Query result determination method and device, storage medium and electronic equipment

Abstract

The invention discloses a query result determination method and device, a storage medium and electronic equipment, and the method comprises the steps: determining a first query result based on a first query request of a target user; determining whether the target system comprises first correction data associated with the first query request or not based on the first query result, wherein the first correction data is determined based on a first correction request sent by the target user; under the condition that the target system comprises the first correction data, correcting the first query result according to the first correction data to obtain a target query result; and sending the target query result to the target user. By means of the method and device, the problem that the query result fed back to the user is inaccurate is solved, and then the effect of accurately feeding back the query result is achieved.

Description

Technical Field

[0001] This application relates to the field of computers, and more specifically, to a method, apparatus, storage medium, and electronic device for determining query results. Background Technology

[0002] In related technologies, the performance of clustering technology is highly dependent on data quality and scenario characteristics, and problems such as misclustering and diffusion generally exist. When users or systems modify or correct data, the traditional approach is to directly send the user request to the backend. However, the data correction process involves merging multiple types of data into the same type due to diffusion and splitting the same type of data into multiple types due to misclustering. This process involves a large number of feature recalculations, which is often slow and cannot provide timely feedback to users.

[0003] This indicates that there is a technical problem in the relevant technology that results inaccurate queries returned to users.

[0004] There is currently no effective solution to the aforementioned problems in the relevant technologies. Summary of the Invention

[0005] This application provides a method, apparatus, storage medium, and electronic device for determining query results, so as to at least solve the technical problem of inaccurate query results fed back to users in related technologies.

[0006] According to one aspect of the embodiments of this application, a method for determining a query result is provided, comprising: determining a first query result based on a first query request from a target user; determining, based on the first query result, whether a target system includes first correction data associated with the first query request, wherein the first correction data is determined based on the first correction request sent by the target user; if the target system includes the first correction data, correcting the first query result according to the first correction data to obtain a target query result; and sending the target query result to the target user.

[0007] In one exemplary embodiment, modifying the first query result according to the first modification data to obtain a target query result includes: determining a first modification instruction included in the first modification data; and modifying the first query result based on the first modification instruction to obtain the target query result.

[0008] In an exemplary embodiment, correcting the first query result based on the first correction instruction to obtain the target query result includes: determining whether the returned data included in the first query result is the same as the first data to be corrected indicated by the first correction instruction; if the returned data is the same as the first data to be corrected and the first correction instruction indicates a merge operation, merging the data included in the returned data according to the merge operation to obtain the target query result; if the returned data is the same as the first data to be corrected and the first correction instruction indicates a split operation, splitting the data included in the returned data according to the split operation to obtain the target query result; and if the returned data is not the same as the first data to be corrected, determining the returned data as the target query result.

[0009] In an exemplary embodiment, before determining the first query result based on the first query request of the target user, the method further includes: receiving the first correction request sent by the target user; determining the first data to be corrected included in the first correction request; determining the first correction instruction corresponding to the first data to be corrected based on the first data to be corrected; determining the first preset period of the first correction instruction based on the priority of the first data to be corrected, wherein the first preset period is used to indicate the expiration time of the first correction instruction; and determining the first correction instruction and the first preset period as the first correction data.

[0010] In one exemplary embodiment, after receiving the first correction request sent by the target user, the method further includes: sending the first correction data to the target system to instruct the target system to store the first correction data; and sending the first correction data to a clustering system to instruct the clustering system to correct the data associated with the first correction data stored in the clustering system according to the first correction data.

[0011] According to another aspect of the embodiments of this application, a method for determining a query result is provided, comprising: receiving a second query request sent by a query system, the second query request being determined based on a first query request sent by a target user; determining a first query result corresponding to the second query request based on the second query request; sending the first query result to the query system to instruct the query system to determine whether a target system includes first correction data associated with the first query request based on the first query result; and, if the target system includes the first correction data, correcting the first query result according to the first correction data to obtain a target query result, and sending the target query result to the target user, wherein the first correction data is determined based on a first correction request sent by the target user.

[0012] In one exemplary embodiment, the method further includes: determining correction data; and correcting stored data associated with the correction data according to the correction data.

[0013] In one exemplary embodiment, determining the correction data includes one of the following: receiving second correction data sent by the query system, determining the second correction data as the correction data, wherein the second correction data includes the first correction data; receiving a second correction request sent by the target user, determining second data to be corrected included in the second correction request, determining a second correction instruction corresponding to the second data to be corrected based on the second data to be corrected, determining a second preset period of the second correction instruction based on the priority of the second data to be corrected, wherein the second preset period is used to indicate the expiration time of the second correction instruction, determining the second correction instruction and the second preset period as third correction data, and determining the third correction data as the correction data.

[0014] In one exemplary embodiment, after determining the second corrected data as the corrected data, the method further includes: sending the second corrected data to the target system to instruct the target system to store the second corrected data.

[0015] In one exemplary embodiment, after correcting the stored data associated with the correction data according to the correction data, the method further includes: if the correction of the stored data associated with the correction data is completed within a third preset period, sending a first deletion instruction to the target system to instruct the target system to delete the correction data from the target system based on the first deletion instruction; if the correction of the stored data associated with the correction data is not completed within the third preset period, sending a second deletion instruction to the target system to instruct the target system to delete the correction data from the target system based on the second deletion instruction.

[0016] According to another aspect of the embodiments of this application, a query result determination apparatus is also provided, comprising: a first determination module, configured to determine a first query result based on a first query request from a target user; a second determination module, configured to determine whether a target system includes first correction data associated with the first query request based on the first query result, wherein the first correction data is determined based on the first correction request sent by the target user; a correction module, configured to correct the first query result according to the first correction data if the target system includes the first correction data, thereby obtaining a target query result; and a first sending module, configured to send the target query result to the target user.

[0017] According to another aspect of the embodiments of this application, a query result determination apparatus is also provided, comprising: a receiving module, configured to receive a second query request sent by a query system, the second query request being determined based on a first query request sent by a target user; a third determining module, configured to determine a first query result corresponding to the second query request based on the second query request; and a second sending module, configured to send the first query result to the query system to instruct the query system to determine whether the target system includes first correction data associated with the first query request based on the first query result, and, if the target system includes the first correction data, to correct the first query result according to the first correction data to obtain a target query result, and to send the target query result to the target user, wherein the first correction data is determined based on the first correction request sent by the target user.

[0018] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored therein, wherein the computer program is configured to perform the steps in any of the above method embodiments when executed by a processor.

