CN110334107B - Qualification review method, device and server based on data analysis - Google Patents
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Abstract
The embodiment of the invention discloses a qualification review method, a device and a server based on data analysis, wherein the method is applied to the field of data analysis and comprises the following steps: receiving an qualification review request uploaded by a user, detecting whether identity data in the qualification review request is matched with reference identity data stored in a preset identity information database, if not, searching target review data corresponding to the identity data in the preset review information database, calculating the similarity between the reference review data and the target review data in the qualification review request, and if the calculated similarity is greater than the preset similarity, performing qualification review on the user by a server according to the reference review data to obtain a qualification review result. By implementing the method, when the qualification review request is received, if the identity data of the user is stored in the preset database, the review result can be directly obtained, and the review efficiency is improved.
Description
Technical Field
The present invention relates to the field of data analysis technologies, and in particular, to a method, an apparatus, and a server for qualification review based on data analysis.
Background
At present, when the qualification is performed, after the applicant submits a qualification request, the review mechanism performs the review on the review data submitted by the applicant, and the qualification is performed on small-scale personnel, so that the review mode is effective.
However, if the request of the applicant is received for the social universality qualification review, the corresponding personnel are reassigned to detect whether the request meets the review requirement, so that the review period is long, and the time and the labor are consumed.
Disclosure of Invention
The embodiment of the invention provides a qualification review method, a device and a server based on data analysis, which can be used for pre-reviewing a user and directly outputting a review result when a review request is received, so that the review efficiency is improved.
In a first aspect, an embodiment of the present invention provides a method for qualification review based on data analysis, the method including:
receiving an qualification review request uploaded by a user, wherein the qualification review request carries identity data and reference review data of the user;
detecting whether the identity data is matched with reference identity data stored in a preset identity information database, wherein the preset identity information database comprises a first preset identity information database and a second preset identity information database, the first preset identity information database stores the identity data of qualified personnel, and the second preset identity information database stores the identity data of unqualified personnel;
If the identity data is not matched with the reference identity data stored in the preset identity information database, searching target review data corresponding to the identity data in a preset review information database;
calculating the similarity between the reference review data and the target review data;
and if the similarity is greater than the preset similarity, performing qualification review on the user according to the reference review data to obtain a qualification review result.
In a second aspect, an embodiment of the present invention provides a qualification apparatus based on data analysis, the apparatus including:
the receiving module is used for receiving a qualification review request uploaded by a user, wherein the qualification review request carries the identity data and the reference review data of the user;
the detection module is used for detecting whether the identity data is matched with the reference identity data stored in the preset identity information database, the preset identity information database comprises a first preset identity information database and a second preset identity information database, the first preset identity information database stores the identity data of qualified personnel, and the second preset identity information database stores the identity data of unqualified personnel;
The searching module is used for searching target review data corresponding to the identity data in a preset review information database if the identity data is not matched with the reference identity data stored in the preset identity information database;
the calculating module is used for calculating the similarity between the reference review data and the target review data;
and the evaluation module is used for performing qualification evaluation on the user according to the reference evaluation data if the similarity is greater than the preset similarity so as to obtain a qualification evaluation result.
In a third aspect, an embodiment of the present invention provides a server, including a processor, an input device, an output device, and a memory, where the processor, the input device, the output device, and the memory are connected to each other, and the memory is configured to store a computer program, where the computer program includes program instructions, and where the processor is configured to invoke the program instructions to perform the method according to the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method according to the first aspect.
In the embodiment of the invention, a server receives an qualification request uploaded by a user, detects whether identity data in the qualification request is matched with reference identity data stored in a preset identity information database, if not, the server searches target evaluation data corresponding to the identity data in the preset identity information database, calculates similarity between the reference evaluation data and the target evaluation data in the qualification request, and if the calculated similarity is greater than the preset similarity, the server performs qualification on the user according to the reference evaluation data to obtain a qualification result. By implementing the method, before the qualification review request is received, the information of the personnel which can pass through the review or the personnel which cannot pass through the review is stored in the preset database by a big data means, and the review result is directly obtained when the qualification review request is received, so that the review efficiency can be improved. And by calculating the similarity between the reference review data and the target review data, the authenticity of the review data uploaded by the user can be verified, and omission in the target review data is avoided. And the accuracy of the evaluation is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow diagram of a data analysis based qualification method in an embodiment of the invention;
FIG. 2 is a flow diagram of another data analysis based qualification method in an embodiment of the invention;
FIG. 3 is a schematic diagram of a data analysis based qualification apparatus according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a server according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
FIG. 1 is a flow chart of a method for data analysis-based qualification review in an embodiment of the invention. As shown in fig. 1, the flow of the qualification method based on data analysis in the present embodiment may include:
s101, a server receives a qualification review request uploaded by a user, wherein the qualification review request carries identity data and reference review data of the user.
