CN114328627B - Data right-determining analysis method, device and medium based on big data - Google Patents
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Abstract
The application discloses a data right-determining analysis method, equipment and medium based on big data, which are used for solving the technical problems of ambiguous attribution right and low data right-determining efficiency of the existing data. The method comprises the following steps: determining a plurality of field names in commodity information of a first data commodity to be put on shelf so as to determine a first data information value corresponding to the first data commodity; querying a pre-built search engine to determine a plurality of second data information values having a similarity to the first data information values; selecting a second data information value with the maximum similarity with the first data information value, and acquiring a second data commodity corresponding to the second data information value when the similarity corresponding to the second data information value exceeds a preset threshold; and comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity to determine that the first data commodity is successful in right confirmation, and storing the first data information value into the search engine, so that the data right confirmation efficiency is improved.
Description
Technical Field
The present application relates to the field of data resource management technologies, and in particular, to a method, an apparatus, and a medium for data right analysis based on big data.
Background
Currently, big data has a great market demand, and its tradable nature is also demonstrated in practice. The big data transaction industry chain comprises big data right confirmation, big data asset assessment, big data matching, big data financing, big data index and the like. Data validation is the primary core of the big data transaction industry chain. The main body of big data right is mainly composed of big data exchange, industry organization, data service provider, large internet enterprises and other non-government institutions. Title circulation of big data is supported by the country in policy, but lacks in the definition of title, so that the efficiency of data right-checking is affected to a certain extent.
Disclosure of Invention
The embodiment of the application provides a data right-confirming analysis method, device and medium based on big data, which are used for solving the technical problem of low right-confirming efficiency of data caused by the fact that the attribution right of the data is not clear in the prior art.
In one aspect, an embodiment of the present application provides a data right analysis method based on big data, including: acquiring commodity information corresponding to a first data commodity to be put on shelf, and determining a plurality of field names in the commodity information so as to determine a first data information value corresponding to the first data commodity according to the field names; inquiring a search engine which is built in advance according to the first data information value to determine a plurality of second data information values which have similarity with the first data information value; each second data information value is a data information value corresponding to one data commodity in the search engine; selecting a second data information value with the maximum similarity with the first data information value from a plurality of second data information values, and acquiring a second data commodity corresponding to the second data information value with the maximum similarity with the first data information value when the similarity corresponding to the second data information value exceeds a preset threshold value; and determining a right-confirming result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, and if the right is confirmed successfully, storing the first data information value into the search engine.
In an implementation manner of the present application, before acquiring the commodity information corresponding to the first data commodity to be put on the shelf, the method further includes: determining the portrait of a corresponding user according to commodity browsing information and purchasing records of the corresponding user of the first data commodity to be put on shelf, and acquiring identity information of the corresponding user; and authenticating the qualification information of the corresponding user according to the portrait of the corresponding user, and authenticating the identity information of the corresponding user in a preset retrieval mode.
In an implementation manner of the present application, before querying a search engine built in advance according to the first data information value, the method further includes: acquiring a plurality of second data commodities for carrying out transactions from an existing transaction system; determining a second data information value corresponding to a second data commodity according to a plurality of field names corresponding to the second data commodity; and storing the acquired second data information values corresponding to the plurality of second data commodities into a search engine.
In one implementation manner of the present application, the querying a search engine built in advance according to the first data information value to determine a plurality of second data information values having similarity with the first data information value specifically includes: inquiring a search engine built in advance according to the first data information value; determining second data information values corresponding to a plurality of second data commodities in the search engine respectively through a preset character string similarity comparison tool, and converting the second data information values into editing operation times required by the first data information values corresponding to the first data commodities; and respectively determining the second data information value corresponding to each data commodity in the plurality of second data commodities in the search engine according to the editing operation times required by the second data information values corresponding to the plurality of second data commodities, and the similarity between the second data information value and the first data information value corresponding to the first data commodity.
In one implementation of the present application, the storing the first data information value in the search engine specifically includes: determining data identification information corresponding to the first data commodity according to a first data information value corresponding to the first data commodity, so as to identify the first data information value corresponding to the first data commodity through the corresponding data identification information; and storing the first data information value corresponding to the first data commodity with the identification into the search engine.