[0019] According to another aspect of the embodiments of this application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, causing the computer device to perform the steps in any of the method embodiments described above.

[0020] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to perform the steps of any of the above method embodiments through the computer program.

[0021] This application allows for the retrieval of a first query result from a clustering system based on a target user's first query request. The returned first query result determines whether the target system includes first corrected data associated with the first query result. This first corrected data is determined based on the target user's first corrected request. If the target system includes the first corrected data, it indicates that the target user has initiated a corrected request. Therefore, the first query result retrieved from the clustering system can be corrected according to the first corrected data in the target system, resulting in a corrected target query result that is then sent to the target user. Since the target system can cache the real-time modified first corrected data, it automatically identifies whether the query content (i.e., the first query result) involves the first corrected data during the target user's query. If the first corrected data exists, the first query result returned from the backend and the cached first corrected data can be integrated. This means that each query requires a comparison to see if the returned result (first query result) contains the first corrected data, and the first corrected data residing in the target system ensures a sub-millisecond response time. Therefore, this solves the problem of inaccurate query results returned to the user in related technologies, achieving accurate query result feedback. Attached Figure Description

[0022] Figure 1 This is a schematic diagram illustrating an application scenario of a method for determining query results according to an embodiment of this application;

[0023] Figure 2 This is a flowchart illustrating an optional method for determining query results according to an embodiment of this application. Figure 1 ;

[0024] Figure 3 This is a flowchart illustrating the real-time display of the corrected results according to an embodiment of this application;

[0025] Figure 4 This is a flowchart illustrating a user-initiated data correction process according to an embodiment of this application.

[0026] Figure 5 This is a flowchart illustrating an optional method for determining query results according to an embodiment of this application. Figure 2 ;

[0027] Figure 6 This is a flowchart illustrating the data correction process performed by the backend clustering system according to an embodiment of this application.

[0028] Figure 7 This is a module interaction diagram of the method for determining the query results based on the optional examples in this application;

[0029] Figure 8 This is a structural block diagram of an optional query result determination device according to an embodiment of this application. Figure 1 ;

[0030] Figure 9 This is a structural block diagram of an optional query result determination device according to an embodiment of this application. Figure 2 ;

[0031] Figure 10 This is a computer system architecture block diagram of an optional electronic device according to an embodiment of this application. Detailed Implementation

[0032] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0033] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0034] The technical terms appearing in this application are explained below:

[0035] Real-time processing: Data is processed immediately after it is generated, with millisecond-level response, emphasizing low latency.

[0036] Offline processing: Batch computation of static datasets, usually scheduled by day / hour, focusing on high throughput.

[0037] Stream-Batch Integration: A technology that uses the same system to process real-time streaming data and offline batch data simultaneously, unifying the development interface and computing engine, balancing low latency and high throughput, and eliminating the complexity and inconsistency of traditional architectures.

[0038] Real-time updates: Data can be queried or used immediately after being updated, typically requiring a millisecond-level response time.

[0039] Diffusion: This refers to the aggregation of multiple images of a target into different categories, resulting in the formation of multiple categories of data, which is called diffusion.

[0040] According to one aspect of the embodiments of this application, a method for determining query results is provided. Optionally, in this embodiment, the above-described method for determining query results may be applied, but is not limited to, to applications such as... Figure 1 The hardware environment shown includes terminal device 102 and server 104. Server 104 can be connected to terminal device 102 via a network and can be used to provide services (e.g., application services, etc.) to terminal device 102 or clients installed on terminal device 102. A database can be set up on server 104 or independently of server 104 to provide data storage services for server 104.

[0041] The aforementioned network may include, but is not limited to, at least one of the following: wired network and wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: wide area network (WAN), metropolitan area network (MAN), and local area network (LAN). The aforementioned wireless network may include, but is not limited to, at least one of the following: Wireless Fidelity (WIFI) and Bluetooth. Terminal device 102 may be, but is not limited to, a personal computer (PC), mobile phone, tablet computer, etc. Server 104 may be, but is not limited to, a cloud server, server cluster, or other server types.

[0042] The query result determination method of this application embodiment can be executed by server 104, terminal device 102, or jointly by server 104 and terminal device 102. Alternatively, the query result determination method of this application embodiment executed by terminal device 102 can also be executed by a client installed on it.

[0043] This embodiment provides a method for determining query results. Figure 2 This is a flowchart illustrating an optional method for determining query results according to an embodiment of this application. Figure 1 ,like Figure 2 As shown, the process of this method may include the following steps:

[0044] Step S202: Determine the first query result based on the first query request of the target user;

[0045] The query result determination method in this embodiment can be applied to the field of image clustering, specifically to scenarios where, after a clustering system or user identifies an incorrect cluster or classification, the corrected data can be immediately made visible in subsequent query results.

[0046] In the above embodiments, image clustering, as a core method of unsupervised learning, has always revolved around data processing models, forming two main directions: batch clustering and real-time clustering. This is primarily driven by data scale, timeliness requirements, and the evolution of computing frameworks. Batch clustering typically involves feeding a batch of images, accumulated over a certain period, into the clustering system at once. Then, methods such as K-Means, hierarchical clustering, or deep embedding clustering can be used to classify the images into different categories. Real-time clustering, on the other hand, processes the received images in real time, performing image parsing, target extraction, and clustering result comparison. Ultimately, it classifies the images into different categories in real time, and each category can then construct its own retrieval structure and provide retrieval capabilities. Because the performance of current clustering technologies (e.g., accuracy, recall, or diffusion) is highly dependent on data quality and scenario characteristics, problems such as mis-clustering and diffusion are common. Therefore, when mis-clustering, diffusion, or missed clustering is detected, users usually manually correct it. Although manual correction is often highly feasible and can directly correct the data in the system, when receiving correction requests from users, related technologies usually send the correction requests directly to the backend. Due to the large amount of recalculation involved in data splitting or merging, this process takes a lot of time and cannot provide timely feedback to users, resulting in users not immediately perceiving a response to their correction requests.

[0047] To at least partially solve the above-mentioned technical problems, in this embodiment, a third-party memory caching component can be used to cache the real-time modified correction data. When the user queries again, the current returned result can be directly corrected using the historical modifications. That is, the data returned by the backend can be integrated with the cached real-time correction data, thereby achieving the goal of real-time effect of the changed data. Users can immediately feel that the correction request has taken effect, improving the interactive experience between users and the user. This allows the operation commands issued by the user on the page that take effect slowly to be presented to the user immediately. Figure 3 This is a flowchart illustrating the real-time display of the corrected results according to an embodiment of this application, such as... Figure 3 As shown, the process includes the following steps:

[0048] Step S302, user query;

[0049] Step S304: Query the backend clustering system;

[0050] Step S306: Query the third-party caching system;

[0051] Step S308: Determine whether there is corrected data. If yes, proceed to step S310; otherwise, proceed to step S312.

