CN115205030A - Wind-controlled user portrait system based on configurable big data analysis - Google Patents
Wind-controlled user portrait system based on configurable big data analysis Download PDFInfo
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Abstract
The invention relates to a configurable big data analysis-based wind control user portrait system, which belongs to the technical field of big data processing, can greatly reduce the iteration period after business personnel newly add or modify user index latitude, needs business personnel and programmers to jointly complete if needing to update a wind control user portrait configuration rule in the prior art, can be operated and completed by the business personnel after the scheme is on line, and does not need developers to carry out secondary iteration development. The invention can reduce the human input of programmers, can effectively improve the working efficiency of business personnel, and can support the timely effect and the timely effect of the configurable wind control user portrait system of big data analysis, thereby greatly improving the fault-tolerant capability.
Description
Technical Field
The invention belongs to the technical field of big data processing, and particularly relates to a configurable big data analysis-based wind control user portrait system.
Background
For a long time, service pain points of the wind control user portrait are concentrated in the characteristics of large latitude, large span and the like of the user portrait, and the problems of large manual investment, low efficiency, slow iteration and the like exist in processing of all dimensions. Whether to efficiently solve each latitude portrait of the user and timely process a plurality of latitudes is a user portrait focus attention field. The general user portrait requires programmers to design a wind control index calculation rule flow in advance, compile and package programs, and then deliver the programs to business personnel to select and use the specified latitude.
Such disadvantages are:
1. the wind control user portrait needs to be realized by professional programmers;
2. when a new rule needs to be added or a rule needs to be modified, business personnel need to feed back to a programmer for encoding, repacking and releasing, the updating period is long, and the effectiveness cannot be guaranteed;
3. the traditional user portrait needs to consume a large amount of memory in latitude aggregation, so that a single machine cannot meet the operation requirement of a service system with a large number of rules;
4. the traditional user latitude is fixed, a corresponding set of calculation and analysis flow needs to be developed again when the user latitude is newly added, the flow is excessive, and the operation and maintenance difficulty is high.
Disclosure of Invention
The invention aims to provide a configurable big data analysis-based wind control user portrait system, which is used for solving the technical problems in the prior art, so that the difficulty of development, operation and maintenance in the portrait process of the wind control user is reduced, and the iteration period is reduced.
In order to realize the purpose, the technical scheme of the invention is as follows:
the wind control user portrait configuration method based on big data analysis comprises the following steps:
s1: the wind control business personnel edit, increase and delete the portrait configuration rule of the wind control user through a recording interface module; in the process, the configuration items meeting the requirements are quickly inquired for operation through fuzzy matching;
s2: after a configuration rule is updated, waiting for a specific period of time, checking the validity of the rule, and converting a legal user portrait rule set into parameters of a rear-end calculation engine;
s3: starting a user portrait latitude index summarizing program, processing in real time through a parallel streaming rule processing engine based on a distributed scheduler, acquiring appointed original user index data according to configuration, and storing the original user index data in HBASE to realize dynamic field expansion;
s4: and starting a user portrait latitude statistical program, dynamically selecting according to the user portrait latitude statistics, and displaying the result.
Further, in step S1, when the wind control user portrait is edited, added, or deleted, the entered wind control user portrait needs to be subjected to standardized format recognition processing, which specifically includes:
acquiring a recorded wind control user portrait;
extracting real-time basic features and real-time fusion features of the wind control user portrait, and acquiring standard basic features and standard fusion features in historical wind control user portrait data from a database;
and respectively matching and recognizing the real-time basic feature and the real-time fusion feature of the currently recorded wind control user portrait with the standard basic feature and the standard fusion feature, if the real-time basic feature is matched with the standard basic feature and the real-time fusion feature is matched with the standard fusion feature, judging that the currently recorded wind control user portrait conforms to a standardized format, and normally operating subsequent actions, otherwise, judging that the currently recorded wind control user portrait does not conform to the standardized format, thereby abandoning the currently recorded wind control user portrait.
Further, the real-time basic features are portrait attributes corresponding to the wind control user portrait; the real-time fusion feature is a fusion feature of financial attributes and wind control attributes of financial users corresponding to the wind control user portrait.
Further, the matching identification of the real-time basic features and the standard basic features is specifically as follows:
when the real-time basic features and the standard basic features are subjected to first matching identification, if the real-time basic features are not matched with the standard basic features, temporarily storing a current first matching identification result;
performing secondary matching identification on the real-time basic features and the standard basic features, and if the real-time basic features are matched with the standard basic features at the moment, discarding the primary matching identification result and taking the secondary matching identification result as the actual matching identification result; and if the real-time basic features are not matched with the standard basic features, taking the first matching identification result as an actual matching identification result.
Further, the matching identification of the real-time fusion features and the standard fusion features is specifically as follows:
when the real-time fusion features and the standard fusion features are subjected to first matching identification, if the real-time fusion features are not matched with the standard fusion features, temporarily storing a current first matching identification result;
performing secondary matching identification on the real-time fusion features and the standard fusion features, and if the real-time fusion features are matched with the standard fusion features at the moment, discarding the first matching identification result and taking the secondary matching identification result as the actual matching identification result; and if the real-time fusion features are not matched with the standard fusion features, taking the first matching recognition result as an actual matching recognition result.
