CN117435621A

CN117435621A - Information response method and device based on power grid service platform and computer equipment

Info

Publication number: CN117435621A
Application number: CN202311488857.8A
Authority: CN
Inventors: 李智诚; 陈华锋; 王程斯
Original assignee: Shenzhen Power Supply Bureau Co Ltd
Current assignee: Shenzhen Power Supply Bureau Co Ltd
Priority date: 2023-11-09
Filing date: 2023-11-09
Publication date: 2024-01-23

Abstract

The application relates to an information response method, an information response device, computer equipment and a storage medium based on a power grid service platform. The method comprises the following steps: receiving current query request information, and performing tag association processing on query data in the current query request information to obtain a query tag corresponding to the query data; when the query tag is in the level range of the standard data tag in the target database, searching corresponding target data in the target level range of the standard data tag based on the query tag, and returning the target data to the terminal corresponding to the current query request information; when the level of the query tag is greater than the level range of the standard data tag, triggering communication connection of the terminal corresponding to the current query request information, and performing information interaction based on the communication connection. By adopting the method, the automatic response or manual response service can be provided in time according to different access requirements of different users, and the service response efficiency is improved.

Description

Information response method and device based on power grid service platform and computer equipment

Technical Field

The present invention relates to the field of information processing technologies, and in particular, to an information response method, an information response device, a computer device, and a storage medium based on a power grid service platform.

Background

The grid service platform is a platform for receiving an access request from a user and providing an electric power service to the user according to the access request.

When receiving user access requests from different channels, the existing power grid service platform directly and uniformly transmits the received various access requests to an application server cluster for processing.

However, when the number of users accessing is suddenly increased or high concurrent access requests are faced, the problems of low access speed, easy platform collapse and the like often occur, so that the capability of providing services to the outside is poor, and the simultaneous access requirements of users from multiple service channels cannot be met.

Disclosure of Invention

In view of the foregoing, it is desirable to provide an information response method, apparatus, computer device, and storage medium based on a power grid service platform, which can improve service response efficiency.

In a first aspect, the present application provides an information response method based on a power grid service platform, including:

receiving current query request information, and performing label association processing on query data in the current query request information to obtain a query label corresponding to the query data, wherein the query label is a label obtained by identifying the service demand intensity corresponding to the query data;

When the query tag is in the level range of the standard data tag in the target database, searching corresponding target data in the target level range of the standard data tag based on the query tag, and returning the target data to the terminal corresponding to the current query request information; the standard data labels are obtained by classifying and sorting the data in the power grid service platform, and at least comprise labels of a secondary level, wherein the service demand intensity corresponding to the labels is increased according to the increase of the level of the labels;

and when the level of the query tag is greater than the level range of the standard data tag, triggering communication connection of the terminal corresponding to the current query request information, and performing information interaction based on the communication connection.

In one embodiment, the performing tag association processing on the query data in the current query request information to obtain a query tag corresponding to the query data includes:

according to the business demand intensity corresponding to the query data, different levels of query labels are associated, the query labels comprise at least three candidate levels of labels, and the business demand intensity corresponding to the labels is increased according to the increase of the levels of the labels;

When the business requirement intensity corresponding to the query data is smaller than or equal to the business requirement intensity corresponding to the standard data label of the highest level, the query labels of the corresponding levels are associated according to the business requirement intensity corresponding to the query data, and the business requirement intensities respectively corresponding to the query labels of the same level and the standard data label are matched;

when the business requirement intensity corresponding to the query data is greater than the business requirement intensity corresponding to the standard data label of the highest level, the query label of the corresponding level is associated according to the business requirement intensity corresponding to the query data, and the level of the query label is greater than the highest level of the standard data label.

In one embodiment, the method for retrieving corresponding target data within the target level range of the standard data tag based on the query tag comprises at least one of the following:

based on the level of the query tag, acquiring a standard data tag of a target level, and searching corresponding target data in the standard data tag of the target level;

and acquiring standard data labels of target levels based on the levels of the query labels, and respectively retrieving corresponding target data in the standard data labels of corresponding levels according to the order of gradual reduction from the target levels.

In one embodiment, when the query tag is within the level range of the standard data tag in the target database, the searching corresponding target data within the target level range of the standard data tag based on the query tag includes:

according to the quantity of the query request information and the business demand intensity corresponding to the query label of each query request information, adjusting the pairing relation between each task execution window and each query request information, wherein the task execution window is a window provided for the retrieval behavior based on the query label, and the service response time of the task execution window is reduced according to the increase of the business demand intensity;

and matching corresponding target task execution windows according to the service demand intensity, wherein the target task execution windows search corresponding target data in a target level range of the standard data labels.

In one embodiment, each data in the target database has a corresponding standard data tag, where the standard data tag is a tag obtained by sorting data in the power grid service platform, and the method includes:

dividing the data of the power grid service platform into one type of data and two types of data according to a data format, wherein the one type of data is conventional data which does not need to be subjected to format conversion processing, and the two types of data are to-be-processed data which needs to be subjected to format conversion processing;

Associating the first class data with a first class data tag, and performing format conversion processing on the second class data to obtain converted second class data;

and after the class-one data and the converted class-two data are classified, sequenced and integrated, associating a secondary data label and storing the secondary data label in the target database, wherein the primary data label and the secondary data label form the standard data label.