[0052] Step S310: Data merging processing;

[0053] Step S312: Directly return the query results from the backend clustering system;

[0054] Step S314: Return the merged result.

[0055] In the above embodiments, the target user can perform a query on the front-end page, inputting query conditions (i.e., sending a first query request), such as data ID, keywords, or other related data identifiers. After receiving the target user's first query request, the query system can send a second query request to the back-end clustering system to obtain the currently stored clustering results (i.e., the aforementioned first query result). The back-end clustering system can return data information related to the category based on the second query request, which may include data ID, data features, clustering status, etc.

[0056] Step S204: Based on the first query result, determine whether the target system includes first correction data associated with the first query request, wherein the first correction data is determined based on the first correction request sent by the target user;

[0057] In the above embodiments, see again Figure 3After receiving the first query result from the backend clustering system, the query system does not directly return the first query result. Instead, it further queries the target system based on key information such as the data ID included in the returned first query result to determine whether there is real-time corrected data (i.e., the aforementioned first corrected data) related to the first query request. By leveraging the fast response characteristics of third-party caching, it can immediately determine whether there is updated or corrected first corrected data that needs to be merged into the first query result. The first corrected data is determined by the first correction request sent by the target user within a historical timeframe. The target system can be a third-party memory caching component, such as Redis or Zookeeper. Redis can be understood as an open-source, high-performance key-value store system, often used as a database, cache, and message broker. It can store data in memory, providing fast data access and supporting various data structures such as strings, hashes, lists, sets, and sorted sets. Zookeeper can be understood as a distributed coordination service that provides a simple and unified API.

[0058] Step S206: If the target system includes the first correction data, the first query result is corrected according to the first correction data to obtain the target query result;

[0059] In the above embodiments, see again Figure 3 If the corresponding information is found, that is, if the corresponding first correction data is found in the target system, the query system can correct the first query result according to the first correction data. That is, the first query result can be adjusted according to the instructions of the first correction data. For example, if the instruction of the first correction data is that A and B are incorrectly clustered into different categories of data and should be merged into A, and if both A and B exist in the first query result, then B will not be returned as an independent category of data. Instead, A and B will be merged, and the corresponding data of B will be merged into A and returned. That is, the corrected target query result can be obtained.

[0060] Step S208: Send the target query result to the target user.

[0061] In the above embodiments, see again Figure 3 If the corresponding first correction data is found in the target system, the first query result can be corrected according to the first correction data, and the corrected target query result can be sent to the target user. If the corresponding first correction data is not found in the target system, it can be indicated that the data corresponding to the first query request has not been corrected or has been corrected. In this case, the first query result obtained from the clustering system can be directly determined as the target query result and sent to the target user.

[0062] This application allows for the retrieval of a first query result from a clustering system based on a target user's first query request. The returned first query result determines whether the target system includes first corrected data associated with the first query result. This first corrected data is determined based on the target user's first corrected request. If the target system includes the first corrected data, it indicates that the target user has initiated a corrected request. Therefore, the first query result retrieved from the clustering system can be corrected according to the first corrected data in the target system, resulting in a corrected target query result that is then sent to the target user. Since the target system can cache the real-time modified first corrected data, it automatically identifies whether the query content (i.e., the first query result) involves the first corrected data during the target user's query. If the first corrected data exists, the first query result returned from the backend and the cached first corrected data can be integrated. This means that each query requires a comparison to see if the returned result (first query result) contains the first corrected data, and the first corrected data residing in the target system ensures a sub-millisecond response time. Therefore, this solves the problem of inaccurate query results returned to the user in related technologies, achieving accurate query result feedback.

[0063] Optionally, the entity performing the above steps may be a query system or other devices with similar processing capabilities, but is not limited to these.

[0064] In one exemplary embodiment, modifying the first query result according to the first modification data to obtain a target query result includes: determining a first modification instruction included in the first modification data; and modifying the first query result based on the first modification instruction to obtain the target query result.

[0065] In the above embodiments, after the query system obtains the first correction data related to the first query result from the target system, it can extract the first correction instruction from the first correction data. The first correction instruction may include a specific operation type (e.g., merge: merging data from different categories that are incorrectly clustered, or splitting: splitting data that is incorrectly clustered into the same category into multiple independent categories), the data ID involved, new attribute values, or other parameters related to the correction operation. The query system can then correct the first query result obtained from the backend clustering system according to the instructions of the first correction instruction, thus obtaining the target query result. The target query result reflects the latest state of the data in the clustering system and also embodies the user's correction intent. For example, if the first correction instruction indicates that two categories of data need to be merged, the query system will check whether both categories of data appear simultaneously in the first query result. If so, the query system will merge the information of the two categories of data and only display the merged category data in the target query result, ignoring the information of the merged category data.

[0066] This embodiment effectively utilizes real-time corrected data from a third-party cache. User data correction requests can be reflected in the query results within milliseconds, significantly improving the system's real-time response capability and ensuring the immediate visibility of data updates. Furthermore, even if data updates in the backend persistent storage are incomplete, the query system can provide accurate query feedback through the corrected data in the third-party cache, reducing the risk of data inconsistency and enhancing the overall robustness and stability of the system. Moreover, the introduction of the third-party caching component not only accelerates the query process but also alleviates the real-time update pressure on backend data storage, enabling a dual-storage engine: original data and corrected data are stored in parallel, and data merging is achieved through the query system, effectively improving resource utilization and load balancing capabilities.

[0067] In an exemplary embodiment, correcting the first query result based on the first correction instruction to obtain the target query result includes: determining whether the returned data included in the first query result is the same as the first data to be corrected indicated by the first correction instruction; if the returned data is the same as the first data to be corrected and the first correction instruction indicates a merge operation, merging the data included in the returned data according to the merge operation to obtain the target query result; if the returned data is the same as the first data to be corrected and the first correction instruction indicates a split operation, splitting the data included in the returned data according to the split operation to obtain the target query result; and if the returned data is not the same as the first data to be corrected, determining the returned data as the target query result.

