CN113627793A - Data processing method and device, electronic equipment and storage medium - Google Patents
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Abstract
The present disclosure provides a data processing method, which can be applied to the financial field and the technical field of big data application. The data processing method comprises the following steps: acquiring subjective evaluation information of a target user in a preset time period, wherein each piece of subjective evaluation information corresponds to a subjective index, and the subjective evaluation information comprises transaction data and evaluation data; determining the subjective index value of each subjective index of the target user according to the subjective evaluation rule table and the subjective evaluation information; checking each subjective index value, and outputting a checking result; and under the condition that the verification result shows that the subjective index value is correct, applying the subjective index value to the scene service corresponding to the subjective index. The present disclosure also provides a data processing apparatus, a device, a storage medium, and a program product.
Description
Technical Field
The present disclosure relates to the field of finance and big data application technologies, and more particularly, to a data processing method, apparatus, device, medium, and program product.
Background
Subjective index is also called sensory index, and refers to an index that cannot or is difficult to be measured directly or counted to obtain a value, and the amount of the subjective index can only be determined by the feeling and evaluation of people. At present, various service products or service systems need to be updated according to subjective indexes of users.
In carrying out the inventive concept of the present disclosure, the inventors found that at least the following problems exist in the related art: for the currently acquired data, the subjective index of the user cannot be accurately evaluated, so that the service product or the service system cannot be accurately updated.
Disclosure of Invention
In view of the foregoing, the present disclosure provides methods, apparatuses, devices, media and program products for improving data processing.
According to a first aspect of the present disclosure, there is provided a data processing method including:
acquiring subjective evaluation information of a target user in a preset time period, wherein each piece of subjective evaluation information corresponds to a subjective index, and the subjective evaluation information comprises transaction data and evaluation data;
determining a subjective index value of each subjective index of the target user according to a subjective evaluation rule table and the subjective evaluation information;
checking each subjective index value, and outputting a checking result;
and under the condition that the verification result shows that the subjective index value is correct, applying the subjective index value to a scene service corresponding to the subjective index.
According to an embodiment of the present disclosure, the acquiring subjective evaluation information of the target user within a preset time period includes:
acquiring a preset time period selection operation;
responding to the preset time period selection operation, and acquiring the transaction data and the evaluation data of the target user in the preset time period;
and processing the transaction data and the evaluation data according to a preset screening rule to generate the subjective evaluation information.
According to an embodiment of the present disclosure, the subjective evaluation rule table includes subjective index name information and description information corresponding to the subjective index;
the method for constructing the subjective evaluation rule table comprises the following steps:
acquiring subjective index name information and a plurality of description information corresponding to each subjective index name information;
generating a subjective evaluation rule table template according to the subjective index name information and each piece of description information;
and processing the subjective evaluation rule table template to generate the subjective evaluation rule table.
According to an embodiment of the present disclosure, the processing the subjective evaluation rule table template to generate the subjective evaluation rule table includes:
obtaining subjective index assignment operation;
responding to the subjective index assignment operation, and determining a subjective index value interval corresponding to each piece of description information, wherein the subjective index value interval comprises a plurality of candidate subjective index values;
and filling each subjective index value interval into an area corresponding to each description information in the subjective evaluation rule table template to generate the subjective evaluation rule table.
According to an embodiment of the present disclosure, the subjective evaluation rule table further includes application scenario information;
the method for constructing the subjective evaluation rule table further comprises the following steps:
acquiring the application scene information corresponding to each subjective index name information;
and filling each piece of application scene information into an area corresponding to each piece of subjective index name information in the subjective evaluation rule table template to generate the subjective evaluation rule table.
According to an embodiment of the present disclosure, the determining a subjective index value of each subjective index of the target user according to a subjective evaluation rule table and the subjective evaluation information includes:
determining target description information corresponding to the target user in the plurality of description information according to the subjective evaluation information;
determining a target subjective index value interval in a plurality of subjective index value intervals according to the target description information;
and determining the subjective index value corresponding to the target user in a plurality of candidate subjective index values according to the target subjective index value interval.
