching associated data with different credibility, characterized in that: The following steps are involved: S1: According to the types of master data and slave data in the related data to be searched, related data is collected from multiple data sources, and the data source level of each data is graded according to the credibility of the data source, and the source time of each related data is marked; among them, the known conditions are regarded as the master data, and the conditions to be searched are regarded as the slave data; S2: pre-process the data and remove invalid data; S3: according to the number of times each slave data appears in all data corresponding to the same data source level, the association level of each slave data is set; wherein the specific method of setting the association level is: judging whether the same master data contains at least two different slave data under the same data source level, if so, setting the association level of the slave data corresponding to the master data under the data source level to level n, where n is the maximum association level, and the number of the association levels is the same as the number of data source levels, otherwise, setting the data level of the slave data to be equal to the data source level; S4: According to the association level and source time of the secondary data, in databases of different levels arranged in descending order of credibility, the associated data is put into storage and downgraded; the storage operation is specifically: the source time level is set to 1-n levels in descending order of time; if the association level of the secondary data is i, when its source time is less than the i-th source time, it is stored in the i-th database; When its source time is greater than or equal to the i-th level source time, if its source time is between the i+a-th level source time and the i+b-th level source time, it is stored in the i+b-th level database, b>a≥0; S5: Search for slave data corresponding to the master data from the database of the corresponding level according to the required association level; the database downgrade operation is specifically as follows: set the maximum data volume corresponding to databases of different levels; determine whether the number of data in the m-th level database is greater than the maximum data volume corresponding to the database of this level, and if so, arrange all the data in the m-th level database in ascending order according to the source time, and cut the data whose sequence number after sorting exceeds the maximum data volume corresponding to the database of this level to the m+1-th level database.

2. The method for searching associated data with different credibility according to claim 1, characterized in that: The method according to claim 1 is implemented by creating a periodic offline task to execute.

3. A terminal device for searching associated data with different credibility, characterized in that: The method comprises a processor, a memory and a computer program stored in the memory and running on the processor, wherein the processor implements the steps of the method according to any one of claims 1 to 2 when executing the computer program.

4. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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