[0068] In the above embodiments, the returned data included in the first query result and the first data to be corrected indicated by the first correction instruction will affect the first correction instruction to correct the first query result to varying degrees. Therefore, it can be determined whether the returned result and the first data to be corrected match before correction.

[0069] In the above embodiments, if the returned data matches (i.e., is the same) the first data to be corrected, and the first correction instruction indicates a merge operation, the query system will immediately execute the merge according to the merge operation. For example, if the returned data includes A and B, and the first correction instruction is for A and B to be incorrectly clustered into different categories, and A is merged (i.e., the first data to be corrected is A and B and it is a merge operation), then the corresponding data of B can be merged into A to obtain the target query result.

[0070] In the above embodiments, if the returned data matches (i.e., is the same) the first data to be corrected, and the first correction instruction indicates a splitting operation, the query system will immediately execute the splitting operation. For example, if the returned data includes A and B, and the first correction instruction is that A and B are incorrectly clustered into the same type of data, and B should be split (i.e., the first data to be corrected is A and B and it is a splitting operation), then A and B can be split, and A can be sent to the target user as the target query result.

[0071] In the above embodiments, if the returned data does not match (i.e. is different) the first data to be corrected, it can be understood that the correction instruction is not applicable to the current query result. In this case, the first query result returned directly can be used as the target query result, avoiding unnecessary data processing or modification and ensuring the accuracy of the query result and the consistency with the original state.

[0072] This embodiment not only provides real-time data correction and display capabilities but also ensures the accuracy of query results and the robustness of the system. Through precise comparison of data states and targeted execution of correction commands, various correction scenarios can be intelligently handled. Whether it's data merging or splitting, it's immediately reflected in the user's query, greatly improving user experience and data processing efficiency. Simultaneously, by differentiating the matching between the data to be corrected and the actual returned data, invalid correction operations can be avoided, reducing system load and ensuring data integrity and consistency.

[0073] In an exemplary embodiment, before determining the first query result based on the first query request of the target user, the method further includes: receiving the first correction request sent by the target user; determining the first data to be corrected included in the first correction request; determining the first correction instruction corresponding to the first data to be corrected based on the first data to be corrected; determining the first preset period of the first correction instruction based on the priority of the first data to be corrected, wherein the first preset period is used to indicate the expiration time of the first correction instruction; and determining the first correction instruction and the first preset period as the first correction data.

[0074] In the above embodiments, a first correction request may also be initiated before the user initiates the first query request. Figure 4 This is a flowchart illustrating the user-initiated data correction process according to an embodiment of this application, such as... Figure 4 As shown, the process includes the following steps:

[0075] Step S402: The user corrects the data in real time;

[0076] Step S404: Perform a validity check. If yes, proceed to step S406; otherwise, proceed to step S408.

[0077] Step S406: Write to a third-party caching system;

[0078] Step S408 failed;

[0079] Step S410: Send to the backend clustering system.

[0080] In the above embodiments, if a user discovers data incorrectly clustered into different categories or incorrectly clustered into the same category through the search page, requiring a merging or splitting operation, they can select the data to be operated on and send a first correction request. Upon receiving the first correction request, the query system can first perform data validity and operability checks. If the user-initiated first data to be corrected exists and the checks pass, the operation to write it to the target system can proceed. If the first data to be corrected does not exist or the checks fail, the operation returns a failure message, and the user can check the specific reason based on the failure message.

[0081] In the above embodiments, after the verification is passed, the query system can calculate the first correction instruction corresponding to the first data to be corrected based on the correction logic for different errors included in the system. For example, if data that has been incorrectly clustered into different categories and thus needs to be merged, the merged data and the retained data can be calculated. That is, if multiple data belonging to the same category are divided into different categories of data, it can be calculated which data among the data that needs to be merged is the retained master data (i.e., the retained data) and which data will be merged into the master data (i.e., the merged data).

[0082] In the above embodiments, to facilitate effective management and processing of correction requests, the lifecycle of the correction data (i.e., the aforementioned first preset period) can be defined according to different priorities or correction benefits. For example, the first preset period for high-priority or high-benefit data to be corrected will be shorter, allowing the clustering system to prioritize its processing. If the backend system fails to process the correction instruction within the preset period, the instruction will be considered expired and automatically deleted from the third-party cache to avoid consuming excessive memory resources or generating unnecessary data conflicts.

[0083] In this embodiment, user correction requests can be reflected in the query results almost immediately, even if there is a delay in backend data updates. Meanwhile, the priority and preset period settings ensure that correction commands are processed on demand without indefinitely consuming system resources, thus contributing to the stability and efficient operation of the system.

[0084] In one exemplary embodiment, after receiving the first correction request sent by the target user, the method further includes: sending the first correction data to the target system to instruct the target system to store the first correction data; and sending the first correction data to a clustering system to instruct the clustering system to correct the data associated with the first correction data stored in the clustering system according to the first correction data.

[0085] In the above embodiments, see again Figure 4 The first corrected data, obtained through logical calculation, can be written to the target system according to a format supported by the target system, instructing the target system to cache the first corrected data. Subsequently, the first corrected data can be sent to the clustering system, and event notification mechanisms such as Kafka and ZooKeeper can be used to instruct the clustering system to modify the stored data related to the first corrected data according to the first corrected data. Kafka can provide a publish-subscribe message queue service; when data correction occurs, the corrected data or instructions can be published as an event to a Kafka topic.

[0086] In this embodiment, data correction operations can trigger event notifications. After receiving the notification, the clustering system can modify the stored data according to the corrected data. Moreover, the clustering system only recalculates the clustering data affected by the correction, thus avoiding full reconstruction.

[0087] This embodiment provides another method for determining query results. Figure 5 This is a flowchart illustrating an optional method for determining query results according to an embodiment of this application. Figure 2 ,like Figure 5 As shown, the process of this method may include the following steps:

[0088] Step S502: Receive a second query request sent by the query system, wherein the second query request is determined based on the first query request sent by the target user;

[0089] The query result determination method in this embodiment can be applied to the field of image clustering, specifically to scenarios where, after a clustering system or user identifies an incorrect cluster or classification, the corrected data can be immediately made visible in subsequent query results.