A second aspect of the present disclosure provides a data processing apparatus comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring subjective evaluation information of a target user within a preset time period, each piece of subjective evaluation information corresponds to a subjective index, and the subjective evaluation information comprises transaction data and evaluation data;
the determination module is used for determining the subjective index value of each subjective index of the target user according to a subjective evaluation rule table and the subjective evaluation information;
the checking module is used for checking each subjective index value and outputting a checking result;
and the application module is used for applying the subjective index value to the scene service corresponding to the subjective index under the condition that the verification result represents that the subjective index value is correct.
A third aspect of the present disclosure provides an electronic device, comprising: one or more processors; a memory for storing one or more programs, wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the above-described data processing method.
A fourth aspect of the present disclosure also provides a computer-readable storage medium having stored thereon executable instructions that, when executed by a processor, cause the processor to perform the above-mentioned data processing method.
A fifth aspect of the present disclosure also provides a computer program product comprising a computer program which, when executed by a processor, implements the above-described data processing method.
According to the embodiment of the disclosure, the target user's subjective index value of each subjective index of the target user is obtained by acquiring the transaction data and the evaluation data of the target user within a preset time period and quantifying the subjective index of the user in the subjective evaluation rule table according to the transaction data and the evaluation data. And after verification, under the condition that the subjective index value is correct, applying the subjective index value to the scene service corresponding to the subjective index. And converting the subjective index of the client into measurable and easy-to-use index data through the subjective evaluation rule table, and applying the index data to the scene service. Therefore, the accuracy of the subjective index value can be improved, so that the service personnel can update the service product or the service system more accurately.
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The foregoing and other objects, features and advantages of the disclosure will be apparent from the following description of embodiments of the disclosure, which proceeds with reference to the accompanying drawings, in which:
fig. 1 schematically shows an application scenario diagram of a data processing method according to an embodiment of the present disclosure.
Fig. 2 schematically shows a flow chart of a data processing method according to an embodiment of the present disclosure.
Fig. 3 schematically shows a data processing method according to another embodiment of the present disclosure.
Fig. 4 schematically shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure.
Fig. 5 schematically shows a block diagram of an electronic device adapted to implement a data processing method according to an embodiment of the present disclosure.
Detailed Description
Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. It should be understood that the description is illustrative only and is not intended to limit the scope of the present disclosure. In the following detailed description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of the embodiments of the disclosure. It may be evident, however, that one or more embodiments may be practiced without these specific details. Moreover, in the following description, descriptions of well-known structures and techniques are omitted so as to not unnecessarily obscure the concepts of the present disclosure.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. The terms "comprises," "comprising," and the like, as used herein, specify the presence of stated features, steps, operations, and/or components, but do not preclude the presence or addition of one or more other features, steps, operations, or components.
All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art unless otherwise defined. It is noted that the terms used herein should be interpreted as having a meaning that is consistent with the context of this specification and should not be interpreted in an idealized or overly formal sense.
Where a convention analogous to "at least one of A, B and C, etc." is used, in general such a construction is intended in the sense one having skill in the art would understand the convention (e.g., "a system having at least one of A, B and C" would include but not be limited to systems that have a alone, B alone, C alone, a and B together, a and C together, B and C together, and/or A, B, C together, etc.).
Service organizations such as banks acquire the transaction data of the customers through the source application system, perform index processing on the transaction data, and provide the transaction data for developers or service personnel of the source application system to use, so that more humanized service is provided for the users. The source application system may include a transaction system in a bank counter, various bank transaction software of a user terminal, and the like.
In carrying out the inventive concept of the present disclosure, the inventors found that at least the following problems exist in the related art: for the currently acquired data, the subjective index of the user cannot be accurately evaluated, so that the service product or the service system cannot be accurately updated.