A wind control user portrait system based on configurable big data analysis performs configuration of a wind control user portrait through the wind control user portrait configuration method based on big data analysis.
A computer storage medium having stored thereon a computer program which, when executed, performs the method of wind controlled user representation configuration based on big data analysis as described above.
Compared with the prior art, the invention has the beneficial effects that:
one of the beneficial effects of the scheme is that the iteration cycle after the user index latitude is newly increased or modified by the service personnel can be greatly reduced, in the prior art, if the configuration rule of the wind control user portrait needs to be updated, the service personnel and the programming personnel are required to complete the operation, the scheme can be completed only by the service personnel after being on line, and secondary iteration development of the developer is not needed. The invention can reduce the human input of programmers, can effectively improve the working efficiency of business personnel, and can support the timely effect and the timely effect of the configurable wind control user portrait system of big data analysis, thereby greatly improving the fault-tolerant capability.
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FIG. 1 is a flow chart illustrating the steps of one embodiment of the present invention.
FIG. 2 is a logic diagram of an embodiment of the present invention.
FIG. 3 is a flowchart illustrating the process of standardized format recognition of a user profile in a wind control system according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention are clearly and completely described below with reference to fig. 1 to 3 of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example (b):
as shown in fig. 1 and 2, a method for configuring a wind-controlled user portrait based on big data analysis is provided, which includes the following steps:
s1: the wind control business personnel edit, increase and delete the configuration rule of the wind control user portrait through the input interface module; in the process, through fuzzy matching, quickly inquiring configuration items meeting the requirements for operation;
s2: after a configuration rule is updated, waiting for a specific period of time, checking the validity of the rule, and converting a legal user portrait rule set into parameters of a rear-end calculation engine;
s3: starting a user portrait latitude index summarizing program, processing in real time through a parallel streaming rule processing engine based on a distributed scheduler, acquiring appointed original user index data according to configuration, and storing the original user index data in HBASE to realize dynamic field expansion;
s4: and starting a user portrait latitude statistical program, dynamically selecting according to the user portrait latitude statistics, and displaying the result.
By the scheme, the iteration cycle after the user index latitude is newly increased or modified by service personnel can be greatly shortened, in the prior art, if the wind control user portrait configuration rule needs to be updated, the operation is completed by the service personnel and programmers together, and the scheme can be completed by the service personnel after being on line and does not need secondary iterative development of developers. The invention can reduce the manpower input of programmers, can effectively improve the working efficiency of business personnel, and can support the timely effectiveness and the timely effectiveness of the configurable wind control user portrait system for big data analysis, thereby greatly improving the fault-tolerant capability.
As shown in fig. 3, in step S1, when the wind control user portrait is edited, added, or deleted, a standardized format recognition process needs to be performed on the entered wind control user portrait, which is specifically as follows:
acquiring a recorded wind control user portrait;
extracting real-time basic features and real-time fusion features of the wind control user portrait, and acquiring standard basic features and standard fusion features in historical wind control user portrait data from a database;
and respectively matching and recognizing the real-time basic feature and the real-time fusion feature of the currently recorded wind control user portrait with the standard basic feature and the standard fusion feature, if the real-time basic feature is matched with the standard basic feature and the real-time fusion feature is matched with the standard fusion feature, judging that the currently recorded wind control user portrait conforms to a standardized format, and normally operating subsequent actions, otherwise, judging that the currently recorded wind control user portrait does not conform to the standardized format, thereby abandoning the currently recorded wind control user portrait.
By the scheme, the recorded wind control user portrait data can be effectively ensured to be the target wind control user portrait data, and subsequent data analysis misoperation caused by recording abnormal wind control user portrait data is avoided.
Further, the real-time basic features are portrait attributes corresponding to the portrait of the wind-controlled user; the real-time fusion feature is a fusion feature of financial attributes and wind control attributes of financial users corresponding to the wind control user portrait.
By the scheme, the basic features and the fusion features are used as the judgment standard of the portrait of the target wind-controlled user, so that the reliability deficiency caused by judgment of single features can be avoided, and the safety and reliability of the input portrait of the wind-controlled user are guaranteed.
Further, the matching identification of the real-time basic features and the standard basic features is specifically as follows:
when the real-time basic feature and the standard basic feature are subjected to first matching identification, if the real-time basic feature is not matched with the standard basic feature, temporarily storing a current first matching identification result;
performing secondary matching identification on the real-time basic features and the standard basic features, and if the real-time basic features are matched with the standard basic features at the moment, discarding the primary matching identification result and taking the secondary matching identification result as the actual matching identification result; and if the real-time basic features are not matched with the standard basic features at the moment, taking the first matching identification result as an actual matching identification result.