[0090] In the above embodiments, image clustering, as a core method of unsupervised learning, has always revolved around data processing models, forming two main directions: batch clustering and real-time clustering. This is primarily driven by data scale, timeliness requirements, and the evolution of computing frameworks. Batch clustering typically involves feeding a batch of images, accumulated over a certain period, into the clustering system at once. Then, methods such as K-Means, hierarchical clustering, or deep embedding clustering can be used to classify the images into different categories. Real-time clustering, on the other hand, processes the received images in real time, performing image parsing, target extraction, and clustering result comparison. Ultimately, it classifies the images into different categories in real time, and each category can then construct its own retrieval structure and provide retrieval capabilities. Because the performance of current clustering technologies (e.g., accuracy, recall, or diffusion) is highly dependent on data quality and scenario characteristics, problems such as mis-clustering and diffusion are common. Therefore, when mis-clustering, diffusion, or missed clustering is detected, users usually manually correct it. Although manual correction is often highly feasible and can directly correct the data in the system, when receiving correction requests from users, related technologies usually send the correction requests directly to the backend. Due to the large amount of recalculation involved in data splitting or merging, this process takes a lot of time and cannot provide timely feedback to users, resulting in users not immediately perceiving a response to their correction requests.

[0091] To at least partially solve the aforementioned technical problems, this embodiment utilizes a third-party memory caching component to cache real-time modified correction data. When a user queries again, the current returned result can be directly corrected using historical modifications. This integrates the data returned from the backend with the cached real-time correction data, achieving real-time effectiveness of the changed data. Users can immediately perceive that the correction request has taken effect, improving the user experience and ensuring that user-submitted commands that take longer to take effect are immediately displayed. (Continue to see...) Figure 3 Target users can perform queries on the front-end page, entering search criteria such as data IDs, keywords, or other relevant data identifiers. Once the query system receives the first query request from the target user, it can send a second query request to the back-end clustering system.

[0092] Step S504: Determine the first query result corresponding to the second query request based on the second query request;

[0093] In the above embodiment, when the backend clustering system receives the second query request, it can query the corresponding results in the stored data according to the second query request and return the first query result to the query system, such as data ID, data features, and clustering status.

[0094] Step S506: The first query result is sent to the query system to instruct the query system to determine whether the target system includes first correction data associated with the first query request based on the first query result, and, if the target system includes the first correction data, to correct the first query result according to the first correction data to obtain the target query result, and to send the target query result to the target user, wherein the first correction data is determined based on the first correction request sent by the target user.

[0095] In the above embodiments, see again Figure 3After retrieving the first query result corresponding to the second query request, the first query result can be sent to the query system. The query system can then determine whether there is first corrected data related to the first query request in the target system based on the first query result. That is, after receiving the first query result returned by the backend clustering system, the query system does not directly return the first query result, but further queries the target system based on key information such as the data ID included in the returned first query result to determine whether there is real-time corrected data (i.e., the aforementioned first corrected data) related to the first query request in the target system. By utilizing the fast response characteristics of third-party caching, it can immediately determine whether there is updated or corrected first corrected data that needs to be merged into the first query result. The first corrected data is determined by the first corrected data requests sent by the target user within a historical timeframe. The target system can be a third-party memory caching component, such as Redis or Zookeeper. Redis can be understood as an open-source, high-performance key-value store system, often used as a database, cache, and message broker. It can store data in memory, providing fast data access and supporting various data structures such as strings, hashes, lists, sets, and sorted sets. Zookeeper can be understood as a distributed coordination service that provides a simple and unified API. If the query system finds the corresponding information, that is, if the corresponding first correction data is found in the target system, the query system can correct the first query result according to the first correction data. That is, the first query result can be adjusted according to the instructions of the first correction data. For example, if the instruction of the first correction data is that A and B are incorrectly clustered into different categories of data and should be merged into A, and if both A and B exist in the first query result, B will not be returned as an independent category of data. Instead, A and B will be merged, and the corresponding data of B will be merged into A and returned. This will give the corrected target query result, which will then be sent to the target user. If the corresponding first correction data is not found in the target system, it indicates that the data corresponding to the first query request has not been corrected or has been corrected. In this case, the first query result obtained from the clustering system can be directly determined as the target query result and sent to the target user.

[0096] This application enables a backend clustering system to receive a second query request from the query system after a target user sends a first query request. The system can then retrieve the corresponding first query result from its own storage and return it to the query system. The system can instruct the query system to determine whether the target system contains first corrected data associated with the first query request. If first corrected data exists, the system can be instructed to correct the first query result according to the first corrected data, thus obtaining the corrected target query result, which is then sent to the target user. Since the target system can cache the real-time modified first corrected data, the system can automatically identify whether the query content (i.e., the first query result) involves the first corrected data during the target user's query. When first corrected data exists, the first query result returned by the backend and the cached first corrected data can be integrated. This means that each query requires a comparison to see if the returned result (first query result) contains the first corrected data, and since the first corrected data resides in the target system, sub-millisecond response times are ensured. Therefore, this solves the problem of inaccurate query results returned to the user in related technologies, achieving accurate query result feedback.

[0097] Optionally, the entity performing the above steps may be a backend clustering system or other devices with similar processing capabilities, but is not limited to these.

[0098] In one exemplary embodiment, the method further includes: determining correction data; and correcting stored data associated with the correction data according to the correction data.

[0099] In the above embodiments, Figure 6 This is a flowchart illustrating the data correction process performed by the backend clustering system according to an embodiment of this application, as follows: Figure 6 As shown, under normal operating conditions, real-time images are parsed and sent to the backend clustering system. The clustering system can classify the real-time images using methods such as K-Means and CluStream for real-time clustering, or it can collect data on a timed and quantitative basis and perform offline clustering using methods such as hierarchical clustering and DBSCAN. Furthermore, when corrected data exists, the clustering system can merge or split stored data related to the corrected data based on the corrected data.

[0100] In this embodiment, the clustering system acts immediately upon receiving a correction request, processing data corrections with a sub-millisecond response time. This means that user-initiated correction operations are reflected in the query results almost instantly. This high-speed response is particularly important for scenarios requiring real-time feedback, such as online monitoring or real-time data analysis, significantly reducing user waiting time and improving the system's real-time interactive performance.

[0101] In one exemplary embodiment, determining the correction data includes one of the following: receiving second correction data sent by the query system, determining the second correction data as the correction data, wherein the second correction data includes the first correction data; receiving a second correction request sent by the target user, determining second data to be corrected included in the second correction request, determining a second correction instruction corresponding to the second data to be corrected based on the second data to be corrected, determining a second preset period of the second correction instruction based on the priority of the second data to be corrected, wherein the second preset period is used to indicate the expiration time of the second correction instruction, determining the second correction instruction and the second preset period as third correction data, and determining the third correction data as the correction data.