The embodiment of the disclosure provides a data processing method and a data processing device, wherein the data processing method comprises the following steps: acquiring subjective evaluation information of a target user in a preset time period, wherein each piece of subjective evaluation information corresponds to a subjective index, and the subjective evaluation information comprises transaction data and evaluation data; determining the subjective index value of each subjective index of the target user according to the subjective evaluation rule table and the subjective evaluation information; checking each subjective index value, and outputting a checking result; and under the condition that the verification result shows that the subjective index value is correct, applying the subjective index value to the scene service corresponding to the subjective index.
It should be noted that the data processing method and the data processing apparatus of the present disclosure may be used in the financial field and the field of big data application technology, and may also be used in any field other than the financial field and the field of big data application technology.
In the technical scheme of the disclosure, the acquisition, storage, application and the like of the personal information of the related user all accord with the regulations of related laws and regulations, and do not violate the good customs of the public order.
Fig. 1 schematically shows an application scenario diagram of a data processing method according to an embodiment of the present disclosure.
As shown in fig. 1, the application scenario 100 according to this embodiment may include a network, a terminal device, and a server. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. The terminal devices 101, 102, 103 may have installed thereon various communication client applications, such as shopping-like applications, web browser applications, search-like applications, instant messaging tools, mailbox clients, social platform software, etc. (by way of example only).
The terminal devices 101, 102, 103 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 105 may be a server providing various services, such as a background management server (for example only) providing support for websites browsed by users using the terminal devices 101, 102, 103. The background management server may analyze and perform other processing on the received data such as the user request, and feed back a processing result (e.g., a webpage, information, or data obtained or generated according to the user request) to the terminal device.
It should be noted that the data processing method provided by the embodiment of the present disclosure may be generally executed by the server 105. Accordingly, the data processing apparatus provided by the embodiments of the present disclosure may be generally disposed in the server 105. The data processing method provided by the embodiment of the present disclosure may also be executed by a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105. Accordingly, the data processing apparatus provided by the embodiment of the present disclosure may also be disposed in a server or a server cluster different from the server 105 and capable of communicating with the terminal devices 101, 102, 103 and/or the server 105.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
The data processing method of the disclosed embodiment will be described in detail below with fig. 2 to 3 based on the scenario described in fig. 1.
Fig. 2 schematically shows a flow chart of a data processing method according to an embodiment of the present disclosure.
As shown in fig. 2, the data processing of this embodiment includes operations S201 to S204, and the data processing method may be performed by a terminal device or a server.
In operation S201, subjective evaluation information of a target user within a preset time period is obtained, where each piece of subjective evaluation information corresponds to a subjective index, and the subjective evaluation information includes transaction data and evaluation data.
According to the embodiment of the present disclosure, the preset time period may include, for example, 3 months, 6 months, or 12 months, and may also be any other time period according to specific implementation needs. The subjective indicators may include, for example, the degree of adhesion of the target user to a certain product, the communication difficulty, the enthusiasm degree, the quartic degree, the integrity, the credibility, and the like. The transaction data may include, for example, user purchase records, deposit records, transaction records, and the like. The evaluation data may include, for example, a subjective evaluation of the target user by a service person, or the like.
According to the embodiment of the present disclosure, the subjective evaluation information for a certain target user may include, for example, both transaction data and evaluation data, or only transaction data or evaluation data. According to specific implementation needs, the content of the subjective evaluation information can be adjusted, and the specific content of the subjective evaluation information is not specifically limited in the embodiment of the present disclosure.
According to an embodiment of the present disclosure, the manner of acquiring the subjective evaluation information may include, for example, channel-side data acquisition and product-side data acquisition. The channel-side data collection may include, for example, collection of evaluation data of a target user by a customer manager or the like. Product-side data collection may include, for example, collection of targeted customer transaction behavior data, and the like.
In operation S202, a subjective index value of each subjective index of the target user is determined according to the subjective evaluation rule table and the subjective evaluation information.
According to an embodiment of the present disclosure, the subjective evaluation table may include, for example, a correspondence between subjective evaluation information and subjective index values. For example, the subjective index value of each subjective index of the target user can be determined by referring to a plurality of keyword information or description information in the subjective evaluation information of the target user in the subjective evaluation table.
In operation S203, each subjective index value is verified, and a verification result is output.
