CN115374094A - Multi-source data fusion method, intelligent terminal and storage medium - Google Patents
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Abstract
The invention provides a multi-source data fusion method, an intelligent terminal and a storage medium, wherein the multi-source data fusion method comprises the following steps: s101: collecting multi-source data, and constructing a multi-source U/C matrix according to field information and sources of the multi-source data; s102: and sequencing the multi-source U/C matrix according to the credibility, and fusing data based on a sequencing result. The invention can reduce the null value rate and improve the accuracy of data, has good data quality, improves the data fusion effect and expands the application range of multi-source data fusion.
Description
Technical Field
The invention relates to the technical field of big data processing, in particular to a multi-source data fusion method, an intelligent terminal and a storage medium.
Background
With the popularization of computers and digital electronic products and the rapid development of the internet, people can contact massive multi-source data every day to fuse the multi-source data and apply the fused data, thereby being beneficial to realizing scientific decision and wider application range.
However, in data fusion, data sources corresponding to multi-source data are dispersedly arranged and are not uniform, and due to different construction times and different acquisition modes of the data sources and different null value constraints on the data, null value rate of the data generated by fusion is high, data quality is poor, and data fusion and application of the fused data are affected.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a multi-source data fusion method, an intelligent terminal and a storage medium, multi-source data are collected, a multi-source U/C matrix is constructed through fields and sources of the multi-source data, the priority of data in different data sources is obtained according to the matrix, and the data are fused based on the priority, so that the empty rate can be reduced, the accuracy of the data is improved, the data quality is good, the data fusion effect is improved, and the application range of the multi-source data fusion is expanded.
In order to solve the above problems, the present invention adopts a technical solution as follows: a multi-source data fusion method, comprising: s101: collecting multi-source data, and constructing a multi-source U/C matrix according to field information and sources of the multi-source data; s102: and sequencing the multi-source U/C matrix according to the credibility, and fusing data based on a sequencing result.
Further, the step of collecting multi-source data specifically includes: and acquiring the format of the data in the data source, and acquiring the data from the data source according to the format.
Further, the step of collecting data from the data source according to the format further comprises: and the data source is connected to acquire the data transmitted by the data source and preprocess the data according to the format of the data.
Further, the step of preprocessing the data according to the format of the data specifically includes: the Chinese fields in the file are converted into English fields.
Further, the step of constructing the multi-source U/C matrix according to the field information and the source of the multi-source data specifically includes: and acquiring a data source corresponding to the data and fields in the data source, and constructing a multi-source U/C matrix according to the corresponding relation between the fields and the data source.
Further, the step of sorting the multi-source U/C matrix according to the confidence level specifically includes: and acquiring the consumers and the producers corresponding to each field according to the multi-source U/C matrix, and sequencing the multi-source U/C matrix based on the credibility of the fields acquired by the consumers and the producers.
Further, the step of sorting the multi-source U/C matrix based on the credibility of the consumer/producer acquisition field specifically includes: and establishing a priority matrix through the credibility based on the credibility of the fields in each data source acquired by the consumer and the producer.
Further, the step of fusing data based on the sorting result specifically includes: and acquiring data to be fused in the multi-source data, determining the credibility of the data to be fused in different data sources according to the priority matrix, and selecting data from the data to be fused for fusion based on credibility sequencing.
Based on the same inventive concept, the invention further provides an intelligent terminal, which comprises a processor and a memory, wherein the processor is in communication connection with the memory, and the memory stores a computer program, and the computer program is used for executing the multi-source data fusion method.
Based on the same inventive concept, the present invention also proposes a computer-readable storage medium storing program data for executing the multi-source data fusion method as described above.
Compared with the prior art, the invention has the beneficial effects that: the method comprises the steps of collecting multi-source data, constructing a multi-source U/C matrix through fields and sources of the multi-source data, obtaining priorities of data in different data sources according to the matrix, and fusing the data based on the priorities, so that the null value rate can be reduced, the accuracy of the data can be improved, the data quality is good, the data fusion effect is improved, and the application range of multi-source data fusion is expanded.
Drawings
FIG. 1 is a flow chart of an embodiment of a multi-source data fusion method of the present invention;
FIG. 2 is a block diagram of an embodiment of an intelligent terminal;
fig. 3 is a block diagram of an embodiment of a computer-readable storage medium of the present invention.