[0102] In the above embodiments, the clustering system itself can also add a data correction branch to determine whether a merging or splitting action is needed. That is, the correction data of the clustering system can come from two sources: the second correction data sent by the query system, which includes the first correction data, and the correction data determined by receiving the second correction request sent by the target user.

[0103] In the above embodiments, if a user discovers data incorrectly clustered into different categories or incorrectly clustered into the same category through the search page, requiring a merge or split operation, they can select the data to be operated on and send a second correction request to a branch of the backend clustering system. Upon receiving the second correction request, the clustering system first performs data validity and operability checks. If the user-initiated second data to be corrected exists and the checks pass, the operation to write to the target system can proceed. If the second data to be corrected does not exist or the checks fail, the operation returns a failure message, and the user can check the specific reason based on the failure message.

[0104] In the above embodiments, after the verification is passed, the clustering system can calculate the second correction instruction corresponding to the second data to be corrected according to the correction logic for different errors included in the system. For example, if data that has been incorrectly clustered into different categories and thus needs to be merged, the merged data and the retained data can be calculated. That is, if multiple data belonging to the same category are divided into different categories of data, it can be calculated which data among the data that needs to be merged is the retained master data (i.e., the retained data) and which data will be merged into the master data (i.e., the merged data).

[0105] In the above embodiments, to facilitate effective management and processing of correction requests, the lifecycle of the correction data (i.e., the aforementioned second preset period) can be defined according to different priorities or correction benefits. For example, the second preset period for high-priority or high-benefit second data to be corrected will be shorter, which can instruct the clustering system to process it first. If the backend system fails to process the correction instruction within the preset period, the instruction will be considered expired and automatically deleted from the third-party cache to avoid consuming too much memory resources or generating unnecessary data conflicts.

[0106] This embodiment allows for the determination of correction data through multiple means, including querying secondary correction data from the system or directly receiving new correction requests from the target user. This multi-source correction data access mechanism enables the system to flexibly respond to various correction needs, whether from automatic system detection or direct user intervention, ensuring timely response and appropriate corrective measures.

[0107] In one exemplary embodiment, after determining the second corrected data as the corrected data, the method further includes: sending the second corrected data to the target system to instruct the target system to store the second corrected data.

[0108] In the above embodiments, once the backend clustering system determines the second corrected data, in order to ensure that the data correction takes effect in real time, the second corrected data can also be sent to the target system, instructing the target system to store the second corrected data for real-time querying.

[0109] In this embodiment, the corrected data is stored in the target system and the original data is stored in the backend clustering system. The dual storage engine can reduce the burden on the backend data storage system and computing system because the corrected data can be directly provided by the target system during the query phase, reducing the need for frequent access to the backend system.

[0110] In one exemplary embodiment, after correcting the stored data associated with the correction data according to the correction data, the method further includes: if the correction of the stored data associated with the correction data is completed within a third preset period, sending a first deletion instruction to the target system to instruct the target system to delete the correction data from the target system based on the first deletion instruction; if the correction of the stored data associated with the correction data is not completed within the third preset period, sending a second deletion instruction to the target system to instruct the target system to delete the correction data from the target system based on the second deletion instruction.

[0111] In the above embodiments, when the clustering system completes the data correction associated with the correction data within a specified third preset period, the processed correction data can be deleted from the target system. If the backend clustering system fails to process the correction data due to some anomaly or insufficient processing capacity, the correction data will automatically expire according to the defined lifecycle (i.e., the aforementioned third preset period). The third preset period can have different expiration times based on different priority values, and can also be determined based on the benefits of correction. Since the correction data used by the clustering system can come from different sources, the third preset period can be either the second preset period or the first preset period under different circumstances.

[0112] In this embodiment, when the backend system successfully completes the data correction associated with the stored correction data within the third preset period, a first deletion command is sent to the target system to delete the correction data. This ensures data consistency between the storage system and the caching system, avoids inaccurate or redundant query results caused by outdated correction data in the cache, and maintains high accuracy of system data. Furthermore, by introducing a second deletion command, even if the backend system fails to complete the data correction within the preset period, the target system will still be triggered to delete the correction data, preventing indefinite occupation of cache resources and ensuring effective resource management and recycling.

[0113] The method for determining the query results in this application will be explained below with reference to specific embodiments.

[0114] Figure 7 This is a module interaction diagram based on the query result determination method in the optional examples of this application, such as... Figure 7As shown, it can include a query system, a third-party caching system, and a clustering system. The query system can handle query requests and data correction requests initiated by target users. Data correction can be user-initiated functions such as merging multiple types of data into the same type of data (merging) or splitting the same type of data into multiple types of data (splitting), or it can be a data correction function built into the clustering system itself. The third-party caching system can provide users with operations such as data storage, querying, and deletion for correcting data. The clustering system can perform image clustering and provide image query and retrieval.

[0115] In the above embodiments, the process for a user to initiate data correction can be found in [reference needed]. Figure 4 Users can find data incorrectly clustered into different categories or into the same category through the search interface, requiring merging or splitting. Selecting the data to be corrected initiates a data correction request. Upon receiving the request, the query system first performs data validity and operability checks. If the data exists, the check passes and allows the user to proceed; otherwise, the operation fails. After successful checks, the query system calculates correction logic for each issue based on stored rules. For example, it calculates the merged and retained data for incorrectly clustered data and data incorrectly clustered into the same category. The corrected data is then written to a third-party caching system, such as Redis or ZooKeeper, according to the target system's requirements, offering high query response performance. Finally, the corrected data is sent to the clustering system, using event notification mechanisms like Kafka or ZooKeeper, ensuring the clustering system truly implements data storage and correction.

[0116] In the above embodiments, the backend clustering system actually performs the data correction action; see further... Figure 6After real-time images are parsed, they are sent to the backend clustering system for classification. The clustering system can use methods such as K-Means or CluStream for real-time clustering, or collect images periodically and perform offline clustering using methods such as hierarchical or DBSCAN. Simultaneously, if corrected data exists, the backend clustering system will also process it, merging or splitting the data based on its content. Corrected data can also be prioritized, with the highest priority data being processed first. Finally, after clustering or corrected data processing is complete, the processed corrected data is cleared from the third-party cache. If the backend clustering system fails to process corrected data due to anomalies or insufficient processing capacity, the corrected data will automatically expire according to a defined lifecycle, such as different expiration times for different priority data, or expiration based on the benefits of the correction. Furthermore, the clustering system itself can add a data correction branch to determine whether merging or splitting is necessary. Once a correction is determined, if real-time application is desired, the corrected data can be placed in the third-party cache for immediate retrieval.