In the embodiment of the invention, the user can upload the qualification review request on the appointed page provided by the user terminal, wherein the qualification review request can be of a long-protection risk handling qualification review request, a loan handling qualification review request and the like, and the qualification review request carries the identity data and the reference review data of the user. The identity data includes identity document image and identity feature data, the identity feature data is used for verifying the authenticity of the identity of the user, such as fingerprint data, iris data, face data and the like of the user, the reference review data is data which is uploaded by the user and is used for taking the qualification of the user as a review reference, and for different types of qualification requests, the corresponding reference review data can be different, for example, the qualification request is a long-protection-risk-handling qualification-review request, the reference review data which the user needs to upload is medical data, including the historical diagnosis and treatment place, diagnosis time, affected condition and the like of the user, the reference review data which the user uploads is bank card flow data, including month expense, credit condition and the like, and it is required to be explained that the reference review data corresponding to the different types of qualification requests can be preset by a research staff, and the embodiment of the invention is not limited.
It should be noted that, the specific way of uploading the identity data and the reference review data by the user may be that the user terminal adopts an optical character recognition (Optical Character Recognition, OCR) technology to recognize the paper reference review data provided by the user and convert the paper reference review data into a document recognizable by the server, so as to obtain the identity data and the reference review data. The user terminal sends the identity data and the reference review data of the user to the server, and the server receives the identity data and the reference review data.
S102, the server detects whether the identity data is matched with the reference identity data stored in the preset identity information database.
In the embodiment of the invention, after the server acquires the identity data and the reference review data uploaded by the user, whether the detected identity data is matched with the reference identity data stored in the preset identity information database or not is detected, wherein the preset identity information database comprises a first preset identity information database and a second preset identity information database, the first preset identity information database stores the identity data of qualified personnel, and the second preset identity information database stores the identity data of unqualified personnel. It should be noted that, for different types of qualification review requests, different preset identity information databases may be corresponding, and the identity data stored in the different preset identity information databases are different, specifically, after receiving a qualification review request uploaded by a user, the server will search whether the identity data exists in the preset identity information database corresponding to the type of qualification review request.
In the specific implementation, if the server finds the identity data of the user in the first preset identity information database, that is, the identity data in the qualification review request is matched with the reference identity data stored in the first preset identity information database, the server determines that the qualification review result for the user passes; if the server finds the identity data of the user in the second preset identity information database, namely the identity data in the qualification review request is matched with the reference identity data stored in the second preset data, determining that the qualification review result for the user is failed in review.
Further, the first preset identity information database and the second preset identity information database are further preset with priorities, the specific mode that the server detects whether the identity data in the qualification review request is matched with the reference identity data stored in the preset identity information database or not may be that the server obtains the priorities of the first preset identity information database and the second preset identity information database, if the priorities of the first preset identity information database are higher than the priorities of the second preset identity information database, the server preferentially detects whether the identity data of the user is matched with the reference identity data stored in the first preset identity information database, if the priorities are matched, the server directly returns a result of passing review to the user terminal, if the priorities are not matched, the server detects whether the identity data of the user is matched with the reference identity data stored in the second preset identity information database, if the priorities are not matched, the server directly returns a result of failing review to the user terminal, and if the priorities are not matched, the server determines that the identity data uploaded by the user are not matched with the reference identity data stored in the preset identity information database.
It may be understood that if the priority of the second preset identity information database is higher than the priority of the first preset identity information database, the server preferentially detects whether the identity data of the user is matched with the reference identity data stored in the second preset identity information database, if so, the server directly returns a result of failed evaluation to the user terminal, if not, the server detects whether the identity data of the user is matched with the reference identity data stored in the first preset identity information database, and if so, the server directly returns a result of passed evaluation to the user terminal, wherein the priorities of the first preset identity information database and the second preset identity information database can be preset by a developer. If the identity data is not matched with the reference identity data stored in the preset identity information database, the server determines that the identity data uploaded by the user is not matched with the reference identity data stored in the preset identity information database. And performs step S103.
It should be noted that, the server may establish the first preset identity information database and the second preset identity information database according to daily behavior data received by history for different users, for example, the specific establishment mode of the first preset identity information database may be that, when a patient visits, the server receives diagnosis information for the patient uploaded by a doctor, where the diagnosis information includes a disease and an age of the patient, the server detects that the age of the patient is greater than a preset age, and after determining that a target disabling level corresponding to the disease is greater than a preset disabling level according to a corresponding relation between the disease and the disabling level, the server stores the identity data of the patient in the first preset identity information database, or the doctor may also directly note that the patient has a qualification of handling long-service when uploading diagnosis information of the patient, and then the server may also store the identity data of the patient in the first preset identity information database. Furthermore, the server may also receive, in real time, the identity data (such as the illicit person) of the person who does not have the long-length risk handling capability, and store the identity data of the person who does not have the long-length risk handling capability in the second preset identity information database. When the preset identity information database stores the identity data, preset storage time length for each identity data can be obtained in advance, and when the fact that the storage time length of the identity data in the preset identity information database is longer than the preset storage time length is detected, the server moves the identity data out of the preset identity information database, wherein the preset storage time length can be preset by a person uploading the identity data.