In one embodiment, when the level of the query tag is greater than the level range of the standard data tag, triggering communication connection of the terminal corresponding to the current query request information, and performing information interaction based on the communication connection, including:

according to the quantity of the query request information and the business demand intensity corresponding to the query label of each query request information, the pairing relation between each information interaction window and the terminal corresponding to each query request information is adjusted, wherein the information interaction window is a window for providing manual service for a user, and the service response time of the information interaction window is reduced according to the increase of the business demand intensity;

and matching a corresponding target information interaction window according to the service demand intensity, wherein the target information interaction window is in communication connection with a terminal corresponding to the current query request information.

In one embodiment, before receiving the current query request information, the method includes:

obtaining a target user database corresponding to the target user information according to the target user information corresponding to the historical query request information, and storing user data corresponding to the target user information and power grid service platform data corresponding to the user data in the target user database;

after receiving the current query request information, the method comprises the following steps:

and matching a current user database corresponding to the current user information according to the current user information corresponding to the current query request information, and taking the current user database as the target database.

In a second aspect, the present application further provides an information response device based on a power grid service platform, including:

and a receiving module: the method comprises the steps of receiving current query request information, carrying out tag association processing on query data in the current query request information to obtain a query tag corresponding to the query data, wherein the query tag is a tag obtained after identifying service demand intensity corresponding to the query data;

the first response module is used for searching corresponding target data in the target level range of the standard data tag based on the query tag when the query tag is in the level range of the standard data tag in the target database, and returning the target data to the terminal corresponding to the current query request information; the standard data labels are obtained by classifying and sorting the data in the power grid service platform, and at least comprise labels of a secondary level, wherein the service demand intensity corresponding to the labels is increased according to the increase of the level of the labels;

And the second response module is used for triggering communication connection of the terminal corresponding to the current query request information when the level of the query label is larger than the level range of the standard data label, and carrying out information interaction based on the communication connection.

In a third aspect, the present application also provides a computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:

In a fourth aspect, the present application also provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:

According to the information response method, the information response device, the computer equipment, the storage medium and the computer program product based on the power grid service platform, the query data in the query request information are associated with the corresponding query tag level according to the service demand intensity, and the data in the power grid service platform are classified and arranged and then associated with the corresponding standard data tag level; when the query tag is within the level range of the standard data tag, searching corresponding data in the database based on the query tag within the level range of the standard data tag, and returning the data to the terminal; when the level of the query tag is greater than the level range of the standard data tag, triggering communication connection with the terminal; therefore, according to different access requirements of different users, automatic response or manual response services can be provided in time, and service response efficiency is improved.

Drawings

In order to more clearly illustrate the embodiments of the present application or the technical solutions in the related art, the drawings that are required to be used in the embodiments or the related technical descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and other drawings may be obtained according to the drawings without inventive effort for a person having ordinary skill in the art.

FIG. 1 is an application environment diagram of an information response method based on a power grid service platform in one embodiment;

FIG. 2 is a flow chart of an information response method based on a power grid service platform in one embodiment;

FIG. 3 is a flow diagram of associating query data with a query tag in one embodiment;

FIG. 4 is a flow diagram of retrieving data within a level range of standard data tags based on query tags in one embodiment;

FIG. 5 is a flow diagram of a scheduling task execution window to execute a search task in one embodiment;

FIG. 6 is a flow chart of associating data of a grid service platform with standard data tags according to one embodiment;

FIG. 7 is a schematic flow chart of information interaction of a scheduling information interaction window in an embodiment;

FIG. 8 is a flow diagram of a method for obtaining a user database based on user information in one embodiment;

FIG. 9 is a block diagram of an information answering device based on a grid services platform in one embodiment;

fig. 10 is an internal structural view of a computer device in one embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be further described in detail with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.

The information response method based on the power grid service platform can be applied to an application environment shown in fig. 1. Wherein the terminal 102 communicates with the server 104 via a network. The server 104 receives the query request information from the terminal 102, and performs tag association processing on query data in the query request information to obtain a query tag corresponding to the query data; the business demand intensity corresponding to the query tag is increased according to the increase of the level of the tag. When the server 104 determines that the query tag is within the level range of the standard data tag in the database, then retrieving corresponding data within the level range of the standard data tag based on the query tag, and returning the data to the terminal 102; the standard data label is a label obtained by classifying and sorting data in the power grid service platform by the server 104, and the service demand intensity corresponding to the standard data label is increased according to the increase of the grade of the label. When the server 104 determines that the level of the query tag is greater than the level range of the standard data tag, a communication connection between the server 104 and the terminal 102 is triggered, and information interaction is performed based on the communication connection.

The data storage system may store data that the server 104 needs to process, and the database may be stored in the data storage system; the data storage system may be integrated on the server 104 or may be located on a cloud or other network server.

The terminal 102 may be, but not limited to, various personal computers, notebook computers, smartphones, tablet computers, internet of things devices and portable wearable devices, and the server 104 may be implemented by a stand-alone server or a server cluster formed by a plurality of servers.

In an exemplary embodiment, as shown in fig. 2, an information response method based on a power grid service platform is provided, and an example of application of the method to the server in fig. 1 is described, which includes the following steps S202 to S206. Wherein:

step S202, receiving current query request information, and performing label association processing on query data in the current query request information to obtain a query label corresponding to the query data, wherein the query label is a label obtained by identifying the service demand intensity corresponding to the query data.

The query request information refers to a request sent by a user or a system to a server. The query data refers to specific parameters or specific conditions in the query request information, and is used for designating the server to return specific data or information; the specific parameters may be represented as keywords, etc., and the specific conditions may be represented as screening conditions, ordering, field selection, etc. The query tag refers to a text or an identifier for describing information such as characteristics, contents, purposes and the like of query data; the query tag may be represented as a tag for referring to information of a specific parameter, a specific condition, etc. in the query data; the query tag may be attached to the query data, or may exist in the form of metadata, a table structure, or the like. The service demand intensity refers to urgency and priority of service demand; the business need strength may be expressed as an indicator of how important and urgent a particular business need or item is in an organization.