[0117] In the above embodiments, the corrected data can be displayed in real time. See also... Figure 3 Users can perform queries on the front-end page. The query system first queries the back-end clustering system, and after obtaining the corresponding return results, it queries the third-party caching system based on the returned data ID and other key information. If the corresponding information is not found, it means that the data has not been corrected, and the query results from the back-end clustering system are returned directly. If corrected data is found, the returned results are corrected based on the corrected data. For example, if records A and B are incorrectly clustered into different categories, they are merged into A. If both A and B exist in the returned results, B is not returned as an independent category of data, but rather the corresponding data of B is merged into A and returned.

[0118] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0119] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory (ROM) / random access memory (RAM), magnetic disk, optical disk), and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of this application.

[0120] According to another aspect of the embodiments of this application, a query result determination apparatus is also provided. This query result determination apparatus can be used to implement the query result determination method provided in the above embodiments, and will not be repeated as already described. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the apparatus described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0121] Figure 8 This is a structural block diagram of an optional query result determination device according to an embodiment of this application. Figure 1 ,like Figure 8 As shown, the device for determining the query result includes:

[0122] The first determining module 82 is used to determine the first query result based on the first query request of the target user;

[0123] The second determining module 84 is used to determine, based on the first query result, whether the target system includes first corrected data associated with the first query request, wherein the first corrected data is determined based on the first corrected request sent by the target user;

[0124] Correction module 86 is used to correct the first query result according to the first correction data when the target system includes the first correction data, so as to obtain the target query result;

[0125] The first sending module 88 is used to send the target query result to the target user.

[0126] In an exemplary embodiment, the correction module 86 can correct the first query result according to the first correction data to obtain the target query result by: determining the first correction instruction included in the first correction data; and correcting the first query result based on the first correction instruction to obtain the target query result.

[0127] In an exemplary embodiment, the correction module 86 can correct the first query result based on the first correction instruction to obtain the target query result in the following manner: determining whether the returned data included in the first query result is the same as the first data to be corrected indicated by the first correction instruction; if the returned data is the same as the first data to be corrected and the first correction instruction indicates a merging operation, merging the data included in the returned data according to the merging operation to obtain the target query result; if the returned data is the same as the first data to be corrected and the first correction instruction indicates a splitting operation, splitting the data included in the returned data according to the splitting operation to obtain the target query result; if the returned data is not the same as the first data to be corrected, determining the returned data as the target query result.

[0128] In an exemplary embodiment, the apparatus may be configured to: receive a first correction request sent by the target user before determining a first query result based on a first query request from a target user; determine first data to be corrected included in the first correction request; determine a first correction instruction corresponding to the first data to be corrected based on the first data to be corrected; determine a first preset period for the first correction instruction based on the priority of the first data to be corrected, the first preset period being used to indicate the expiration time of the first correction instruction; and determine the first correction instruction and the first preset period as the first correction data.

[0129] In an exemplary embodiment, the apparatus may further be configured, after receiving the first correction request sent by the target user, to: send the first correction data to the target system to instruct the target system to store the first correction data; and send the first correction data to a clustering system to instruct the clustering system to correct the data associated with the first correction data stored in the clustering system according to the first correction data. It should be noted that the above modules can be implemented by software or hardware. For the latter, implementation can be achieved in the following ways, but is not limited to: all the above modules are located in the same processor; or, the above modules are located in different processors in any combination.

[0130] Figure 9This is a structural block diagram of an optional query result determination device according to an embodiment of this application. Figure 2 ,like Figure 9 As shown, the device for determining the query result includes:

[0131] The receiving module 92 is used to receive a second query request sent by the query system, wherein the second query request is determined based on a first query request sent by the target user;

[0132] The third determining module 94 is used to determine the first query result corresponding to the second query request based on the second query request;

[0133] The second sending module 96 is configured to send the first query result to the query system, instructing the query system to determine whether the target system includes first correction data associated with the first query request based on the first query result, and, if the target system includes the first correction data, to correct the first query result according to the first correction data to obtain a target query result, and to send the target query result to the target user, wherein the first correction data is determined based on the first correction request sent by the target user.

[0134] In one exemplary embodiment, the apparatus may further be used to: determine correction data; and correct stored data associated with the correction data according to the correction data.

[0135] In an exemplary embodiment, the apparatus may determine one of the following correction data by: receiving second correction data sent by the query system, determining the second correction data as the correction data, wherein the second correction data includes the first correction data; receiving a second correction request sent by the target user, determining second data to be corrected included in the second correction request, determining a second correction instruction corresponding to the second data to be corrected based on the second data to be corrected, determining a second preset period of the second correction instruction based on the priority of the second data to be corrected, wherein the second preset period is used to indicate the expiration time of the second correction instruction, determining the second correction instruction and the second preset period as third correction data, and determining the third correction data as the correction data.

[0136] In one exemplary embodiment, the apparatus may further be configured to, after determining the second correction data as the correction data, send the second correction data to the target system to instruct the target system to store the second correction data.

[0137] In one exemplary embodiment, the apparatus may further be configured to, after correcting stored data associated with the correction data according to the correction data: if the correction of stored data associated with the correction data is completed within a third preset period, send a first deletion instruction to the target system to instruct the target system to delete the correction data from the target system based on the first deletion instruction; if the correction of stored data associated with the correction data is not completed within the third preset period, send a second deletion instruction to the target system to instruct the target system to delete the correction data from the target system based on the second deletion instruction.

[0138] According to another aspect of the embodiments of this application, a computer-readable storage medium is provided, the computer-readable storage medium including a stored program, wherein the program executes the steps in any of the above method embodiments when it is run.

[0139] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as USB flash drives, ROMs, RAMs, portable hard drives, magnetic disks, or optical disks.

[0140] According to another aspect of the embodiments of this application, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor is configured to perform the steps of any of the method embodiments described above via the computer program. In an exemplary embodiment, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor, and the input / output device is connected to the processor.

[0141] Specific examples in this embodiment can be found in the examples described in the above embodiments and exemplary implementations, and will not be repeated here.

[0142] According to another aspect of the embodiments of this application, a computer program product is also provided, comprising a computer program / instructions containing program code for performing the methods shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via communication section 1009, and / or installed from removable medium 1011. When the computer program is executed by central processing unit 1001, it performs various functions provided in the embodiments of this application. The sequence numbers of the embodiments of this application above are merely descriptive and do not represent the superiority or inferiority of the embodiments.