Detailed Description
The following embodiments of the present application are described by specific examples, and other advantages and effects of the present application will be readily apparent to those skilled in the art from the disclosure of the present application. The present application is capable of other and different embodiments and its several details are capable of modifications and/or changes in various respects, all without departing from the spirit of the present application. It should be noted that the various embodiments of the present disclosure, described and illustrated in the figures herein generally, may be combined with each other without conflict, and that the structural components or functional modules therein may be arranged and designed in a variety of different configurations. Thus, the following detailed description of the embodiments of the disclosure, provided in the accompanying drawings, is not intended to limit the scope of the disclosure, as claimed, but is merely representative of selected embodiments of the disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
The terminology used in the description of the present disclosure is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this disclosure and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
Referring to fig. 1, fig. 1 is a flowchart illustrating a multi-source data fusion method according to an embodiment of the present invention. The multi-source data fusion method of the present invention is described with reference to fig. 1.
In this embodiment, the multi-source data fusion method can be applied to intelligent terminals such as mobile phones, computers, tablet computers, and notebook computers, and only needs that the intelligent terminal can acquire data from a plurality of data sources and fuse the data.
According to the method, after the multi-source U/C matrix is built, the fields corresponding to the data in different data sources are sequenced, and when null values occur in data fusion, the data are acquired from the data sources in sequence for supplement, so that the null value rate of the data can be reduced, and the data quality is improved. Specifically, the multi-source data fusion method comprises the following steps:
s101: and collecting multi-source data, and constructing a multi-source U/C matrix according to field information and sources of the multi-source data.
In this embodiment, the step of acquiring multi-source data specifically includes: and acquiring the format of the data in the data source, and acquiring the data from the data source according to the format.
Wherein the step of collecting data from the data source according to the format further comprises: and the data source is connected to acquire the data transmitted by the data source and preprocess the data according to the format of the data.
In this embodiment, the intelligent terminal may store information of data stored in each data source and a connection mode, and after acquiring information of data to be acquired, the intelligent terminal determines a data source for acquiring data through the information, connects with the data source, and acquires corresponding data. The information includes information such as name, type, and update date of the data.
In other embodiments, the intelligent terminal may also acquire information of a data source that needs to acquire data, and after acquiring the information of the data source, the intelligent terminal is connected with the data source to acquire multi-source data.
In one embodiment, the multi-source data is employee data of an enterprise, and the data sources include a recruitment system, a performance assessment system, a human resources system, a financial system, and an OA system. The intelligent terminal acquires information of data to be acquired, acquires a data source for storing the data, and acquires the data from the corresponding data source.
In this embodiment, the step of preprocessing the data according to the format of the data specifically includes: the Chinese fields in the file are converted into English fields. Specifically, whether to preprocess the data is determined according to the format of the data in the data source. And if the format of the acquired data is a database table, not processing. If the format is a file, processing is needed, and the preprocessing is mainly to convert the Chinese field name in the file into English.
In other embodiments, the preprocessing may also include data cleansing, data integration, data transformation, and data reduction to perform the necessary processing of auditing, screening, sorting, etc. of the collected data. Where the data clean-up routine "cleans up" the data by filling in missing values, smoothing out noisy data, identifying or deleting outliers, and resolving inconsistencies. Mainly achieves the following aims: format standardization, abnormal data removal, error correction and repeated data removal. Data integration combines and stores data in multiple data sources uniformly, and data change comprises the step of converting the data into a form suitable for data mining through smooth aggregation, data generalization, normalization and the like. Data reduction can be used to obtain a reduced representation of a data set that is much smaller, but still close to maintaining the integrity of the original data, and results the same or nearly the same as before reduction.
In this embodiment, the step of constructing the multi-source U/C matrix according to the field information and the source of the multi-source data specifically includes: and acquiring a data source corresponding to the data and a field in the data source, and constructing a multi-source U/C matrix according to the corresponding relation between the field and the data source.
In this embodiment, the intelligent terminal prestores field information corresponding to the data to be fused, and searches for a field included in the data of each data source according to the field information. The field information includes information of all fields. Wherein, the field information is obtained by the mode of user input.