According to the embodiment of the disclosure, the method for verifying each subjective index value may include, for example, a method of verifying by a designated person or a method of automatically verifying by a system. According to specific implementation needs, other forms of verification methods may also be adopted, and embodiments of the present disclosure do not specifically limit the verification method of the subjective index value.
According to the embodiment of the disclosure, by checking the subjective index values, inaccurate subjective index values can be removed, and the accuracy of each subjective index value is further improved.
In operation S204, in case that the verification result indicates that the subjective index value is correct, the subjective index value is applied to a scene service corresponding to the subjective index.
According to an embodiment of the present disclosure, the scenario services may include, for example, precision marketing, risk control, business analysis, business consultation, business handling, and the like. According to specific implementation needs, the leader index can be applied to any scene service, and the specific type of the scene service is not specifically limited in the embodiment of the present disclosure.
According to an embodiment of the present disclosure, a method of applying subjective index values to a scene service corresponding to subjective indexes may include, for example, deploying each subjective index value into a corresponding channel, product.
According to the embodiment of the present disclosure, in the case that the verification result characterizes the subjective index value is wrong, the operations S201 and S202 are repeatedly performed until the verification result characterizes the subjective index value is correct.
According to the embodiment of the disclosure, the target user's subjective index value of each subjective index of the target user is obtained by acquiring the transaction data and the evaluation data of the target user within a preset time period and quantifying the subjective index of the user in the subjective evaluation rule table according to the transaction data and the evaluation data. And after verification, under the condition that the subjective index value is correct, applying the subjective index value to the scene service corresponding to the subjective index. And converting the subjective index of the client into measurable and easy-to-use index data through the subjective evaluation rule table, and applying the index data to the scene service. Therefore, the accuracy of the subjective index value can be improved, so that the service personnel can update the service product or the service system more accurately.
Fig. 3 schematically shows a data processing method according to another embodiment of the present disclosure.
As shown in fig. 3, the method includes operations S301 to S303.
In operation S301, subjective evaluation information of the target user is collected, where the subjective evaluation information may include, for example, subjective index data, and the collection of the subjective index data may include channel-side data collection and product-side data collection. And generating customer transaction data and customer manager evaluation data after channel side data acquisition and product side data acquisition.
In operation S302, the customer transaction behavior data and the customer manager evaluation data are processed by the subjective index rule to generate a subjective index value. The subjective index rules may include, for example, a subjective evaluation rule table.
In operation S303, the subjective index value is applied to a scenario service, which may include, for example, precision marketing, risk control, and business analysis.
According to the embodiment of the disclosure, acquiring subjective evaluation information of a target user within a preset time period includes:
and acquiring a preset time period selection operation. And responding to the selection operation of the preset time period, and acquiring the transaction data and the evaluation data of the target user in the preset time period. And processing the transaction data and the evaluation data according to a preset screening rule to generate subjective evaluation information.
According to an embodiment of the present disclosure, before the preset time period selection operation is acquired, for example, a preset time period selection page may be presented, and the preset time period selection page may include, for example, an initial time selection box and an end time selection box. The start time and the end time of the preset time period may be selected through the initial time selection box and the end time selection box.
According to the embodiment of the present disclosure, the preset time period may be determined according to the behavior habit of the target user, for example. The behavior habits may include, for example, how often transactions are made.
According to an embodiment of the present disclosure, the preset time period may include, for example, 10 days, 20 days, 3 months, 6 months, or the like. The specific duration of the preset time period is not specifically limited in this disclosure.
According to an embodiment of the present disclosure, the preset filtering rule may include, for example, a customized filtering rule. For example, when the communication difficulty of the target user is quantified, for example, data of online business transaction of the user may be deleted. Alternatively, for example, invalid data or the like may be deleted.
According to the embodiment of the disclosure, by screening the transaction data, the evaluation data and the like, irrelevant and invalid data can be deleted, the operation pressure of the system is reduced, and the processing speed of the system is increased.
According to an embodiment of the present disclosure, the subjective evaluation rule table includes subjective index name information and description information corresponding to subjective indexes.