The method includes the steps of extracting key information from query request information, evaluating requirements of users according to the key information, and associating query data in the query request information with query tags of different levels according to different service requirement intensities corresponding to different requirements.

Optionally, the user intention can be analyzed by inquiring the request information, and whether the user requirement is one of the problems, the help request and the feedback provision is detected, so that the nature and the urgency of the service requirement are evaluated; the service demand intensity can be evaluated by associating information such as the context of the query request information, the dialogue history and the like; the emotion and emotion of the query request information can be recognized to know the attitude of the user, so that the service demand intensity is evaluated; the interaction mode and the use preference of the user can be known by monitoring the information such as user behavior, feedback information, historical access records and the like, so that the service demand intensity can be evaluated.

Alternatively, the traffic demand intensity may be represented using values or indicators, often denoted as "priority" or "urgency", for assessing the relative importance of different traffic demands, in order to more specifically quantify and measure: each business requirement may be assigned a numerical level, e.g., from 1 to 10, where 1 represents the lowest priority and 10 represents the highest priority; different factors can also be assigned different weights, and corresponding priorities of each business requirement can be calculated through the weights, for example, the factors can be expressed as enterprise strategic requirements, compliance requirements, client preference requirements and the like; the priority of the business needs may also be determined by a satisfaction score fed back by the user, e.g., a lower satisfaction demand may require a higher priority.

Step S204, when the query tag is within the level range of the standard data tag in the target database, searching corresponding target data within the target level range of the standard data tag based on the query tag, and returning the target data to the terminal corresponding to the current query request information; the standard data labels are obtained by classifying and sorting the data in the power grid service platform, and at least comprise labels of a second level, wherein the service demand intensity corresponding to the labels is increased according to the increase of the level of the labels.

Wherein a database refers to a system for storing, managing and organizing data. Standard data tags refer to general text or general identifiers that share and understand data between different organizations and systems, and are used to describe information such as characteristics, content, usage, etc. of the data; standard data tags follow specific standards or specifications to ensure that data can be consistently interpreted and used so that data can be effectively shared and interacted with in different systems, platforms and organizations; standard data tags may be attached to the data in the database, or may exist in the form of metadata, table structures, etc. In addition, the meaning interpretation and evaluation of the business requirement intensity corresponding to the standard data label can refer to the above expression of the business requirement intensity corresponding to the query label.

The method comprises the steps of carrying out classification and arrangement on data in a power grid service platform, associating standard data tags of different levels with the classified and arranged data according to corresponding service demand intensity, and storing the standard data tags in a database; when the level of the query tag corresponding to the query data is within the level range of the standard data tag, the corresponding standard data tag can be searched in the database through the query tag, the data matched according to the standard data tag is used as response information, and the response information is automatically returned to the terminal.

Optionally, the standard data tag at least includes a second-level tag, where data corresponding to the first-level tag is original data, and data corresponding to the second-level tag is standard data, that is, the data in the database includes: one is standard data generated by normalizing original data, wherein the standard data is associated with a first-level tag and a second-level tag at the same time; the other is standard data which does not need to be processed, and the standard data is associated with a secondary label.

Optionally, the range of the service demand intensity may be divided into a plurality of values or a plurality of value intervals, where each value or each value interval of the service demand intensity corresponds to the standard data tag of each level; for example, when the standard data labels are at a first level and a second level, the first level standard data label corresponds to the service demand intensity of the first numerical value interval, and the second level standard data label corresponds to the service demand intensity of the second numerical value interval, wherein the first and second intervals represent the sequentially increasing service demand intensity ranges.

And step S206, when the level of the query tag is greater than the level range of the standard data tag, triggering the communication connection of the terminal corresponding to the current query request information, and carrying out information interaction based on the communication connection.

Wherein a communication connection refers to a connection means for allowing data to be transferred and converted between different devices, computers or systems; the communication connection may be represented as a way of establishing a communication link between the server and the terminal device. Information interaction refers to the process of transferring, sharing, and exchanging information between individuals, organizations, devices, or systems; the information interaction process may involve various forms of information, such as text, images, sound, data, and the like.

For example, when the level of the query tag is greater than the level range of the standard data tag, the corresponding standard data tag cannot be retrieved in the database through the query tag, and then the communication connection relationship between the server and the terminal is established, and information interaction is performed with the user through a manual mode.

In the information response method based on the power grid service platform, the query data in the query request information is associated with the corresponding query tag level according to the service demand intensity, and the data in the power grid service platform is classified and arranged and then associated with the corresponding standard data tag level; when the query tag is within the level range of the standard data tag, searching corresponding data in the database based on the query tag within the level range of the standard data tag, and returning the data to the terminal; when the level of the query tag is greater than the level range of the standard data tag, triggering communication connection with the terminal; therefore, according to different access requirements of different users, automatic response or manual response services can be provided in time, and service response efficiency is improved.

In an exemplary embodiment, as shown in fig. 3, the tag association processing is performed on the query data in the current query request information to obtain the query tag corresponding to the query data, which includes steps S302 to S306. Wherein:

step S302, according to the service demand intensity corresponding to the query data, query labels of different levels are associated, the query labels comprise at least three candidate levels, and the service demand intensity corresponding to the labels is increased according to the increase of the levels of the labels.

Wherein, the query tag includes at least three candidate levels of tags, which means that the query tag may have one of a first level, a second level, a third level and more than the first level.