S103, if the identity data is not matched with the reference identity data stored in the preset identity information database, the server searches target review data corresponding to the identity data in the preset review information database.
In the embodiment of the invention, if the identity data in the qualification review request is not matched with the reference identity data stored in the preset identity information database, the server searches the target review data corresponding to the identity data in the preset review information database. The preset review information database stores pre-recorded data for review of different personnel, the pre-recorded data for review can be obtained in a big data mode, for example, if the type of the qualification request is that of a long-protection risk handling qualification request, the preset review information database can be a medical insurance information database which stores historical diagnosis records of the different personnel, the diagnosis records comprise diagnosis time, diagnosis place, affected diseases and the like, and the server takes the diagnosis records of the user recorded in the medical insurance information database as target review data of the user. Or, the qualification request may be a loan qualification request, and the preset review information database may be a collection of transaction information databases of each bank, where the collection stores bank card running water information, credit records, and the like of different people, and the server uses the information of the bank card running water information, the credit records, and the like, recorded in the transaction information database, for the user as target review data of the user.
S104, the server calculates the similarity between the reference review data and the target review data.
In the embodiment of the invention, after target review data corresponding to identity data uploaded by a user is searched in a preset review information database, the server calculates the similarity between reference review data and the target review data, wherein the reference review data comprises at least one review item, and the target review data comprises at least one review item. The specific calculation mode of the similarity can be that the server acquires the same number of the review items in the reference review data and the target review data; and calculating a ratio between the number of identical review items and the number of review items in the reference review data; the server determines the calculated ratio as a similarity between the reference review data and the target review data.
For example, if the type of the qualification request is a long-guard-risk-handling qualification request, the review items included in the reference review data uploaded by the user are diabetes, hypertension, heart disease, and hepatitis b, the review items included in the target review data are diabetes and hypertension, and the server determines that the number of the same review items in the reference review data and the target review data is 2, the ratio between the number of the same review items and the number of the review items in the reference review data is 50%, that is, the similarity is 50%.
Further, after the server calculates the similarity between the reference review data and the target review data, if the calculated similarity is greater than the preset similarity, the server executes step S105.
Optionally, the similarity between the reference review data and the target review data calculated by the server is smaller than the preset similarity, the server may send prompt information to the user terminal, where the prompt information includes a description that a qualification review request is suspected to have a defect, and 3 operation options, which are a first operation option, a second operation option and a third operation option, respectively, where the first operation option may be a review continuing option and using the reference review data to perform the review operation option, the second operation option may be a review continuing option and using the target review data to perform the review operation option, the third operation option is to re-upload the reference review data option, the server receives a selection operation of the user terminal for the operation option, and if the server receives the selection operation of the first operation option, the server performs authenticity verification on the reference review data uploaded by the user, where a manner of authenticity verification includes checking whether the reference review data image includes a preset identifier, such as a preset identifier in a hospital charging ticket, or manually checking the reference review data. If the server receives the selection operation aiming at the second operation option, the server directly adopts the target review data to review the qualification of the user. If the server receives the selection operation aiming at the third operation option, the server re-receives the review data uploaded by the user terminal as reference review data, and the similarity between the reference review data and the target review data is calculated again. If the similarity is larger than the preset similarity, the server adopts the received reference review data to carry out qualification review on the user, and if the similarity is smaller than the preset similarity, the server sends the prompt information to the user terminal. By calculating the similarity between the reference review data and the target review data, the authenticity of the review data uploaded by the user can be verified, and omission in the target review data is avoided. And the accuracy of the evaluation is improved.
S105, if the similarity is larger than the preset similarity, the server conducts qualification review on the user according to the reference review data to obtain a qualification review result.
In the embodiment of the invention, after the server calculates the similarity between the reference evaluation data and the target evaluation data, if the calculated similarity is greater than the preset similarity, the server performs qualification evaluation on the user according to the reference evaluation data and obtains a qualification evaluation result, wherein the qualification evaluation result comprises that the evaluation passes or fails, and further, after the server obtains the evaluation result, the evaluation result is sent to the user terminal, so that the user can review the evaluation result on the user terminal.
In the embodiment of the invention, a server receives an qualification request uploaded by a user, detects whether identity data in the qualification request is matched with reference identity data stored in a preset identity information database, if not, the server searches target evaluation data corresponding to the identity data in the preset identity information database, calculates similarity between the reference evaluation data and the target evaluation data in the qualification request, and if the calculated similarity is greater than the preset similarity, the server performs qualification on the user according to the reference evaluation data to obtain a qualification result. By implementing the method, before the qualification review request is received, the information of the personnel which can pass through the review or the personnel which cannot pass through the review is stored in the preset database by a big data means, and the review result is directly obtained when the qualification review request is received, so that the review efficiency can be improved. And by calculating the similarity between the reference review data and the target review data, the authenticity of the review data uploaded by the user can be verified, omission in the target review data is avoided, and the accuracy of review is improved.