According to an embodiment of the present disclosure, the subjective index name information may include, for example, a custom name for each subjective index or a common name for each subjective index, or the like. The description information may include, for example, a brief description of each subjective index, and the like.
According to the embodiment of the disclosure, the method for constructing the subjective evaluation rule table comprises the following steps:
subjective index name information and a plurality of pieces of description information corresponding to each piece of subjective index name information are acquired. And generating a subjective evaluation rule table template according to the subjective index name information and each piece of description information. And processing the subjective evaluation rule table template to generate a subjective evaluation rule table.
According to an embodiment of the present disclosure, the method for processing the subjective evaluation rule table may include, for example, determining a correspondence between each type of subjective index name information and an intuitive index value.
According to the embodiment of the disclosure, processing the subjective evaluation rule table template to generate the subjective evaluation rule table comprises:
and obtaining subjective index assignment operation. And responding to subjective index assignment operation, and determining a subjective index value interval corresponding to each piece of description information, wherein the subjective index value interval comprises a plurality of candidate subjective index values. And filling each subjective index value interval into an area corresponding to each description information in the subjective evaluation rule table template to generate a subjective evaluation rule table.
According to embodiments of the present disclosure, the assignment operation may include, for example, a manual input or a system automatic input.
According to an embodiment of the present disclosure, the subjective index value section may include, for example, a numerical value section, for example, 5 pieces of description information correspond to a certain subjective index, and the subjective index value section corresponding to each piece of description information may include, for example, 1 to 2, 3 to 4, 5 to 6, 7 to 8, and 9 to 10. Further, the range of values may include any range between any two values, for example, the range of values may include 0 to 100 or 0 to 1.
According to an embodiment of the present disclosure, the alternative subjective index value may include, for example, a numerical value in each subjective index value interval. Taking 1-2 as the subjective index value interval as an example, the alternative subjective index values are 1 and 2. The alternative subjective index value may also be any value other than an integer, such as 1.2, 1.5, etc., according to the specific implementation needs.
According to an embodiment of the present disclosure, the subjective evaluation rule table further includes application scenario information.
According to an embodiment of the present disclosure, the application scenario information may include, for example, a service scenario or a usage scenario, etc. corresponding to each subjective index. For example, the application scenario corresponding to the communication difficulty may include, for example, precision marketing, and the like.
According to the embodiment of the disclosure, the method for constructing the subjective evaluation rule table further includes:
and acquiring application scene information corresponding to each subjective index name information. And filling each application scene information into an area corresponding to each subjective index name information in the subjective evaluation rule table template to generate a subjective evaluation rule table.
According to the embodiments of the present disclosure, by filling the application scenario information corresponding to each subjective index name information into the subjective evaluation rule table, the functionality and the intuitiveness of the subjective evaluation rule table can be increased. The service staff can use information such as subjective index value accurately.
According to the embodiment of the present disclosure, determining the subjective index value of each subjective index of the target user according to the subjective evaluation rule table and the subjective evaluation information includes:
and determining target description information corresponding to the target user in the plurality of description information according to the subjective evaluation information. And determining a target subjective index value interval in the plurality of subjective index value intervals according to the target description information. And determining a subjective index value corresponding to the target user in the plurality of candidate subjective index values according to the target subjective index value interval.
Based on the data processing method, the disclosure also provides a data processing device. The apparatus will be described in detail below with reference to fig. 4.
Fig. 4 schematically shows a block diagram of a data processing apparatus according to an embodiment of the present disclosure.
As shown in fig. 4, the data processing apparatus 400 of this embodiment includes a first acquisition module 401, a determination module 402, a verification module 403, and an application module 404.
The first obtaining module 401 is configured to obtain subjective evaluation information of a target user within a preset time period, where each subjective evaluation information corresponds to a subjective index, and the subjective evaluation information includes transaction data and evaluation data. In an embodiment, the first obtaining module 401 may be configured to perform the operation S201 described above, which is not described herein again.