Illustratively, according to the service demand intensity corresponding to the query data, the query data is associated with the query tag of the corresponding level, wherein when the service demand intensity corresponding to the query data is larger, the query data is associated with the query tag of the larger level.

Optionally, the range of the service demand intensity may be divided into a plurality of values or a plurality of value intervals, where each value or each value interval of the service demand intensity corresponds to the query tag of each level; for example, when the level of the query tag is one of the first level, the second level and the third level, the first level query tag corresponds to the service demand intensity of the first numerical interval, the second level query tag corresponds to the service demand intensity of the second numerical interval, and the third level query tag corresponds to the service demand intensity of the third numerical interval, wherein the first, second and third numerical intervals represent sequentially increasing service demand intensity ranges.

Step S304, when the business requirement intensity corresponding to the query data is smaller than or equal to the business requirement intensity corresponding to the standard data label of the highest level, the query labels of the corresponding levels are associated according to the business requirement intensity corresponding to the query data, and the business requirement intensities respectively corresponding to the query labels of the same level and the standard data labels are matched.

In an exemplary embodiment, when the service demand intensity corresponding to the query data is less than or equal to the service demand intensity corresponding to the standard data label of the highest level, that is, the evaluation value of the service demand intensity corresponding to the query data is less than or equal to the evaluation value of the service demand intensity corresponding to the standard data label, the query data is associated with the label level corresponding to the service demand intensity.

Optionally, when the service demand intensity corresponding to the query data is smaller than or equal to the service demand intensity corresponding to the standard data label of the highest level, and when the highest level of the standard data label is the second level, the service demand intensity corresponding to the query data is lower, and then the query data is associated with the first-level query label; and if the service requirement intensity corresponding to the query data is higher, associating the query data with a secondary query tag.

Step S306, when the service demand intensity corresponding to the query data is greater than the service demand intensity corresponding to the standard data label of the highest level, associating the query label of the corresponding level according to the service demand intensity corresponding to the query data, wherein the level of the query label is greater than the highest level of the standard data label.

Illustratively, when the service requirement intensity corresponding to the query data is greater than the service requirement intensity corresponding to the standard data label of the highest level, and when the highest level of the standard data label is two-level, the query data is associated with the three-level query label, and the query data of the associated three-level query label is converted into manual processing.

In this embodiment, the standard data tag and the level determination standard of the query tag are unified by using the service demand intensity as an index, and the data can be efficiently identified by the standardized tag level.

In an exemplary embodiment, as shown in fig. 4, the method of retrieving corresponding target data within a target level range of standard data tags based on a query tag includes at least one of steps S402 to S404. Wherein:

step S402, based on the level of the query tag, obtaining the standard data tag of the target level, and searching the corresponding target data in the standard data tag of the target level.

Illustratively, when the highest level of the standard data tag is the second level, if the level of the query tag is the first level, corresponding data is retrieved within the range of the first level standard data tag; and if the level of the query tag is two levels, retrieving corresponding data in the range of the two levels of standard data tags.

Step S404, based on the level of the query tag, obtaining standard data tags of the target level, and respectively retrieving corresponding target data in the standard data tags of the corresponding level according to the order of decreasing from the target level step by step.

Illustratively, when the highest level of the standard data tag is the second level, if the level of the query tag is the second level, the corresponding data is retrieved within the range of the second level and the first level standard data tag, respectively, in sequence.

In this embodiment, the search can be performed within the range of the standard data tag of a single level or multiple levels according to different user requirements, so as to adjust the search range and the search precision based on different user requirements.

In one exemplary embodiment, as shown in fig. 5, when the query tag is within the level range of the standard data tag in the target database, corresponding target data is retrieved within the target level range of the standard data tag based on the query tag, including steps S502 to S504. Wherein:

Step S502, according to the number of the query request information and the service demand intensity corresponding to the query label of each query request information, adjusting the pairing relation between each task execution window and each query request information, wherein the task execution window is a window provided for the search behavior based on the query label, and the service response time of the task execution window is reduced according to the increase of the service demand intensity.

The task execution window is a system for planning, coordinating and scheduling resources to execute tasks; the task execution window may be represented as a system for scheduling resources to execute a retrieval task. Service response time refers to the time interval from the request to the receipt of a service response; the service response time may be expressed as the time interval between receipt of query request information by the task execution window and initiation of execution of the retrieval task.

Illustratively, when a plurality of query request information is received simultaneously, the plurality of query request information is respectively allocated to each task execution window to execute different retrieval tasks according to different query request information.

Alternatively, when the number of the query request information is greater than the number of the task execution windows in the idle state, the allocation priority of the query request information may be evaluated according to the service requirement level corresponding to the query request information, for example, the task execution windows may be preferentially allocated to the query request information with higher service requirement strength.

Optionally, the query request information with large correlation can be distributed to the same task execution window for processing; for example, at the same time, the same problem of different users is received, and then the same problem can be distributed in the same task execution window for processing; for another example, a plurality of questions of the same user are received at the same time and are semantically related, and then the questions can be distributed to the same task execution window for processing.

Optionally, the service response time of the task execution window may be evaluated according to the service demand level corresponding to the query request information, for example, after the query request information is allocated to the corresponding task execution window, if it is determined that the service demand level corresponding to the query request information is higher, the task execution window preferentially processes, so as to reduce the service response time.

Step S504, matching corresponding target task execution windows according to the service demand intensity, and searching corresponding target data in the target level range of the standard data labels by the target task execution windows.