Further, the matching identification of the real-time fusion features and the standard fusion features is specifically as follows:
when the real-time fusion features and the standard fusion features are subjected to first matching identification, if the real-time fusion features are not matched with the standard fusion features, temporarily storing a current first matching identification result;
performing secondary matching identification on the real-time fusion features and the standard fusion features, and if the real-time fusion features are matched with the standard fusion features at the moment, discarding the primary matching identification results, and taking the secondary matching identification results as actual matching identification results; and if the real-time fusion feature is not matched with the standard fusion feature at the moment, taking a first matching identification result as an actual matching identification result.
Through the scheme, the basic features and the fusion features are matched and identified twice, so that system misjudgment can be effectively avoided, and accidental errors are reduced to a great extent.
A wind control user portrait system based on configurable big data analysis performs configuration of a wind control user portrait through the wind control user portrait configuration method based on big data analysis.
A computer storage medium having stored thereon a computer program which, when executed, performs a wind-controlled user portrait configuration method based on big data analysis as described above.
The above are preferred embodiments of the present invention, and all changes made according to the technical solutions of the present invention that produce functional effects do not exceed the scope of the technical solutions of the present invention belong to the protection scope of the present invention.
Claims (7)
1. The wind control user portrait configuration method based on big data analysis is characterized by comprising the following steps of:
s1: the wind control business personnel edit, increase and delete the portrait configuration rule of the wind control user through a recording interface module; in the process, the configuration items meeting the requirements are quickly inquired for operation through fuzzy matching;
s2: after a configuration rule is updated, waiting for a specific period of time, checking the validity of the rule, and converting a legal user portrait rule set into parameters of a rear-end calculation engine;
s3: starting a user portrait latitude index summarizing program, processing in real time through a parallel streaming rule processing engine based on a distributed scheduler, acquiring appointed original user index data according to configuration, and storing the original user index data in HBASE to realize dynamic field expansion;
s4: and starting a user portrait latitude statistical program, dynamically selecting according to the user portrait latitude statistics, and displaying the result.
2. The method for configuring a wind-controlled user portrait based on big data analysis according to claim 1, wherein in step S1, when the wind-controlled user portrait is edited, added, or deleted, a standardized format recognition process needs to be performed on the entered wind-controlled user portrait, specifically as follows:
acquiring a recorded portrait of a wind-controlled user;
extracting real-time basic features and real-time fusion features of the wind control user portrait, and acquiring standard basic features and standard fusion features in historical wind control user portrait data from a database;
and respectively matching and recognizing the real-time basic feature and the real-time fusion feature of the currently recorded wind control user portrait with the standard basic feature and the standard fusion feature, if the real-time basic feature is matched with the standard basic feature and the real-time fusion feature is matched with the standard fusion feature, judging that the currently recorded wind control user portrait conforms to a standardized format, and normally operating subsequent actions, otherwise, judging that the currently recorded wind control user portrait does not conform to the standardized format, thereby abandoning the currently recorded wind control user portrait.
3. The method of claim 2, wherein the real-time base features are portrait attributes corresponding to the wind-controlled user portrait; the real-time fusion feature is a fusion feature of financial attributes and wind control attributes of financial users corresponding to the wind control user portrait.
4. The wind controlled user portrait configuration method based on big data analysis, as recited in claim 3, wherein the real-time base features are identified by matching with the standard base features as follows:
when the real-time basic feature and the standard basic feature are subjected to first matching identification, if the real-time basic feature is not matched with the standard basic feature, temporarily storing a current first matching identification result;
performing secondary matching identification on the real-time basic features and the standard basic features, and if the real-time basic features are matched with the standard basic features at the moment, discarding the primary matching identification result and taking the secondary matching identification result as the actual matching identification result; and if the real-time basic features are not matched with the standard basic features, taking the first matching identification result as an actual matching identification result.
5. The wind-controlled user portrait configuration method based on big data analysis of claim 4, wherein the real-time fusion features are matched with the standard fusion features for identification as follows:
when the real-time fusion features and the standard fusion features are subjected to first matching identification, if the real-time fusion features are not matched with the standard fusion features, temporarily storing a current first matching identification result;
performing secondary matching identification on the real-time fusion features and the standard fusion features, and if the real-time fusion features are matched with the standard fusion features at the moment, discarding the primary matching identification results, and taking the secondary matching identification results as actual matching identification results; and if the real-time fusion feature is not matched with the standard fusion feature at the moment, taking a first matching identification result as an actual matching identification result.
6. A wind-controlled user representation system based on configurable big data analysis, characterized in that the configuration of the wind-controlled user representation is performed by the wind-controlled user representation configuration method based on big data analysis according to any of claims 1-5.
7. A computer storage medium having a computer program stored thereon, the computer program when executed performing the method for wind-controlled user representation configuration based on big data analysis of any of claims 1-5.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115392937A (en) * | 2022-10-25 | 2022-11-25 | 成都新希望金融信息有限公司 | User fraud risk identification method and device, electronic equipment and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115392937A (en) * | 2022-10-25 | 2022-11-25 | 成都新希望金融信息有限公司 | User fraud risk identification method and device, electronic equipment and storage medium |
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Application publication date: 20221018 |