A determining module 402, configured to determine a subjective index value of each subjective index of the target user according to the subjective evaluation rule table and the subjective evaluation information. In an embodiment, the determining module 402 may be configured to perform the operation S202 described above, which is not described herein again.
And a checking module 403, configured to check each subjective index value and output a checking result. In an embodiment, the check module 403 may be configured to perform the operation S203 described above, which is not described herein again.
And an application module 404, configured to apply the subjective index value to the scene service corresponding to the subjective index if the verification result indicates that the subjective index value is correct. In an embodiment, the application module 404 may be configured to perform the operation S204 described above, which is not described herein again.
According to an embodiment of the present disclosure, the first obtaining module 401 includes a first obtaining unit, a second obtaining unit, and a processing unit.
A first acquisition unit configured to acquire a preset time period selection operation.
And the second acquisition unit is used for responding to the selection operation of the preset time period and acquiring the transaction data and the evaluation data of the target user in the preset time period.
And the processing unit is used for processing the transaction data and the evaluation data according to a preset screening rule to generate subjective evaluation information.
According to an embodiment of the present disclosure, the subjective evaluation rule table includes subjective index name information and description information corresponding to subjective indexes.
According to an embodiment of the present disclosure, the data processing apparatus 400 further includes a second obtaining module, a generating module, and a processing module.
And the second acquisition module is used for acquiring the subjective index name information and a plurality of description information corresponding to each subjective index name information.
And the generating module is used for generating a subjective evaluation rule table template according to the subjective index name information and each piece of description information.
And the processing module is used for processing the subjective evaluation rule table template to generate a subjective evaluation rule table.
According to an embodiment of the present disclosure, a processing module includes a third obtaining unit, a first determining unit, and a filling unit.
And the third acquisition unit is used for acquiring subjective index assignment operation.
The first determination unit is used for responding to subjective index assignment operation and determining a subjective index value interval corresponding to each piece of description information, wherein the subjective index value interval comprises a plurality of candidate subjective index values;
and the filling unit is used for filling each subjective index value interval into an area corresponding to each description information in the subjective evaluation rule table template to generate the subjective evaluation rule table.
According to an embodiment of the present disclosure, the subjective evaluation rule table further includes application scenario information.
According to an embodiment of the present disclosure, the data processing apparatus 400 further includes a third obtaining module and a padding module.
And the third acquisition module is used for acquiring the application scene information corresponding to each subjective index name information.
And the filling module is used for filling each application scene information into the area corresponding to each subjective index name information in the subjective evaluation rule table template to generate the subjective evaluation rule table.
According to an embodiment of the present disclosure, the determining module 402 includes a second determining unit, a third determining unit, and a fourth determining unit.
And a second determination unit configured to determine target description information corresponding to the target user among the plurality of description information according to the subjective evaluation information.
And the third determining unit is used for determining a target subjective index value interval in the subjective index value intervals according to the target description information.
And the fourth determining unit is used for determining the subjective index value corresponding to the target user in the plurality of candidate subjective index values according to the target subjective index value interval.
According to the embodiment of the present disclosure, any plurality of the first obtaining module 401, the determining module 402, the verifying module 403, and the applying module 404 may be combined into one module to be implemented, or any one of them may be split into a plurality of modules. Alternatively, at least part of the functionality of one or more of these modules may be combined with at least part of the functionality of the other modules and implemented in one module. According to an embodiment of the present disclosure, at least one of the first obtaining module 401, the determining module 402, the verifying module 403 and the applying module 404 may be at least partially implemented as a hardware circuit, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a system on a chip, a system on a substrate, a system on a package, an Application Specific Integrated Circuit (ASIC), or may be implemented by hardware or firmware in any other reasonable manner of integrating or packaging a circuit, or implemented by any one of three implementations of software, hardware and firmware, or an appropriate combination of any several of them. Alternatively, at least one of the first obtaining module 401, the determining module 402, the checking module 403 and the application module 404 may be at least partly implemented as a computer program module, which when executed may perform a corresponding function.
Fig. 5 schematically shows a block diagram of an electronic device adapted to implement a data processing method according to an embodiment of the present disclosure.