Illustratively, after the corresponding task execution window is allocated to the query request information, according to the query tag corresponding to the query request information, the data in the database is searched within the level range of the corresponding standard data tag by the task execution window.

In this embodiment, the task execution window is scheduled according to the number of query request information and the corresponding service demand level, so as to improve the efficiency of multitasking and the efficiency of automatic response service.

In an exemplary embodiment, as shown in fig. 6, each data in the target database has a corresponding standard data tag, where the standard data tag is a tag obtained by sorting data in the power grid service platform, and the method includes steps S602 to S606. Wherein:

step S602, dividing the data of the power grid service platform into one type of data and two types of data according to the data format, wherein the one type of data is conventional data which does not need to be subjected to format conversion processing, and the two types of data are to-be-processed data which needs to be subjected to format conversion processing.

The power grid service platform is a comprehensive platform for monitoring, managing and optimizing the operation of the circuit system; the data of the grid services platform may be represented as power production data, power load data, fault data, historical data, customer data, etc. Format conversion processing refers to the process of converting data from one format or structure to another; the format conversion process may be represented as a process of converting data into a form that can be stored in a database and properly read, processed, and understood.

Step S604, associating one class of data with one class of data tag, and performing format conversion processing on the two classes of data to obtain converted two classes of data.

Step S606, after the class I data and the converted class II data are classified, sequenced and integrated, the class II data are associated with the class II data labels and stored in the target database, wherein the class I data labels and the class II data labels form standard data labels.

Wherein, the classification processing refers to the process of classifying data into different categories or compositions; classification may be based on the content of the data, e.g., based on domain, topic, user, etc. The ordering processing refers to arranging the data according to a specific rule or condition; the data may be processed according to an ascending or descending arrangement. The integration process refers to merging data from different sources into a consistent data set; the integration process may be represented as a process of normalizing data, ensuring data consistency and comparability.

The service demand intensity corresponding to the first-level data tag is smaller than the service demand intensity corresponding to the second-level data tag, and the first-level data tag is associated with the first-level data tag after classification, sorting and integration processing, that is, the first-level data tag and the second-level data tag are simultaneously associated with the first-level data tag and the second-level data tag, so that the first-level data tag and the second-level data tag can be matched with information of the first-level data in two forms respectively, for example, the first-level query tag can be matched with the first-level data in the form corresponding to the first-level data tag, and the first-level data in the form can meet the lower service demand degree corresponding to the first-level query tag.

In this embodiment, the integrity of data transmission is ensured by associating the conventional data with the first-level tag to save the original information of the conventional data in the original form.

In an exemplary embodiment, as shown in fig. 7, when the level of the query tag is greater than the level range of the standard data tag, a communication connection of the terminal corresponding to the current query request information is triggered, and information interaction is performed based on the communication connection, including steps S702 to S704. Wherein:

step S702, according to the number of the inquiry request information and the service demand intensity corresponding to the inquiry label of each inquiry request information, the pairing relation between each information interaction window and the terminal corresponding to each inquiry request information is adjusted, the information interaction window is a window for providing manual service for the user, and the service response time of the information interaction window is reduced according to the increase of the service demand intensity.

The information interaction window is a system for carrying out real-time communication between the manual customer service and the user; real-time communication may be represented as multiple rounds of conversations in the form of real-time text, real-time conversations, etc. Service response time refers to the time interval from the request to the receipt of a service response; the service response time may be expressed as the time interval between receipt of the query request information and the start of establishment of the communication connection by the information interaction window.

Illustratively, when a plurality of inquiry request messages are received simultaneously, the inquiry request messages are respectively distributed to each information interaction window so as to establish communication connection with different terminals according to different inquiry request messages.

Optionally, when the number of the query request information is greater than the number of the information interaction windows in the idle state, the allocation priority of the query request information may be evaluated according to the service requirement level corresponding to the query request information, for example, the information interaction windows may be preferentially allocated to the query request information with higher service requirement strength.

Optionally, the query request information with large correlation can be distributed to the same information interaction window for processing; for example, multiple questions of the same user may be received at the same time and distributed for processing in the same information interaction window.

Optionally, the service response time of the information interaction window may be evaluated according to the service demand level corresponding to the query request information, for example, after the query request information is allocated to the corresponding information interaction window, if it is determined that the service demand level corresponding to the query request information is higher, the information interaction window is preferentially processed, so that the service response time is reduced.

Step S704, matching the corresponding target information interaction window according to the service demand intensity, wherein the target information interaction window is in communication connection with the terminal corresponding to the current query request information.

Illustratively, according to the query tag corresponding to the query request information, the query request information is distributed with a corresponding information interaction window, and a manual customer service provides response service for the user based on the query request information.

In this embodiment, according to the number of the query request information and the corresponding service demand level, the information interaction window is scheduled, so that the efficiency of the manual response service is improved.

In an exemplary embodiment, as shown in fig. 8, step S802 is included before receiving the current query request information, and step S804 is included after receiving the current query request information. Wherein:

step S802, obtaining a target user database corresponding to the target user information according to the target user information corresponding to the historical query request information, and storing user data corresponding to the target user information and power grid service platform data corresponding to the user data in the target user database.

The historical query request information refers to a request sent by a user or a system to a server in a period of time. User information refers to information related to a particular person or entity. A user database refers to a database for managing and maintaining data related to a certain user.

For example, the identification of different users can be realized according to the user information corresponding to the query request information, such as the user identity information, the user account information, and the like; each user corresponds to a user database, and user data corresponding to one user and power grid service platform data corresponding to the user data are stored in the corresponding user database. Wherein the user data focuses on the identity, needs and behavior of the individual or entity for providing personalized services and support; the power grid service platform data focuses on information on electric power and energy sources, and is used for operation and management of an electric power system; the user data is associated with grid service platform data for billing and load management.