In one implementation manner of the present application, after determining the right result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, the method further includes: determining the position information of a user corresponding to the first data commodity based on the acquired commodity information corresponding to the first data commodity; and feeding back the right confirmation result of the first data commodity to the corresponding user according to the position information of the corresponding user.
In one implementation manner of the present application, when the determining that the right of the first data commodity is successful by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, the method further includes: transmitting a first data information value corresponding to the first data commodity to a third party right-determining center; verifying the first data commodity through the third party right verification center, and determining a corresponding right verification certificate for the first data commodity after the first data commodity passes the verification; and issuing the corresponding right-determining certificate to the user corresponding to the first data commodity, so that the corresponding user can prove the first data commodity according to the right-determining certificate.
In one implementation manner of the present application, when the comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, determining that the first data commodity fails to confirm the right, the method further includes: the first data commodity and the personal information of the user corresponding to the first data commodity are sent to the user corresponding to the second data information value with the maximum similarity to the first data information value; and notifying the user corresponding to the second data information value with the maximum similarity to the first data information value to perform infringement evidence.
On the other hand, the embodiment of the application also provides a data right analysis device based on big data, which comprises: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to: acquiring commodity information corresponding to a first data commodity to be put on shelf, and determining a plurality of field names in the commodity information so as to determine a first data information value corresponding to the first data commodity according to the field names; inquiring a search engine which is built in advance according to the first data information value to determine a plurality of second data information values which have similarity with the first data information value; each second data information value is a data information value corresponding to one data commodity in the search engine; selecting a second data information value with the maximum similarity with the first data information value from a plurality of second data information values, and acquiring a second data commodity corresponding to the second data information value with the maximum similarity with the first data information value when the similarity corresponding to the second data information value exceeds a preset threshold value; and determining a right-confirming result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, and if the right is confirmed successfully, storing the first data information value into the search engine.
In another aspect, embodiments of the present application also provide a non-volatile computer storage medium storing computer-executable instructions configured to: acquiring commodity information corresponding to a first data commodity to be put on shelf, and determining a plurality of field names in the commodity information so as to determine a first data information value corresponding to the first data commodity according to the field names; inquiring a search engine which is built in advance according to the first data information value to determine a plurality of second data information values which have similarity with the first data information value; each second data information value is a data information value corresponding to one data commodity in the search engine; selecting a second data information value with the maximum similarity with the first data information value from a plurality of second data information values, and acquiring a second data commodity corresponding to the second data information value with the maximum similarity with the first data information value when the similarity corresponding to the second data information value exceeds a preset threshold value; and determining a right-confirming result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, and if the right is confirmed successfully, storing the first data information value into the search engine.
The embodiment of the application provides a data right analysis method, equipment and medium based on big data, which at least comprise the following beneficial effects: determining a first data information value corresponding to the first data commodity through the field names in the obtained commodity information of the first data commodity to be put on shelf, so that the data values corresponding to a plurality of field names in the commodity information corresponding to the first data commodity to be put on shelf can be combined into data with a long character string type, and the first data commodity can be taken as a whole for right-determining analysis; inquiring a search engine built in advance according to the first data information value, determining a plurality of second data information values which have similarity with the first data information value in the search engine, finding a second data information value which has the maximum similarity with the first data information value, and when the similarity corresponding to the found second data information value exceeds a preset threshold value, indicating that the first data information value has infringement risk, and at the moment, comparing the data value corresponding to each field name in the second data information value with the data value corresponding to each field name in the first data information value to be put on shelf to further obtain a right result corresponding to the first data information value; when the right of the first data information value to be put on shelf is successfully confirmed, the first data information value is stored in the search engine, so that whether the newly put on shelf data commodity has the right of attribution of data or not can be confirmed by comparing existing data commodity, the right confirming efficiency of the data is improved, and the benefit of the right attributing person of the data is guaranteed.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute a limitation on the application. In the drawings:
FIG. 1 is a flow chart of a data right analysis method based on big data provided by an embodiment of the application;
Fig. 2 is a schematic diagram of an internal structure of a data right analysis device based on big data according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be clearly and completely described below with reference to specific embodiments of the present application and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, embodiments of the application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
The embodiment of the application provides a data right-determining analysis method, equipment and medium based on big data, which are used for determining a first data information value corresponding to a first data commodity through a field name in commodity information of the first data commodity to be put on, so that data values corresponding to a plurality of field names in commodity information corresponding to the first data commodity to be put on can be combined into data with a long character string type, and the first data commodity can be taken as a whole for right-determining analysis; inquiring a search engine built in advance according to the first data information value, determining a plurality of second data information values which have similarity with the first data information value in the search engine, finding a second data information value which has the maximum similarity with the first data information value, and when the similarity corresponding to the found second data information value exceeds a preset threshold value, indicating that the first data information value has infringement risk, and at the moment, comparing the data value corresponding to each field name in the second data information value with the data value corresponding to each field name in the first data information value to be put on shelf to further obtain a right result corresponding to the first data information value; and when the right of the first data information value to be put on the shelf is successfully confirmed, storing the first data information value into the search engine. The technical problem of low data authority confirming efficiency caused by the fact that the attribution authority of the data is not clear in the prior art is solved.