FIG. 2 is a flow chart of another method for data analysis-based qualification review in accordance with an embodiment of the present invention. As shown in fig. 2, the flow of the qualification method based on data analysis in the present embodiment may include:
s201, the server receives a qualification review request uploaded by the user, wherein the qualification review request carries identity data and reference review data of the user.
In the embodiment of the invention, the user can upload the qualification review request on the appointed page on the user terminal, wherein the qualification review request carries the identity data and the reference review data of the user. The identity data comprises identity document images and identity characteristic data, the identity characteristic data is true of the identity of the user, such as fingerprint data, iris data, face data and the like of the user, the reference review data is data which is uploaded by the user and is used for taking qualification of the user as review reference, and corresponding reference review data can be different for different types of qualification review requests.
S202, the server detects whether the identity data is matched with preset identity data.
In the embodiment of the invention, after the server acquires the identity data uploaded by the user terminal, the authenticity of the identity data is detected, specifically, whether the identity data is matched with preset identity data or not is detected, if the identity data is matched with the preset identity data, the server determines that the identity data uploaded by the user is the true identity data, if the identity data is not matched with the preset identity data, the server determines that the identity data uploaded by the user is suspected to be abnormal, and the identity data is submitted to manual review, or prompt information is sent to the user to prompt the user to upload the identity data again, and the identity data uploaded again by the user is received.
In a specific implementation, the identity data comprises an identity document image and identity feature data, the identity feature data comprises face data, fingerprint data, iris data and the like, and the server detects whether the identity data uploaded by the user is matched with preset identity data or not in a mode that the server acquires preset identity feature data corresponding to the identity document image and a verification sequence corresponding to the preset identity feature data. The preset identity characteristic data corresponding to the identity document image can be preset by a user when the user handles the identity document, and if the identity document is an identity card, the user can input face data, fingerprint data and iris data when handling the identity card, and the face data, the fingerprint data and the iris data are used as preset face data, preset iris data. Further, the server detects whether the identity feature data is matched with the preset identity feature data.
In one implementation, the preset identity feature data is one of face data, fingerprint data or iris data, for example, the preset face data, the server calculates similarity between the face data uploaded by the user and the preset face data, and if the similarity is greater than a preset threshold, the server determines that the identity data uploaded by the user is matched with the preset identity data.
In one implementation, the preset identity feature data is at least two of face data, fingerprint data and iris data, such as preset face data and preset fingerprint data, and the corresponding verification sequence is that the preset face data is in front and the preset fingerprint data is in back, the server calculates the similarity between the face data uploaded by the user and the preset face data, calculates the similarity between the fingerprint data uploaded by the user and the preset fingerprint data, and if the similarity between the face data uploaded by the user and the preset fingerprint data is greater than a preset threshold, the server further detects whether the uploading sequence of the identity feature data is matched with the verification sequence corresponding to the preset identity feature data, wherein the verification sequence corresponding to the preset identity feature data is preset by the user when the identity document is transacted. If the uploading sequence of the identity feature data is not matched with the verification sequence corresponding to the preset identity feature data, the server may send a prompt message to the user terminal to prompt the user terminal to upload the qualification review request again.
S203, the server detects whether the identity data is matched with the reference identity data stored in the preset identity information database.
In the embodiment of the invention, the preset identity information database comprises a first preset identity information database and a second preset identity information database, wherein the first preset identity information database stores the identity data of qualified personnel, and the second preset identity information database stores the identity data of unqualified personnel.
In one implementation manner, the specific establishment manner of the first preset identity information database may be that the server obtains daily behavior data for each user in at least one user, where the daily behavior data includes at least one of financial data, credit data, and medical data; when the server detects that the target daily behavior data corresponding to the target user meets the preset qualification review rule, acquiring the identity data of the target user; and storing the identity data of the target user into a first preset identity information database. For example, if the qualification request is a loan qualification request, the server may obtain financial data and credit data of different users, such as bank flows, credit card credit loss records, and the like, and determine for each user whether it is eligible for loan, and if so, the server stores the identity data of the user in a first preset identity information database.
In one implementation manner, the specific establishment manner of the second preset identity information database may be that the server acquires abnormal behavior information uploaded by the appointed person, and extracts identity data in the abnormal behavior information; the server stores the identity data in the abnormal behavior information into a second preset identity information database, and determines a preset storage duration corresponding to the identity data in the abnormal behavior information according to the abnormal behavior information; and when the fact that the storage time of the identity data in the abnormal behavior information in the second preset identity information database is longer than the preset storage time is detected, the identity data in the abnormal behavior information is moved out of the second preset identity information database. For example, the appointed person is police, the abnormal behavior information is illegal information, the server extracts identity data in the illegal information and stores the identity data in a second preset identity information database, and further, the server acquires illegal contents in the illegal information and determines the storage time length aiming at the identity data in the illegal information according to the corresponding relation between the illegal contents and the storage time length. The correspondence between the illegal content and the storage duration can be preset by a developer, and the embodiment of the invention is not limited.