Alternatively, the user data may be represented as basic identity information, contact information, financial information, social network information, etc., and the grid service platform data may be represented as electricity usage information, electricity demand information, circuit quality information, etc.

Step S804, according to the current user information corresponding to the current query request information, matching the current user database corresponding to the current user information, and taking the current user database as a target database.

The user is identified according to the user information corresponding to the query request information, so that the user is matched with a user database corresponding to the user, and in the user database, the search action is performed on the user data corresponding to the user and the power grid service platform data corresponding to the user data.

In this embodiment, the user information and the user database of each user are obtained, so that the user data and the power grid service platform data are respectively stored in different user databases, and different personalized response services are provided according to different users.

In an exemplary embodiment, the information response method based on the power grid service platform includes the following steps:

the method is applied to the power grid service platform, wherein the power grid service platform is used for uniformly managing and scheduling information of each link of power generation, power transmission, power distribution and power utilization, and providing monitoring, metering, charging, prediction, guarantee and optimized service for users.

The server collects data of the power grid service platform and data of users in all areas and transmits the data to the database; the data which is collected but not transmitted to the database can be temporarily stored in the data buffer area, so that the data is prevented from being missed in the transmission process. The data of the database at this time includes one type of data requiring no conversion processing and two types of data requiring conversion processing. And associating one class of data with one class of data labels, converting the two classes of data to generate data with the same data format, classifying, sorting and integrating the two classes of data according to different user account information, and respectively storing the data in a user database of a corresponding user, wherein the one class of data and the two classes of data after conversion are associated with two classes of data labels, and the one class of data labels and the two classes of data labels form a standard data label.

When the power grid service platform data and the user data are collected, the power grid data and the user data are compared, the workload and the electric quantity of the power grid and the user are predicted, adjustment is carried out to optimize, and the accuracy of the data of the user is improved.

And the user sends inquiry request information, such as inquiring the current month of electricity and paying fees, to the server through the terminal, and the server associates the inquiry request information with the corresponding inquiry label according to the service demand degree corresponding to the inquiry request information.

If the level of the query tag is within the level range of the standard data tag, the server distributes a corresponding task execution window for the retrieval behavior corresponding to the query request information according to the current user access quantity and the current user access demand, the server matches the user information corresponding to the query request information to a user database corresponding to the user, the task execution window retrieves the corresponding standard data tag in the user database according to the query tag and invokes corresponding data, the data is used as response information and returns to the terminal, and automatic response service is provided for the user.

The method comprises the steps of integrating acquired user data and power grid service platform data according to user account information, establishing a user model, wherein the model data comprise power consumption, cost, power consumption state, prediction data and the like of a user, and automatically responding by applying intelligent analysis and machine learning algorithms and calling corresponding model data according to user access information.

The user model can comprise a semantic training model, the semantic training model carries out semantic training on data in a database, and corresponding answers can be made by applying a natural language processing algorithm and retrieving data with high matching degree according to user access information.

The task execution window can be distributed in real time according to the service demands of users in a cluster environment, the workflow among all nodes is coordinated, and the task execution efficiency and the completion quality are improved.

If the level of the query tag is greater than the highest level of the standard data tag, the server distributes the information interaction window in an idle state for the query request information according to the current access quantity and the current access requirement of the user and the working condition of the information interaction window, and the information interaction window establishes communication connection between the artificial customer service and the terminal to provide the artificial response service for the user.

In addition, the server monitors the power grid service platform data and the user data in real time, timely discovers abnormal conditions in the power system based on information such as power supply load, power grid state and operation parameters, and makes corresponding alarm treatment to a manager or a user; meanwhile, based on historical data and a prediction model, a server predicts future workload, electricity price and power grid state of the power system, and optimizes and adjusts data of abnormal trends.

Moreover, the server analyzes the electricity consumption behavior and trend of the user through an aggregation algorithm, and gives electricity consumption suggestions and an energy-saving optimization scheme to the user so as to reduce the load of the power grid and the electricity consumption cost of the user; meanwhile, the future electricity consumption and electricity consumption state of the user are predicted, and resources are allocated in advance, so that the user requirements can be met in time during peak hours or emergency requirements.

It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.

Based on the same inventive concept, the embodiment of the application also provides an information response device based on the power grid service platform, which is used for realizing the information response method based on the power grid service platform. The implementation scheme of the device for solving the problem is similar to that described in the above method, so the specific limitation in the embodiments of the information response device based on the power grid service platform provided below may be referred to the limitation of the information response method based on the power grid service platform hereinabove, and will not be repeated herein.

In an exemplary embodiment, as shown in fig. 9, there is provided an information response device based on a power grid service platform, including: a receiving module 902, a first answering module 904, and a second answering module 906, wherein:

the receiving module 902 is configured to receive current query request information, perform tag association processing on query data in the current query request information, and obtain a query tag corresponding to the query data, where the query tag is a tag obtained by identifying a service demand intensity corresponding to the query data.

The first response module 904 is configured to, when the query tag is within a level range of a standard data tag in the target database, retrieve corresponding target data within a target level range of the standard data tag based on the query tag, and return the target data to a terminal corresponding to the current query request information; the standard data labels are obtained by classifying and sorting the data in the power grid service platform, and at least comprise labels of a second level, wherein the service demand intensity corresponding to the labels is increased according to the increase of the level of the labels.

And the second response module 906 is configured to trigger a communication connection of the terminal corresponding to the current query request information when the level of the query tag is greater than the level range of the standard data tag, and perform information interaction based on the communication connection.