The following describes the technical scheme provided by the embodiment of the application in detail through the attached drawings.
Fig. 1 is a flowchart of a data right analysis method based on big data according to an embodiment of the present application. As shown in fig. 1, the data right analysis method based on big data provided by the embodiment of the application mainly includes the following steps:
s101: and acquiring commodity information corresponding to the first data commodity to be put on shelf, and determining a plurality of field names in the commodity information so as to determine a first data information value corresponding to the first data commodity according to the field names.
The server receives a first data commodity to be put on shelf, which is uploaded by a user, acquires commodity information in the first data commodity, and determines a plurality of field names from the commodity information, so that a first data information value corresponding to the first data commodity is determined according to the plurality of field names corresponding to the first data commodity.
It should be noted that in the embodiment of the present application, a plurality of field names and data values corresponding to each field name in the first data commodity are represented by "field names: a data value; in the form of' the first data information value of the long character string type is combined, so that commodity information of the first data commodity is combined into a whole for performing the right-determining analysis, and the method is simpler, more convenient and quicker.
In one embodiment of the application, before acquiring commodity information corresponding to a first data commodity to be put on shelf, a server needs to determine an portrait of a corresponding user according to commodity browsing information and purchasing records of the user corresponding to the first data commodity to be put on shelf, and meanwhile, identity information of the user corresponding to the first data commodity is acquired; and then authenticating qualification information of the corresponding user according to the portrait of the corresponding user, and authenticating identity information of the corresponding user in a preset retrieval mode. Therefore, before the data is subjected to the right-confirming analysis, the user corresponding to the data commodity which needs to be subjected to the right-confirming analysis is authenticated, and after the corresponding user authentication is passed, the data commodity is subjected to the right-confirming analysis, so that an attacker can be effectively prevented from maliciously submitting a data commodity shelf request, the data right-confirming efficiency is improved, and the benefit of a right person to which the data commodity belongs is further protected.
S102: and querying a search engine built in advance according to the first data information value to determine a plurality of second data information values with similarity to the first data information value.
It should be noted that, in the embodiment of the present application, a cluster system with ELASTICSEARCH search engines is built, so that when one ELASTICSEARCH search engine in the cluster system is down, data right determination analysis can be performed through any one ELASTICSEARCH search engine in the cluster system, thereby avoiding the reduction of the data right determination efficiency due to the down of ELASTICSEARCH search engines.
Specifically, the server queries a pre-built search engine according to first data information values of first data commodities, and respectively determines second data information values corresponding to a plurality of second data commodities in the search engine through a preset character string similarity comparison tool, and converts the second data information values into editing operation times required by the first data information values corresponding to the first data commodities; and respectively determining the second data information value corresponding to each data commodity in the plurality of second data commodities in the search engine according to the editing operation times required by the second data information values corresponding to the plurality of second data commodities, and the similarity between the second data information values corresponding to the first data commodities. This allows automated retrieval of whether other data items similar to the first data information value already exist in the search engine.
In one embodiment of the present application, the server further needs to acquire a plurality of second data commodities for performing transactions from the existing transaction system, determine a second data information value corresponding to the second data commodities according to a plurality of field names corresponding to the second data commodities, and store the acquired second data information value corresponding to the plurality of second data commodities in the search engine.