In other embodiments, the intelligent terminal may also pre-store field information corresponding to each field keyword, determine the field information according to the field keyword input by the user, and then search for a field included in the data acquired from each data source according to the field information. Or the field contained in each data source is prestored by the intelligent terminal, the field contained in the field information is obtained after the field information input by the user is obtained, and the multi-source U/C matrix is constructed on the basis of the field and the data source containing the field.
In another specific embodiment, the intelligent terminal may further search a keyword from data transmitted by the data source in a keyword search or identification manner, use a keyword in the keyword, which is consistent with the field information, as a field included in the data source, and further construct the multi-source U/C matrix through the field and the data source.
In a specific embodiment, according to the value of cross-department use of data, a field which meets the cross-department business cooperation requirement and reflects the state attribute of the core business entity is selected. The collected multi-source data is employee data, and the field information comprises names, employee numbers, departments, posts, academic calendars, graduates, time of employment, state of employment, salary grades, attendance rates and performance prizes. And searching fields contained in the data of each data source through the field information, thereby obtaining the multi-source U/C matrix. The constructed multi-source U/C matrix is shown in a table I:
watch 1
S102: and sequencing the multi-source U/C matrix according to the credibility, and fusing data based on a sequencing result.
In this embodiment, the step of sorting the multi-source U/C matrix according to the confidence specifically includes: and acquiring the consumers and the producers corresponding to each field according to the multi-source U/C matrix, and sequencing the multi-source U/C matrix based on the credibility of the fields acquired by the consumers and the producers.
The step of sequencing the multi-source U/C matrix based on the credibility of the fields obtained by the consumers and the producers specifically comprises the following steps: and establishing a priority matrix through the credibility based on the credibility of the fields contained in each data source acquired by the consumers and the producers.
In a specific embodiment, the sorting of the multi-source data is specifically based on the credibility of the producer corresponding to the field, and the sorting mode is mainly to determine the credibility (possibly real and accurate degree) of the data by evaluating the generation mode (producer) of the data (field). If the data is automatically generated by the system, the confidence level is considered to be high. For example, the employee number is automatically generated by the human resource system according to the rule, and the reliability of the employee number in the human resource system is very high; if the data is generated by other systems, but the system is clearly checked when in use, such as employee numbers in a financial system, the credibility of the data is higher, and if the data is only manually filled in the system and whether the correct filling has no great influence on the system, the credibility of the data in the system is lower. If there are graduates in the OA system, but the information of the type, location, level, etc. of the graduates is not at all important for the process of the OA system (the process is mainly defined according to the position and role), the data credibility of the graduates in the OA system is low. The priority matrix formed by the data credibility is shown in the second table:
watch two
In this embodiment, the step of fusing data based on the sorting result specifically includes: and acquiring data to be fused in the multi-source data, determining the credibility of the data to be fused in different data sources according to the priority matrix, and selecting data from the data to be fused for fusion based on the credibility ranking. Specifically, when data are fused, if a null value occurs, a field of the null value corresponding to the data to be fused is obtained, reliability ranking of the field in different data sources is obtained according to a priority matrix, and the data are selected to be fused based on the ranking. Data with high reliability is preferentially selected for supplement, so that the null rate of the data is reduced, and the data quality is improved.
Has the advantages that: the multi-source data fusion method provided by the invention collects multi-source data, constructs a multi-source U/C matrix through fields and sources of the multi-source data, acquires the priority of data in different data sources according to the matrix, and fuses the data based on the priority, so that the empty value rate can be reduced, the accuracy of the data is improved, the data quality is good, the data fusion effect is improved, and the application range of multi-source data fusion is expanded.
Based on the same inventive concept, the present invention further provides an intelligent terminal, please refer to fig. 2, fig. 2 is a structural diagram of an embodiment of the intelligent terminal of the present invention, and the intelligent terminal of the present invention is specifically described with reference to fig. 2.
In this embodiment, the intelligent terminal includes a processor and a memory, the processor is connected to the memory in communication, and the memory stores a computer program, and the computer program is used to execute the multi-source data fusion method according to the above embodiment.