In one exemplary embodiment, the receiving module 902 includes an associated query tag unit, a first query tag association unit, and a second query tag association unit. Wherein:

and the associated query tag unit is used for associating query tags of different levels according to the service demand intensity corresponding to the query data, wherein the query tags comprise tags of at least three candidate levels, and the service demand intensity corresponding to the tags is increased according to the increase of the levels of the tags.

The first query tag association module is used for associating the query tag of the corresponding level according to the service demand intensity corresponding to the query data when the service demand intensity corresponding to the query data is smaller than or equal to the service demand intensity corresponding to the standard data tag of the highest level, and the query tag of the same level and the standard data tag respectively correspond to the service demand intensity and are matched.

And the second query tag association module is used for associating the query tag of the corresponding level according to the service demand intensity corresponding to the query data when the service demand intensity corresponding to the query data is greater than the service demand intensity corresponding to the standard data tag of the highest level, and the level of the query tag is greater than the highest level of the standard data tag.

In one exemplary embodiment, the first response module 904 includes at least one of a first retrieval unit and a second retrieval unit. Wherein:

the first retrieval unit is used for acquiring the standard data label of the target level based on the level of the query label, and retrieving corresponding target data in the standard data label of the target level.

And the second retrieval unit is used for acquiring standard data labels of the target level based on the level of the query label, and respectively retrieving corresponding target data in the standard data labels of the corresponding level according to the order of gradually decreasing the target level.

In one exemplary embodiment, the first response module 904 includes a task window scheduling unit and a task window execution unit. Wherein:

the task window scheduling unit is used for adjusting the pairing relation between each task execution window and each query request information according to the quantity of the query request information and the service demand intensity corresponding to the query label of each query request information, wherein the task execution window is a window provided for the search behavior based on the query label, and the service response time of the task execution window is reduced according to the increase of the service demand intensity.

The task window execution unit is used for matching a corresponding target task execution window according to the service demand intensity, and the target task execution window retrieves corresponding target data in a target level range of the standard data label.

In one exemplary embodiment, the first response module 904 includes a data classification unit, a first data tag association unit, and a second data tag association unit. Wherein:

the data classification unit is used for classifying the data of the power grid service platform into one type of data and two types of data according to the data format, wherein the one type of data is conventional data which does not need to be subjected to format conversion processing, and the two types of data are to-be-processed data which needs to be subjected to format conversion processing.

The first data tag association unit is used for associating one class of data with one class of data tag, and performing format conversion processing on the two classes of data to obtain converted two classes of data.

The second data tag association unit is used for carrying out classification, sequencing and integration processing on the first class data and the converted second class data, associating the second class data tags and storing the second class data tags in the target database, wherein the first class data tags and the second class data tags form standard data tags.

In one exemplary embodiment, the second answer module 906 includes an interactive window scheduling unit and an interactive window execution unit. Wherein:

The interactive window scheduling unit is used for adjusting the pairing relation between each information interactive window and the terminal corresponding to each query request information according to the quantity of the query request information and the service demand intensity corresponding to the query label of each query request information, wherein the information interactive window is a window for providing manual service for a user, and the service response time of the information interactive window is reduced according to the increase of the service demand intensity.

And the interactive window execution unit is used for matching a corresponding target information interactive window according to the service demand intensity, and the target information interactive window is in communication connection with a terminal corresponding to the current query request information.

In an exemplary embodiment, the apparatus further comprises obtaining a user database unit and matching user database units. Wherein:

and the user database obtaining unit is used for obtaining a target user database corresponding to the target user information according to the target user information corresponding to the historical query request information, and storing the user data corresponding to the target user information and the power grid service platform data corresponding to the user data in the target user database.

And the matching user database unit is used for matching the current user database corresponding to the current user information according to the current user information corresponding to the current query request information, and taking the current user database as a target database.

The modules in the information response device based on the power grid service platform can be all or partially realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In an exemplary embodiment, a computer device is provided, which may be a server, and the internal structure thereof may be as shown in fig. 10. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing power grid service platform data and user data. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program, when executed by the processor, implements an information response method based on a grid service platform.

It will be appreciated by those skilled in the art that the architecture shown in fig. 10 is merely a block diagram of some of the architecture relevant to the present application and is not intended to limit the computer device to which the present application may be applied, and that a particular computer device may include more or less components than those shown, or may combine some of the components, or have a different arrangement of components.

In one exemplary embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:

receiving current query request information, performing label association processing on query data in the current query request information to obtain a query label corresponding to the query data, wherein the query label is a label obtained after identifying the service demand intensity corresponding to the query data;

when the query tag is in the level range of the standard data tag in the target database, searching corresponding target data in the target level range of the standard data tag based on the query tag, and returning the target data to the terminal corresponding to the current query request information; the standard data labels are obtained by classifying and sorting the data in the power grid service platform, and at least comprise labels of a second level, wherein the service demand intensity corresponding to the labels is increased according to the increase of the level of the labels;

When the level of the query tag is greater than the level range of the standard data tag, triggering communication connection of the terminal corresponding to the current query request information, and performing information interaction based on the communication connection.