S103: and selecting a second data information value with the maximum similarity with the first data information value from the plurality of second data information values, and acquiring a second data commodity corresponding to the second data information value with the maximum similarity with the first data information value when the similarity corresponding to the second data information value exceeds a preset threshold.
The server selects a second data information value with the maximum similarity to the first data information value from a plurality of second data information values of the search engine, compares the similarity corresponding to the second data information value with a preset threshold value, and if the similarity exceeds the preset threshold value, indicates that the first data information value corresponding to the first data commodity has infringement risk, and at the moment, needs to acquire the second data commodity corresponding to the second data information value with the maximum similarity to the first data information value, so that whether the first data information value is infringed or not can be further determined according to commodity information of the second data commodity, and the data right confirming efficiency is improved.
S104: and determining the right-confirming result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, and if the right-confirming is successful, storing the first data information value into a search engine.
The server compares the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity to determine a right confirming result corresponding to the first data information value, and the server needs to store the first data information value of the first data commodity into a search engine under the condition that the right confirming result is successful in confirming the right, so that basis is provided for subsequent right confirming analysis.
Specifically, the server determines the data identification information corresponding to the first data commodity according to the first data information value corresponding to the first data commodity, so that the first data information value corresponding to the first data commodity is identified through the corresponding data identification information, and then the first data information value corresponding to the identified first data commodity is stored in the search engine.
In one embodiment of the present application, after determining the right result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, the server determines the position information of the user corresponding to the first data commodity according to the obtained commodity information corresponding to the first data commodity, and then feeds back the right result of the first data commodity to the corresponding user according to the position information of the user corresponding to the first data commodity.
In one embodiment of the application, when the server determines that the first data commodity is successfully authenticated by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, the server sends the first data information value corresponding to the first data commodity to a third party authentication center, the third party authentication center authenticates the first data commodity, after the authentication is passed, a corresponding authentication certificate is determined for the first data commodity, and then the corresponding authentication certificate is issued to a user corresponding to the first data commodity, so that the corresponding user authenticates the first data commodity according to the authentication certificate.
In one embodiment of the present application, when determining that the first data commodity fails to be authorized by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, the server sends the first data commodity and the personal information of the user corresponding to the first data commodity to the user corresponding to the second data information value with the maximum similarity to the first data information value, and notifies the user corresponding to the second data information value with the maximum similarity to the first data information value to perform infringement evidence.
The above is a method embodiment of the present application. Based on the same inventive concept, the embodiment of the application also provides a data right analysis device based on big data, and the structure of the data right analysis device is shown in fig. 2.
Fig. 2 is a schematic diagram of an internal structure of a data right analysis device based on big data according to an embodiment of the present application. As shown in fig. 2, the apparatus includes at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to: acquiring commodity information corresponding to a first data commodity to be put on shelf, and determining a plurality of field names in the commodity information so as to determine a first data information value corresponding to the first data commodity according to the field names; inquiring a search engine built in advance according to the first data information value to determine a plurality of second data information values with similarity to the first data information value; each second data information value is a data information value corresponding to one data commodity in the search engine; selecting a second data information value with the maximum similarity with the first data information value from a plurality of second data information values, and acquiring a second data commodity corresponding to the second data information value with the maximum similarity with the first data information value when the similarity corresponding to the second data information value exceeds a preset threshold value; and determining the right-confirming result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, and if the right-confirming is successful, storing the first data information value into a search engine.
The embodiment of the application also provides a nonvolatile computer storage medium, which stores computer executable instructions, wherein the computer executable instructions are configured to: acquiring commodity information corresponding to a first data commodity to be put on shelf, and determining a plurality of field names in the commodity information so as to determine a first data information value corresponding to the first data commodity according to the field names; inquiring a search engine built in advance according to the first data information value to determine a plurality of second data information values with similarity to the first data information value; each second data information value is a data information value corresponding to one data commodity in the search engine; selecting a second data information value with the maximum similarity with the first data information value from a plurality of second data information values, and acquiring a second data commodity corresponding to the second data information value with the maximum similarity with the first data information value when the similarity corresponding to the second data information value exceeds a preset threshold value; and determining the right-confirming result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, and if the right-confirming is successful, storing the first data information value into a search engine.