[0143] Figure 10 A schematic block diagram of a computer system architecture for implementing embodiments of the present application is shown. Figure 10As shown, the computer system 1000 includes a Central Processing Unit (CPU) 1001, which can perform various appropriate actions and processes based on programs stored in ROM 1002 or programs loaded into RAM 1003 from storage section 1008. Random access memory 1003 also stores various programs and data required for system operation. The CPU 1001, ROM 1002, and RAM 1003 are interconnected via bus 1004. Input / output (I / O) interface 1005 is also connected to bus 1004.

[0144] The following components are connected to I / O interface 1005: an input section 1006 including a keyboard, mouse, etc.; an output section 1007 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 1008 including a hard disk, etc.; and a communication section 1009 including a network interface card such as a local area network card, modem, etc. The communication section 1009 performs communication processing via a network such as the Internet. Drive 1010 is also connected to I / O interface 1005 as needed. Removable media 1011, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., are installed on drive 1010 as needed so that computer programs read from them can be installed into storage section 1008 as needed.

[0145] Specifically, according to embodiments of this application, the processes described in the various method flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 1009, and / or installed from removable medium 1011. When the computer program is executed by central processing unit 1001, it performs various functions defined in the system of this application.

[0146] It should be noted that, Figure 10 The computer system 1000 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.

[0147] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. They can be implemented using computer-executable program code, and thus can be stored in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those described herein, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0148] The above are merely preferred embodiments of this application and are not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the principles of this application should be included within the protection scope of this application.

Claims

1. A method for determining query results, characterized in that, include: The first query result is determined based on the target user's first query request; Based on the first query result, it is determined whether the target system includes first corrected data associated with the first query request, wherein the first corrected data is determined based on the first corrected request sent by the target user; If the target system includes the first correction data, the first query result is corrected according to the first correction data to obtain the target query result; The target query results are sent to the target user.

2. The method according to claim 1, characterized in that, The first query result is corrected according to the first correction data to obtain the target query result, including: Determine the first correction instruction included in the first correction data; The first query result is corrected based on the first correction instruction to obtain the target query result.

3. The method according to claim 2, characterized in that, The first query result is corrected based on the first correction instruction to obtain the target query result, including: Determine whether the returned data included in the first query result is the same as the first data to be corrected indicated by the first correction instruction; If the returned data is the same as the first data to be corrected and the first correction instruction indicates a merge operation, the data included in the returned data are merged according to the merge operation to obtain the target query result; If the returned data is the same as the first data to be corrected, and the first correction instruction indicates a splitting operation, the data included in the returned data is split according to the splitting operation to obtain the target query result; If the returned data is different from the first data to be corrected, the returned data is determined as the target query result.

4. The method according to claim 1, characterized in that, Before determining the first query result based on the first query request of the target user, the method further includes: Receive the first correction request sent by the target user; Determine the first data to be corrected included in the first correction request; A first correction instruction corresponding to the first data to be corrected is determined based on the first data to be corrected; a first preset period of the first correction instruction is determined based on the priority of the first data to be corrected, wherein the first preset period is used to indicate the expiration time of the first correction instruction; The first correction instruction and the first preset period are determined as the first correction data.

5. The method according to claim 4, characterized in that, After receiving the first correction request sent by the target user, the method further includes: The first corrected data is sent to the target system to instruct the target system to store the first corrected data; The first correction data is sent to the clustering system to instruct the clustering system to correct the data associated with the first correction data stored in the clustering system according to the first correction data.

6. A method for determining query results, characterized in that, include: Receive a second query request sent by the query system, the second query request being determined based on the first query request sent by the target user; Determine the first query result corresponding to the second query request based on the second query request; The first query result is sent to the query system to instruct the query system to determine whether the target system includes first corrected data associated with the first query request based on the first query result, and, if the target system includes the first corrected data, to correct the first query result according to the first corrected data to obtain the target query result, and to send the target query result to the target user, wherein the first corrected data is determined based on the first corrected request sent by the target user.

7. The method according to claim 6, characterized in that, The method further includes: Determine the corrected data; The stored data associated with the correction data is corrected according to the correction data.

8. The method according to claim 7, characterized in that, The corrected data includes one of the following: Receive the second corrected data sent by the query system, and determine the second corrected data as the corrected data, wherein the second corrected data includes the first corrected data; The system receives a second correction request sent by the target user, determines the second data to be corrected included in the second correction request, determines the second correction instruction corresponding to the second data to be corrected based on the second data to be corrected, determines the second preset period of the second correction instruction based on the priority of the second data to be corrected, the second preset period is used to indicate the expiration time of the second correction instruction, determines the second correction instruction and the second preset period as the third correction data, and determines the third correction data as the correction data.

9. The method according to claim 8, characterized in that, After determining the second corrected data as the corrected data, the method further includes: The second corrected data is sent to the target system to instruct the target system to store the second corrected data.

10. The method according to claim 7, characterized in that, After correcting the stored data associated with the correction data according to the correction data, the method further includes: If the data associated with the correction data is corrected within the third preset period, a first deletion instruction is sent to the target system to instruct the target system to delete the correction data from the target system based on the first deletion instruction; If the data correction associated with the correction data is not completed within the third preset period, a second deletion instruction is sent to the target system to instruct the target system to delete the correction data from the target system based on the second deletion instruction.

11. A device for determining query results, characterized in that, include: The first determining module is used to determine the first query result based on the first query request of the target user; The second determining module is used to determine, based on the first query result, whether the target system includes first corrected data associated with the first query request, wherein the first corrected data is determined based on the first corrected request sent by the target user; The correction module is used to correct the first query result according to the first correction data when the target system includes the first correction data, so as to obtain the target query result; The first sending module is used to send the target query result to the target user.

12. A device for determining query results, characterized in that, include: The receiving module is used to receive a second query request sent by the query system, wherein the second query request is determined based on a first query request sent by the target user; The third determining module is used to determine the first query result corresponding to the second query request based on the second query request; The second sending module is configured to send the first query result to the query system, instructing the query system to determine whether the target system includes first correction data associated with the first query request based on the first query result, and, if the target system includes the first correction data, to correct the first query result according to the first correction data to obtain a target query result, and to send the target query result to the target user, wherein the first correction data is determined based on the first correction request sent by the target user.

13. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the steps of the method according to any one of claims 1 to 5, or the steps of the method according to any one of claims 6 to 10.

14. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5, or the steps of the method according to any one of claims 6 to 10.

15. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5, or the steps of the method according to any one of claims 6 to 10.

Images