After the first preset identity information database and the second preset identity information database are established, if the server finds the identity data of the user in the first preset identity information database, namely the identity data in the qualification review request is matched with the reference identity data stored in the first preset identity information database, the server determines that the qualification review result of the user passes; if the server finds the identity data of the user in the second preset identity information database, namely the identity data in the qualification review request is matched with the reference identity data stored in the second preset data, determining that the qualification review result for the user is failed in review. If the identity data in the qualification request is not matched with the reference identity data stored in the first preset identity information database and the second preset identity information database, determining that the identity data in the qualification request is not matched with the reference identity data stored in the preset identity information database, and executing step S204.
S204, if the identity data is not matched with the reference identity data stored in the preset identity information database, the server searches target review data corresponding to the identity data in the preset review information database.
S205, the server calculates the similarity between the reference review data and the target review data.
In the embodiment of the invention, after target review data corresponding to identity data uploaded by a user is searched in a preset review information database, the server calculates the similarity between reference review data and the target review data, wherein the reference review data comprises at least one review item, and the target review data comprises at least one review item. The specific calculation mode of the similarity can be that the server acquires the same number of the review items in the reference review data and the target review data; and calculating a ratio between the number of identical review items and the number of review items in the reference review data; the server determines the calculated ratio as a similarity between the reference review data and the target review data. If the similarity calculated by the server is smaller than or equal to the preset similarity, the server determines that the qualification review request has defects; and sending defect information corresponding to the qualification review request to the user. If the similarity calculated by the server is greater than the preset similarity, step S206 is performed.
S206, if the similarity is larger than the preset similarity, the server conducts qualification review on the user according to the reference review data to obtain a qualification review result.
In the embodiment of the invention, after the server calculates the similarity between the reference evaluation data and the target evaluation data, if the calculated similarity is greater than the preset similarity, the server performs qualification evaluation on the user according to the reference evaluation data and obtains a qualification evaluation result, wherein the qualification evaluation result comprises that the evaluation passes or fails, and further, after the server obtains the evaluation result, the evaluation result is sent to the user terminal, so that the user can review the evaluation result on the user terminal.
In the embodiment of the invention, a server receives an qualification request uploaded by a user, detects the authenticity of identity data in the qualification request, after determining that the identity data is the authentic identity data, the server detects whether the identity data in the qualification request is matched with reference identity data stored in a preset identity information database, if not, the server searches target evaluation data corresponding to the identity data in the preset evaluation information database, calculates the similarity between the reference evaluation data and the target evaluation data in the qualification request, and if the calculated similarity is greater than the preset similarity, the server performs qualification evaluation on the user according to the reference evaluation data to obtain a qualification result. By implementing the method, the identity data uploaded by the user can be ensured to be real identity data through the identity feature data and the verification sequence, and the information of the personnel who can pass or cannot pass the review is stored into the preset database through a big data means before the qualification review request is received, and the review result is directly obtained when the qualification review request is received, so that the review efficiency can be improved. And by calculating the similarity between the reference review data and the target review data, the authenticity of the review data uploaded by the user can be verified, omission in the target review data is avoided, and the accuracy of review is improved.
The qualification device based on data analysis according to the embodiment of the present invention will be described in detail with reference to fig. 3. It should be noted that, the qualification device based on data analysis shown in fig. 3 is used to perform the method of the embodiment shown in fig. 1-2 of the present invention, for convenience of explanation, only the portion relevant to the embodiment of the present invention is shown, and specific technical details are not disclosed, and reference is made to the embodiment shown in fig. 1-2 of the present invention.
Referring to fig. 3, a schematic structural diagram of a data analysis-based qualification device according to the present invention is provided, and the data analysis-based qualification device 30 may include: a receiving module 301, a detecting module 302, a searching module 303, a calculating module 304, a review module 305 and a storage module 306.
The receiving module 301 is configured to receive a qualification review request uploaded by a user, where the qualification review request carries identity data and reference review data of the user;
a detection module 302, configured to detect whether the identity data matches with reference identity data stored in a preset identity information database, where the preset identity information database includes a first preset identity information database and a second preset identity information database, the first preset identity information database stores identity data of qualified personnel, and the second preset identity information database stores identity data of unqualified personnel;
The searching module 303 is configured to search, if the identity data is not matched with the reference identity data stored in the preset identity information database, target review data corresponding to the identity data in a preset review information database;
a calculation module 304, configured to calculate a similarity between the reference review data and the target review data;
and the review module 305 is configured to, if the similarity is greater than a preset similarity, perform a qualification review on the user according to the reference review data, so as to obtain a qualification review result.