The embodiments of the present application are described in a progressive manner, and the same and similar parts of the embodiments are all referred to each other, and each embodiment is mainly described in the differences from the other embodiments. In particular, for the apparatus and medium embodiments, the description is relatively simple, as it is substantially similar to the method embodiments, with reference to the section of the method embodiments being relevant.
The devices and media provided in the embodiments of the present application are in one-to-one correspondence with the methods, so that the devices and media also have similar beneficial technical effects as the corresponding methods, and since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media are not repeated here.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (8)
1. A data validation analysis method based on big data, the method comprising:
acquiring commodity information corresponding to a first data commodity to be put on shelf, and determining a plurality of field names in the commodity information so as to determine a first data information value corresponding to the first data commodity according to the field names;
Inquiring a search engine which is built in advance according to the first data information value to determine a plurality of second data information values which have similarity with the first data information value; each second data information value is a data information value corresponding to one data commodity in the search engine;
Selecting a second data information value with the maximum similarity with the first data information value from a plurality of second data information values, and acquiring a second data commodity corresponding to the second data information value with the maximum similarity with the first data information value when the similarity corresponding to the second data information value exceeds a preset threshold value;
Determining a right-confirming result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, and if the right-confirming is successful, storing the first data information value into the search engine;
before the commodity information corresponding to the first data commodity to be put on the shelf is obtained, the method further comprises:
Determining the portrait of a corresponding user according to commodity browsing information and purchasing records of the corresponding user of the first data commodity to be put on shelf, and acquiring identity information of the corresponding user;
authenticating qualification information of the corresponding user according to the portrait of the corresponding user, and authenticating identity information of the corresponding user in a preset retrieval mode;
The searching engine built in advance is inquired according to the first data information value to determine a plurality of second data information values with similarity to the first data information value, and the searching engine specifically comprises:
Inquiring a search engine built in advance according to the first data information value;
Determining second data information values corresponding to a plurality of second data commodities in the search engine respectively through a preset character string similarity comparison tool, and converting the second data information values into editing operation times required by the first data information values corresponding to the first data commodities;
And respectively determining the second data information value corresponding to each data commodity in the plurality of second data commodities in the search engine according to the editing operation times required by the second data information values corresponding to the plurality of second data commodities, and the similarity between the second data information value and the first data information value corresponding to the first data commodity.
2. The method for analyzing data right based on big data according to claim 1, wherein before querying a search engine built in advance according to the first data information value, the method further comprises:
acquiring a plurality of second data commodities for carrying out transactions from an existing transaction system;
determining a second data information value corresponding to a second data commodity according to a plurality of field names corresponding to the second data commodity;
and storing the acquired second data information values corresponding to the plurality of second data commodities into a search engine.
3. The method for analyzing data right based on big data according to claim 1, wherein said storing the first data information value in the search engine specifically comprises:
Determining data identification information corresponding to the first data commodity according to a first data information value corresponding to the first data commodity, so as to identify the first data information value corresponding to the first data commodity through the corresponding data identification information;
and storing the first data information value corresponding to the first data commodity with the identification into the search engine.
4. The method for analyzing data right based on big data according to claim 1, wherein after determining the result of right of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, the method further comprises:
Determining the position information of a user corresponding to the first data commodity based on the acquired commodity information corresponding to the first data commodity;
and feeding back the right confirmation result of the first data commodity to the corresponding user according to the position information of the corresponding user.
5. The big data based data right analysis method according to claim 1, wherein when the data value corresponding to each field name in the second data commodity is compared with the data value corresponding to each field name in the first data commodity, the method further comprises:
Transmitting a first data information value corresponding to the first data commodity to a third party right-determining center;
Verifying the first data commodity through the third party right verification center, and determining a corresponding right verification certificate for the first data commodity after the first data commodity passes the verification;
and issuing the corresponding right-determining certificate to the user corresponding to the first data commodity, so that the corresponding user can prove the first data commodity according to the right-determining certificate.