As shown in fig. 5, an electronic device 500 according to an embodiment of the present disclosure includes a processor 501 that can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage section 508 into a Random Access Memory (RAM) 503. The processor 501 may comprise, for example, a general purpose microprocessor (e.g., a CPU), an instruction set processor and/or associated chipset, and/or a special purpose microprocessor (e.g., an Application Specific Integrated Circuit (ASIC)), among others. The processor 501 may also include onboard memory for caching purposes. Processor 501 may include a single processing unit or multiple processing units for performing different actions of a method flow according to embodiments of the disclosure.
In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 500 are stored. The processor 501, the ROM 502, and the RAM 503 are connected to each other by a bus 504. The processor 501 performs various operations of the method flows according to the embodiments of the present disclosure by executing programs in the ROM 502 and/or the RAM 503. Note that the programs may also be stored in one or more memories other than the ROM 502 and the RAM 503. The processor 501 may also perform various operations of method flows according to embodiments of the present disclosure by executing programs stored in the one or more memories.
According to an embodiment of the present disclosure, electronic device 500 may also include an input/output (I/O) interface 505, input/output (I/O) interface 505 also being connected to bus 504. The electronic device 500 may also include one or more of the following components connected to the I/O interface 505: an input portion 506 including a keyboard, a mouse, and the like; an output portion 507 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 508 including a hard disk and the like; and a communication section 509 including a network interface card such as a LAN card, a modem, or the like. The communication section 509 performs communication processing via a network such as the internet. The driver 510 is also connected to the I/O interface 505 as necessary. A removable medium 511 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 510 as necessary, so that a computer program read out therefrom is mounted into the storage section 508 as necessary.
The present disclosure also provides a computer-readable storage medium, which may be contained in the apparatus/device/system described in the above embodiments; or may exist separately and not be assembled into the device/apparatus/system. The computer-readable storage medium carries one or more programs which, when executed, implement the method according to an embodiment of the disclosure.
According to embodiments of the present disclosure, the computer-readable storage medium may be a non-volatile computer-readable storage medium, which may include, for example but is not limited to: a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. For example, according to embodiments of the present disclosure, a computer-readable storage medium may include ROM 502 and/or RAM 503 and/or one or more memories other than ROM 502 and RAM 503 described above.
Embodiments of the present disclosure also include a computer program product comprising a computer program containing program code for performing the method illustrated in the flow chart. When the computer program product runs in a computer system, the program code is used for causing the computer system to realize the item recommendation method provided by the embodiment of the disclosure.
The computer program performs the above-described functions defined in the system/apparatus of the embodiments of the present disclosure when executed by the processor 501. The systems, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
In one embodiment, the computer program may be hosted on a tangible storage medium such as an optical storage device, a magnetic storage device, or the like. In another embodiment, the computer program may also be transmitted, distributed in the form of a signal on a network medium, downloaded and installed through the communication section 509, and/or installed from the removable medium 511. The computer program containing program code may be transmitted using any suitable network medium, including but not limited to: wireless, wired, etc., or any suitable combination of the foregoing.
In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 509, and/or installed from the removable medium 511. The computer program, when executed by the processor 501, performs the above-described functions defined in the system of the embodiments of the present disclosure. The systems, devices, apparatuses, modules, units, etc. described above may be implemented by computer program modules according to embodiments of the present disclosure.
In accordance with embodiments of the present disclosure, program code for executing computer programs provided by embodiments of the present disclosure may be written in any combination of one or more programming languages, and in particular, these computer programs may be implemented using high level procedural and/or object oriented programming languages, and/or assembly/machine languages. The programming language includes, but is not limited to, programming languages such as Java, C + +, python, the "C" language, or the like. The program code may execute entirely on the user computing device, partly on the user device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Those skilled in the art will appreciate that various combinations and/or combinations of features recited in the various embodiments and/or claims of the present disclosure can be made, even if such combinations or combinations are not expressly recited in the present disclosure. In particular, various combinations and/or combinations of the features recited in the various embodiments and/or claims of the present disclosure may be made without departing from the spirit or teaching of the present disclosure. All such combinations and/or associations are within the scope of the present disclosure.