In one implementation, the identity data includes an identity document image and identity feature data, the identity feature data includes at least two of face data, fingerprint data, and iris data, and the detection module 302 is further configured to:
acquiring preset identity characteristic data corresponding to the identity document image and a verification sequence corresponding to the preset identity characteristic data, wherein the preset identity characteristic data comprises at least two of preset face data, preset fingerprint data and preset iris data;
detecting whether the identity characteristic data is matched with the preset identity characteristic data or not;
If yes, detecting whether the uploading sequence of the identity characteristic data is matched with the checking sequence;
if yes, triggering an operation of detecting whether the identity data is matched with the reference identity data stored in the preset identity information database.
In one implementation, the reference review data includes at least one review item, the target review data includes at least one review item, and the computing module 304 is specifically configured to:
acquiring the same number of review items in the reference review data and the target review data;
calculating a ratio between the number of identical review items and the number of review items in the reference review data;
the ratio is determined as a similarity between the reference review data and the target review data.
In one implementation, the review module 305 is specifically configured to:
if the identity data is matched with the reference identity data stored in the first preset identity information database, determining that the qualification review result aiming at the user passes the review;
and if the identity data is matched with the reference identity data stored in the second preset identity information database, determining that the qualification review result aiming at the user is failed in review.
In one implementation, the review module 305 is further configured to:
if the similarity is smaller than or equal to the preset similarity, determining that the qualification review request has defects;
and sending defect information corresponding to the qualification review request to the user.
In one implementation, the storage module 306 is specifically configured to:
acquiring daily behavioral data for each of at least one user, the daily behavioral data including at least one of financial data, credit data, medical data;
when detecting that the target daily behavior data corresponding to the target user meets the preset qualification review rule, acquiring the identity data of the target user;
and storing the identity data of the target user into the first preset identity information database.
In one implementation, the storage module 306 is specifically configured to:
acquiring abnormal behavior information uploaded by appointed personnel, and extracting identity data in the abnormal behavior information;
storing the identity data in the abnormal behavior information into the second preset identity information database, and determining a preset storage time length corresponding to the identity data in the abnormal behavior information according to the abnormal behavior information;
And when the fact that the storage time of the identity data in the abnormal behavior information in the second preset identity information database is longer than the preset storage time is detected, the identity data in the abnormal behavior information is moved out of the second preset identity information database.
In the embodiment of the present invention, the receiving module 301 receives the qualification request uploaded by the user, the detecting module 302 detects whether the identity data in the qualification request is matched with the reference identity data stored in the preset identity information database, if not, the searching module 303 searches the preset identity information database for the target review data corresponding to the identity data, the calculating module 304 calculates the similarity between the reference review data and the target review data in the qualification request, and if the calculated similarity is greater than the preset similarity, the evaluating module 305 performs qualification on the user according to the reference review data to obtain the qualification result. By implementing the method, before the qualification review request is received, the information of the personnel which can pass through the review or the personnel which cannot pass through the review is stored in the preset database by a big data means, and the review result is directly obtained when the qualification review request is received, so that the review efficiency can be improved.
Referring to fig. 4, a schematic structural diagram of a server is provided in an embodiment of the present invention. As shown in fig. 4, the server includes: at least one processor 401, an input device 403, an output device 404, a memory 405, and at least one communication bus 402. Wherein communication bus 402 is used to enable connected communications between these components. The input device 403 may be a control panel, a microphone, or the like, and the output device 404 may be a display screen or the like. The memory 405 may be a high-speed RAM memory or a non-volatile memory (non-volatile memory), such as at least one disk memory. The memory 405 may also optionally be at least one storage device located remotely from the aforementioned processor 401. Wherein the processor 401 may be described in connection with fig. 3, a set of program codes is stored in the memory 405, and the processor 401, the input device 403, the output device 404 call the program codes stored in the memory 405 for performing the following operations:
an input device 403, configured to receive a qualification request uploaded by a user, where the qualification request carries identity data and reference review data of the user;
a processor 401, configured to detect whether the identity data matches with reference identity data stored in a preset identity information database, where the preset identity information database includes a first preset identity information database in which identity data of qualified personnel is stored and a second preset identity information database in which identity data of unqualified personnel is stored;
The processor 401 is configured to search, if the identity data is not matched with the reference identity data stored in the preset identity information database, target review data corresponding to the identity data in a preset review information database;
a processor 401 for calculating a similarity between the reference review data and the target review data;
and the processor 401 is configured to perform a qualification review on the user according to the reference review data if the similarity is greater than a preset similarity, so as to obtain a qualification review result.
In one implementation, the identity data includes an identity document image and identity feature data, where the identity feature data includes at least two of face data, fingerprint data, and iris data, and the processor 401 is specifically configured to:
acquiring preset identity characteristic data corresponding to the identity document image and a verification sequence corresponding to the preset identity characteristic data, wherein the preset identity characteristic data comprises at least two of preset face data, preset fingerprint data and preset iris data;
detecting whether the identity characteristic data is matched with the preset identity characteristic data or not;
if yes, detecting whether the uploading sequence of the identity characteristic data is matched with the checking sequence;
If yes, triggering an operation of detecting whether the identity data is matched with the reference identity data stored in the preset identity information database.