6. The big data based data right analysis method according to claim 1, wherein when the comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, determining that the first data commodity fails to determine the right, the method further comprises:
The first data commodity and the personal information of the user corresponding to the first data commodity are sent to the user corresponding to the second data information value with the maximum similarity to the first data information value;
And notifying the user corresponding to the second data information value with the maximum similarity to the first data information value to perform infringement evidence.
7. A data right analysis device based on big data, the device comprising:
At least one processor; and
A memory communicatively coupled to the at least one processor; wherein,
The memory stores instructions executable by the at least one processor to enable the at least one processor to:
acquiring commodity information corresponding to a first data commodity to be put on shelf, and determining a plurality of field names in the commodity information so as to determine a first data information value corresponding to the first data commodity according to the field names;
Inquiring a search engine which is built in advance according to the first data information value to determine a plurality of second data information values which have similarity with the first data information value; each second data information value is a data information value corresponding to one data commodity in the search engine;
Selecting a second data information value with the maximum similarity with the first data information value from a plurality of second data information values, and acquiring a second data commodity corresponding to the second data information value with the maximum similarity with the first data information value when the similarity corresponding to the second data information value exceeds a preset threshold value;
Determining a right-confirming result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, and if the right-confirming is successful, storing the first data information value into the search engine;
Before acquiring the commodity information corresponding to the first data commodity to be put on shelf, the method further comprises the following steps:
Determining the portrait of a corresponding user according to commodity browsing information and purchasing records of the corresponding user of the first data commodity to be put on shelf, and acquiring identity information of the corresponding user;
authenticating qualification information of the corresponding user according to the portrait of the corresponding user, and authenticating identity information of the corresponding user in a preset retrieval mode;
The searching engine built in advance is inquired according to the first data information value to determine a plurality of second data information values with similarity to the first data information value, and the searching engine specifically comprises:
Inquiring a search engine built in advance according to the first data information value;
Determining second data information values corresponding to a plurality of second data commodities in the search engine respectively through a preset character string similarity comparison tool, and converting the second data information values into editing operation times required by the first data information values corresponding to the first data commodities;
And respectively determining the second data information value corresponding to each data commodity in the plurality of second data commodities in the search engine according to the editing operation times required by the second data information values corresponding to the plurality of second data commodities, and the similarity between the second data information value and the first data information value corresponding to the first data commodity.
8. A non-transitory computer storage medium storing computer-executable instructions, the computer-executable instructions configured to:
acquiring commodity information corresponding to a first data commodity to be put on shelf, and determining a plurality of field names in the commodity information so as to determine a first data information value corresponding to the first data commodity according to the field names;
Inquiring a search engine which is built in advance according to the first data information value to determine a plurality of second data information values which have similarity with the first data information value; each second data information value is a data information value corresponding to one data commodity in the search engine;
Selecting a second data information value with the maximum similarity with the first data information value from a plurality of second data information values, and acquiring a second data commodity corresponding to the second data information value with the maximum similarity with the first data information value when the similarity corresponding to the second data information value exceeds a preset threshold value;
Determining a right-confirming result of the first data commodity by comparing the data value corresponding to each field name in the second data commodity with the data value corresponding to each field name in the first data commodity, and if the right-confirming is successful, storing the first data information value into the search engine;
Before acquiring the commodity information corresponding to the first data commodity to be put on shelf, the method further comprises the following steps:
Determining the portrait of a corresponding user according to commodity browsing information and purchasing records of the corresponding user of the first data commodity to be put on shelf, and acquiring identity information of the corresponding user;
authenticating qualification information of the corresponding user according to the portrait of the corresponding user, and authenticating identity information of the corresponding user in a preset retrieval mode;
The searching engine built in advance is inquired according to the first data information value to determine a plurality of second data information values with similarity to the first data information value, and the searching engine specifically comprises:
Inquiring a search engine built in advance according to the first data information value;
Determining second data information values corresponding to a plurality of second data commodities in the search engine respectively through a preset character string similarity comparison tool, and converting the second data information values into editing operation times required by the first data information values corresponding to the first data commodities;
And respectively determining the second data information value corresponding to each data commodity in the plurality of second data commodities in the search engine according to the editing operation times required by the second data information values corresponding to the plurality of second data commodities, and the similarity between the second data information value and the first data information value corresponding to the first data commodity.
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