In one embodiment, when the processor executes the computer program, the step of performing tag association processing on query data in the current query request information to obtain a query tag corresponding to the query data includes the following steps: according to the service demand intensity corresponding to the query data, associating query tags of different levels, wherein the query tags comprise at least three candidate level tags, and the service demand intensity corresponding to the tags is increased according to the increase of the level of the tags; when the service demand intensity corresponding to the query data is smaller than or equal to the service demand intensity corresponding to the standard data label of the highest level, the query labels of the corresponding levels are associated according to the service demand intensity corresponding to the query data, and the service demand intensities respectively corresponding to the query labels of the same level and the standard data labels are matched; when the service demand intensity corresponding to the query data is greater than the service demand intensity corresponding to the standard data label of the highest level, the query label of the corresponding level is associated according to the service demand intensity corresponding to the query data, and the level of the query label is greater than the highest level of the standard data label.

In one embodiment, the steps of a method for retrieving corresponding target data within a target level range of standard data tags based on a query tag when a computer program is executed by a processor, include at least one of the following steps: based on the level of the query tag, acquiring a standard data tag of a target level, and searching corresponding target data in the standard data tag of the target level; and acquiring standard data labels of the target level based on the level of the query label, and respectively searching corresponding target data in the standard data labels of the corresponding level according to the order of gradually decreasing the target level.

In one embodiment, when the processor executes the computer program, when the query tag is within the level range of the standard data tag in the target database, the step of retrieving corresponding target data within the target level range of the standard data tag based on the query tag, comprises the steps of: according to the quantity of the query request information and the business demand intensity corresponding to the query tags of each query request information, the pairing relation between each task execution window and each query request information is adjusted, wherein the task execution window is a window provided for the search behavior based on the query tags, and the service response time of the task execution window is reduced according to the increase of the business demand intensity; and matching corresponding target task execution windows according to the service demand intensity, and searching corresponding target data within a target level range of the standard data tag by the target task execution windows.

In one embodiment, when the processor executes the computer program, each data in the target database has a corresponding standard data tag, where the standard data tag is a tag obtained by sorting data in the power grid service platform, and the method includes the following steps: dividing the data of the power grid service platform into one type of data and two types of data according to the data format, wherein the one type of data is conventional data which does not need to be subjected to format conversion processing, and the two types of data are to-be-processed data which needs to be subjected to format conversion processing; associating one class of data with one class of data tag, and carrying out format conversion processing on the two classes of data to obtain converted two classes of data; and after the class-one data and the converted class-two data are classified, sequenced and integrated, associating the class-two data with the class-two data, and storing the class-two data in a target database, wherein the class-one data label and the class-two data label form a standard data label.

In one embodiment, when the processor executes the computer program and the level of the query tag is greater than the level range of the standard data tag, the step of triggering the communication connection of the terminal corresponding to the current query request information and performing information interaction based on the communication connection includes the following steps: according to the quantity of the query request information and the service demand intensity corresponding to the query label of each query request information, the pairing relation between each information interaction window and the terminal corresponding to each query request information is adjusted, the information interaction window is a window for providing manual service for a user, and the service response time of the information interaction window is reduced according to the increase of the service demand intensity; and matching a corresponding target information interaction window according to the service demand intensity, wherein the target information interaction window is in communication connection with a terminal corresponding to the current query request information.

In one embodiment, the steps preceding the receipt of the current query request information when the processor executes the computer program include the steps of: and obtaining a target user database corresponding to the target user information according to the target user information corresponding to the historical query request information, and storing user data corresponding to the target user information and power grid service platform data corresponding to the user data in the target user database. The steps before receiving the current query request information comprise the following steps: and matching a current user database corresponding to the current user information according to the current user information corresponding to the current query request information, and taking the current user database as a target database.

In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored which, when executed by a processor, carries out the steps of the method embodiments described above.

It should be noted that, the user information (including, but not limited to, user equipment information, user personal information, etc.) and the data (including, but not limited to, data for analysis, stored data, presented data, etc.) referred to in the present application are information and data authorized by the user or sufficiently authorized by each party, and the collection, use, and processing of the related data are required to meet the related regulations.

Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in the various embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the various embodiments provided herein may include at least one of relational databases and non-relational databases. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processors referred to in the embodiments provided herein may be general purpose processors, central processing units, graphics processors, digital signal processors, programmable logic units, quantum computing-based data processing logic units, etc., without being limited thereto.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The above examples only represent a few embodiments of the present application, which are described in more detail and are not to be construed as limiting the scope of the present application. It should be noted that it would be apparent to those skilled in the art that various modifications and improvements could be made without departing from the spirit of the present application, which would be within the scope of the present application. Accordingly, the scope of protection of the present application shall be subject to the appended claims.

Claims

1. An information response method based on a power grid service platform is characterized by comprising the following steps:

2. The method of claim 1, wherein the performing tag association processing on the query data in the current query request information to obtain a query tag corresponding to the query data includes:

3. The method of claim 1, wherein the method of retrieving corresponding target data within a target level range of the standard data tag based on the query tag comprises at least one of:

4. The method of claim 1, wherein when the query tag is within a level range of a standard data tag in a target database, retrieving corresponding target data within the target level range of the standard data tag based on the query tag comprises:

5. The method according to claim 1, wherein each data in the target database has a corresponding standard data tag, and the standard data tag is a tag obtained by sorting data in a power grid service platform, and comprises:

6. The method according to claim 1, wherein when the level of the query tag is greater than the level range of the standard data tag, triggering a communication connection of the terminal corresponding to the current query request information, and performing information interaction based on the communication connection, includes:

7. The method of claim 1, wherein prior to receiving the current query request information, comprising:

8. An information response device based on a power grid service platform, which is characterized by comprising:

the receiving module is used for receiving current query request information, carrying out label association processing on query data in the current query request information to obtain a query label corresponding to the query data, wherein the query label is a label obtained by identifying the service demand intensity corresponding to the query data;

9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 7 when the computer program is executed.

10. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 7.