In one implementation, the reference review data includes at least one review item, and the target review data includes at least one review item, and the processor 401 is specifically configured to:
acquiring the same number of review items in the reference review data and the target review data;
calculating a ratio between the number of identical review items and the number of review items in the reference review data;
the ratio is determined as a similarity between the reference review data and the target review data.
In one implementation, the processor 401 is specifically configured to:
if the identity data is matched with the reference identity data stored in the first preset identity information database, determining that the qualification review result aiming at the user passes the review;
and if the identity data is matched with the reference identity data stored in the second preset identity information database, determining that the qualification review result aiming at the user is failed in review.
In one implementation, the processor 401 is configured to determine that the qualification request has a defect if the similarity is less than or equal to a preset similarity;
And the output device 404 is used for sending the defect information corresponding to the qualification request to the user.
In one implementation, an input device 403 is used to obtain daily behavioral data for each of the at least one user, including at least one of financial data, credit data, medical data;
the processor 401 is specifically configured to:
when detecting that the target daily behavior data corresponding to the target user meets the preset qualification review rule, acquiring the identity data of the target user;
and storing the identity data of the target user into the first preset identity information database.
In one implementation, the input device 403 is configured to obtain abnormal behavior information uploaded by a specified person, and extract identity data in the abnormal behavior information;
the processor 401 is specifically configured to:
storing the identity data in the abnormal behavior information into the second preset identity information database, and determining a preset storage time length corresponding to the identity data in the abnormal behavior information according to the abnormal behavior information;
and when the fact that the storage time of the identity data in the abnormal behavior information in the second preset identity information database is longer than the preset storage time is detected, the identity data in the abnormal behavior information is moved out of the second preset identity information database.
In the embodiment of the present invention, the input device 403 receives the qualification request uploaded by the user, the processor 401 detects whether the identity data in the qualification request is matched with the reference identity data stored in the preset identity information database, if not, the processor 401 searches the preset identity information database for the target review data corresponding to the identity data, the processor 401 calculates the similarity between the reference review data and the target review data in the qualification request, and if the calculated similarity is greater than the preset similarity, the processor 401 performs qualification on the user according to the reference review data to obtain the qualification result. By implementing the method, before the qualification review request is received, the information of the personnel which can pass through the review or the personnel which cannot pass through the review is stored in the preset database by a big data means, and the review result is directly obtained when the qualification review request is received, so that the review efficiency can be improved.
The modules described in the embodiments of the present invention may be implemented by general-purpose integrated circuits such as a CPU (Central Processing Unit ) or by ASIC (Application Specific Integrated Circuit, application specific integrated circuit).
It should be appreciated that in embodiments of the present invention, the processor 401 may be a central processing module (Central Processing Unit, CPU), which may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSPs), application specific integrated circuits (Application Specific Integrated Circuit, ASICs), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGAs) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Those skilled in the art will appreciate that implementing all or part of the above-described methods in the embodiments may be accomplished by computer programs to instruct related hardware, where the programs may be stored in a computer readable storage medium, and where the programs may include the processes of the embodiments of the methods described above when executed. The computer readable storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), or the like.
The foregoing disclosure is illustrative of the present invention and is not to be construed as limiting the scope of the invention, which is defined by the appended claims.
Claims (8)
1. A method of data analysis-based qualification review, the method comprising:
receiving diagnosis information, which is uploaded by a doctor and is specific to a patient, wherein the diagnosis information comprises symptoms and ages of the patient; when the age of the patient is detected to be greater than a preset age and the target disabling level corresponding to the disease is determined to be greater than the preset disabling level according to the corresponding relation between the disease and the disabling level, the identity data of the patient is stored in a first preset identity information database;
receiving an qualification review request uploaded by a user, wherein the qualification review request carries identity data and reference review data of the user; wherein the qualification request is a long-risk-guard-transacting qualification request, the reference review data comprises medical data, and the medical data comprises historical diagnosis and treatment places, diagnosis and treatment time and symptoms of the user; the identity data comprises an identity document image and identity characteristic data, and the identity characteristic data comprises at least two of face data, fingerprint data and iris data;
Acquiring preset identity characteristic data corresponding to the identity document image and a verification sequence corresponding to the preset identity characteristic data, wherein the preset identity characteristic data comprises at least two of preset face data, preset fingerprint data and preset iris data;
detecting whether the identity characteristic data is matched with the preset identity characteristic data, if so, detecting whether the uploading sequence of the identity characteristic data is matched with the checking sequence;
if so, detecting whether the identity data is matched with the reference identity data stored in a preset identity information database, wherein the preset identity information database comprises a first preset identity information database and a second preset identity information database, the first preset identity information database stores the identity data of qualified personnel, and the second preset identity information database stores the identity data of unqualified personnel;
if the identity data is not matched with the reference identity data stored in the preset identity information database, searching target review data corresponding to the identity data in a preset review information database; the target review data comprises diagnosis and treatment records of the user;
Calculating the similarity between the reference review data and the target review data;
if the similarity is greater than the preset similarity, performing qualification review on the user according to the reference review data to obtain a qualification review result;
the calculating the similarity between the reference review data and the target review data includes:
acquiring the same number of review items in the reference review data and the target review data;
calculating a ratio between the number of identical review items and the number of review items in the reference review data, and determining the ratio as a similarity between the reference review data and the target review data; wherein, the review item is a condition item.