It should be noted that the intelligent terminal may include a processor, a memory, a network interface, and a database connected through a system bus. Wherein, the processor of the intelligent terminal is used for providing calculation and control capability. The memory of the intelligent terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the intelligent terminal is used for storing the data involved in the method of the embodiment. The network interface of the intelligent terminal is used for being connected and communicated with an external terminal through a network.
It should be noted that the ProceSsor may be a Central ProceSsing Unit (CPU), other general-purpose ProceSsor, a Digital Signal ProceSsor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf Programmable Gate Array (FPGA) or other Programmable logic device, a discrete Gate or transistor logic device, a discrete hardware component, or the like. The general purpose processor may be a microprocessor or the processor may be any conventional processor or the like, the processor being the control center of the computer device and the various interfaces and lines connecting the various parts of the overall computer device.
The memory may be used to store computer programs and/or modules, and the processor may implement various functions of the computer device by executing or executing the computer programs and/or modules stored in the memory, as well as by invoking data stored in the memory. The memory may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, program instructions for implementing the methods in the above-described embodiments, and the like. The storage data area may store data processed by the program instructions of the method in the above-described embodiments.
Based on the same inventive concept, the present invention further provides a computer-readable storage medium, please refer to fig. 3, fig. 3 is a structural diagram of an embodiment of the computer-readable storage medium of the present invention, and the computer-readable storage medium of the present invention is described with reference to fig. 3.
In the present embodiment, a computer-readable storage medium stores program data used to perform the multi-source data fusion method as described in the above embodiments.
The computer-readable storage medium may include, but is not limited to, floppy diskettes, optical disks, CD-ROMs (compact disc-read only memories), magneto-optical disks, ROMs (read only memories), RAMs (random access memories), EPROMs (erasable programmable read only memories), EEPROMs (electrically erasable programmable read only memories), magnetic or optical cards, flash memory, or other type of media/machine-readable medium suitable for storing machine-executable instructions. The computer readable storage medium may be a product that is not accessed to the intelligent terminal or may be a component that is used by the accessed intelligent terminal.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A multi-source data fusion method, characterized in that the multi-source data fusion method comprises:
s101: collecting multi-source data, and constructing a multi-source U/C matrix according to field information and sources of the multi-source data;
s102: and sequencing the multi-source U/C matrix according to the credibility, and fusing data based on a sequencing result.
2. The multi-source data fusion method of claim 1, wherein the step of collecting multi-source data specifically comprises:
and acquiring the format of the data in the data source, and acquiring the data from the data source according to the format.
3. The multi-source data fusion method of claim 2 wherein the step of collecting data from the data sources according to a format further comprises:
and the data source is connected to acquire the data transmitted by the data source and preprocess the data according to the format of the data.
4. The multi-source data fusion method of claim 3, wherein the step of preprocessing the data according to the format of the data specifically comprises:
the Chinese fields in the file are converted into English fields.
5. The multi-source data fusion method of claim 1, wherein the step of constructing the multi-source U/C matrix according to the field information and the source of the multi-source data specifically comprises:
and acquiring a data source corresponding to the data and fields in the data source, and constructing a multi-source U/C matrix according to the corresponding relation between the fields and the data source.
6. The multi-source data fusion method of claim 5, wherein the step of ranking the multi-source U/C matrices according to confidence specifically comprises:
and acquiring the consumers and the producers corresponding to each field according to the multi-source U/C matrix, and sequencing the multi-source U/C matrix based on the credibility of the fields acquired by the consumers and the producers.
7. The multi-source data fusion method of claim 6, wherein the step of ranking the multi-source U/C matrix based on the confidence level of the consumer/producer acquisition field specifically comprises:
and establishing a priority matrix through the credibility based on the credibility of the fields in each data source acquired by the consumer and the producer.
8. The multi-source data fusion method of claim 7, wherein the step of fusing data based on the sorted results specifically comprises:
and acquiring data to be fused in the multi-source data, determining the credibility of the data to be fused in different data sources according to the priority matrix, and selecting data from the data to be fused for fusion based on credibility sequencing.
9. An intelligent terminal, characterized in that the intelligent terminal comprises a processor, a memory, the processor being connected in communication with the memory, the memory storing a computer program, the computer program being used to execute the multi-source data fusion method according to any one of claims 1-8.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores program data for performing the multi-source data fusion method according to any one of claims 1-8.
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