The embodiments of the present disclosure have been described above. However, these examples are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments are described separately above, this does not mean that the measures in the embodiments cannot be used in advantageous combination. The scope of the disclosure is defined by the appended claims and equivalents thereof. Various alternatives and modifications can be devised by those skilled in the art without departing from the scope of the present disclosure, and such alternatives and modifications are intended to be within the scope of the present disclosure.
Claims (10)
1. A method of data processing, comprising:
acquiring subjective evaluation information of a target user in a preset time period, wherein each piece of subjective evaluation information corresponds to a subjective index, and the subjective evaluation information comprises transaction data and evaluation data;
determining a subjective index value of each subjective index of the target user according to a subjective evaluation rule table and the subjective evaluation information;
checking each subjective index value, and outputting a checking result;
and under the condition that the verification result shows that the subjective index value is correct, applying the subjective index value to a scene service corresponding to the subjective index.
2. The method according to claim 1, wherein the obtaining subjective evaluation information of the target user within a preset time period comprises:
acquiring a preset time period selection operation;
responding to the preset time period selection operation, and acquiring the transaction data and the evaluation data of the target user in the preset time period;
and processing the transaction data and the evaluation data according to a preset screening rule to generate the subjective evaluation information.
3. The method according to claim 1, wherein the subjective evaluation rule table includes subjective index name information and description information corresponding to the subjective index;
the method for constructing the subjective evaluation rule table comprises the following steps:
acquiring subjective index name information and a plurality of description information corresponding to each subjective index name information;
generating a subjective evaluation rule table template according to the subjective index name information and each piece of description information;
and processing the subjective evaluation rule table template to generate the subjective evaluation rule table.
4. The method of claim 3, wherein the processing the subjective evaluation rules table template to generate the subjective evaluation rules table comprises:
obtaining subjective index assignment operation;
responding to the subjective index assignment operation, and determining a subjective index value interval corresponding to each piece of description information, wherein the subjective index value interval comprises a plurality of candidate subjective index values;
and filling each subjective index value interval into an area corresponding to each description information in the subjective evaluation rule table template to generate the subjective evaluation rule table.
5. The method according to claim 3, wherein the subjective evaluation rule table further includes application scenario information;
the method for constructing the subjective evaluation rule table further comprises the following steps:
acquiring the application scene information corresponding to each subjective index name information;
and filling each piece of application scene information into an area corresponding to each piece of subjective index name information in the subjective evaluation rule table template to generate the subjective evaluation rule table.
6. The method according to any one of claims 1 to 5, wherein the determining a subjective index value for each subjective index of the target user according to a subjective evaluation rule table and the subjective evaluation information includes:
determining target description information corresponding to the target user in the plurality of description information according to the subjective evaluation information;
determining a target subjective index value interval in a plurality of subjective index value intervals according to the target description information;
and determining the subjective index value corresponding to the target user in a plurality of candidate subjective index values according to the target subjective index value interval.
7. A data processing apparatus comprising:
the system comprises a first acquisition module, a second acquisition module and a third acquisition module, wherein the first acquisition module is used for acquiring subjective evaluation information of a target user within a preset time period, each piece of subjective evaluation information corresponds to a subjective index, and the subjective evaluation information comprises transaction data and evaluation data;
the determination module is used for determining the subjective index value of each subjective index of the target user according to a subjective evaluation rule table and the subjective evaluation information;
the checking module is used for checking each subjective index value and outputting a checking result;
and the application module is used for applying the subjective index value to the scene service corresponding to the subjective index under the condition that the verification result represents that the subjective index value is correct.
8. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
wherein the one or more programs, when executed by the one or more processors, cause the one or more processors to perform the method of any of claims 1-6.
9. A computer readable storage medium having stored thereon executable instructions which, when executed by a processor, cause the processor to perform the method of any one of claims 1 to 6.
10. A computer program product comprising a computer program which, when executed by a processor, implements a method according to any one of claims 1 to 6.
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