2. The method of claim 1, wherein after said detecting whether said identity data matches reference identity data stored in a preset identity information database, the method further comprises:
if the identity data is matched with the reference identity data stored in the first preset identity information database, determining that the qualification review result aiming at the user passes the review;
And if the identity data is matched with the reference identity data stored in the second preset identity information database, determining that the qualification review result aiming at the user is failed in review.
3. The method of claim 1, wherein after the calculating the similarity between the reference review data and the target review data, the method further comprises:
if the similarity is smaller than or equal to the preset similarity, determining that the qualification review request has defects;
and sending defect information corresponding to the qualification review request to the user.
4. A method according to any one of claims 1-3, characterized in that the method further comprises:
acquiring daily behavioral data for each of at least one user, the daily behavioral data including at least one of financial data, credit data, medical data;
when detecting that the target daily behavior data corresponding to the target user meets the preset qualification review rule, acquiring the identity data of the target user;
and storing the identity data of the target user into the first preset identity information database.
5. The method according to claim 4, wherein the method further comprises:
Acquiring abnormal behavior information uploaded by appointed personnel, and extracting identity data in the abnormal behavior information;
storing the identity data in the abnormal behavior information into the second preset identity information database, and determining a preset storage time length corresponding to the identity data in the abnormal behavior information according to the abnormal behavior information;
and when the fact that the storage time of the identity data in the abnormal behavior information in the second preset identity information database is longer than the preset storage time is detected, the identity data in the abnormal behavior information is moved out of the second preset identity information database.
6. A data analysis-based qualification apparatus, the apparatus comprising:
the receiving module is used for receiving diagnosis information, which is uploaded by a doctor and is specific to a patient, wherein the diagnosis information comprises symptoms and ages of the patient;
the detection module is used for storing the identity data of the patient into a first preset identity information database under the condition that the age of the patient is detected to be larger than a preset age and the target disabling level corresponding to the disease is determined to be larger than the preset disabling level according to the corresponding relation between the disease and the disabling level;
The receiving module is also used for receiving a qualification review request uploaded by a user, wherein the qualification review request carries the identity data and the reference review data of the user; wherein the qualification request is a long-risk-guard-transacting qualification request, the reference review data comprises medical data, and the medical data comprises historical diagnosis and treatment places, diagnosis and treatment time and symptoms of the user; the identity data comprises an identity document image and identity characteristic data, and the identity characteristic data comprises at least two of face data, fingerprint data and iris data;
the detection module is also used for acquiring preset identity characteristic data corresponding to the identity document image and a verification sequence corresponding to the preset identity characteristic data, wherein the preset identity characteristic data comprises at least two of preset face data, preset fingerprint data and preset iris data; detecting whether the identity characteristic data is matched with the preset identity characteristic data, if so, detecting whether the uploading sequence of the identity characteristic data is matched with the checking sequence; if so, detecting whether the identity data is matched with the reference identity data stored in a preset identity information database, wherein the preset identity information database comprises a first preset identity information database and a second preset identity information database, the first preset identity information database stores the identity data of qualified personnel, and the second preset identity information database stores the identity data of unqualified personnel;
The searching module is used for searching target review data corresponding to the identity data in a preset review information database if the identity data is not matched with the reference identity data stored in the preset identity information database; the target review data comprises diagnosis and treatment records of the user;
the calculating module is used for calculating the similarity between the reference review data and the target review data;
the evaluation module is used for performing qualification evaluation on the user according to the reference evaluation data if the similarity is larger than a preset similarity so as to obtain a qualification evaluation result;
the computing module is specifically configured to:
acquiring the same number of review items in the reference review data and the target review data;
calculating a ratio between the number of identical review items and the number of review items in the reference review data, and determining the ratio as a similarity between the reference review data and the target review data; wherein, the review item is a condition item.
7. A server comprising a processor, an input device, an output device and a memory, the processor, the input device, the output device and the memory being interconnected, wherein the memory is adapted to store a computer program comprising program instructions, the processor being configured to invoke the program instructions to perform the method of any of claims 1-5.
8. A computer readable storage medium, characterized in that the computer readable storage medium stores a computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method of any of claims 1-5.
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