Data processing system, method, device, equipment, medium and product

Abstract

The invention provides a data processing system, method, device and equipment, a medium and a product, and relates to the technical field of artificial intelligence, in particular to the technical fields of big data, cloud computing and the like. The data processing system comprises a data platform, a tool platform and an application platform, wherein the application platform comprises a plurality of service systems; the data platform is used for providing global tags of multiple dimensions; the tool platform is used for combining the global tags to obtain tag combinations corresponding to the business systems, and sending the tag combinations to the business systems; and each business system is used for screening the plurality of candidate objects according to the label combination to obtain a target object, and providing services for the target object. The data driving capability can be improved.

Description

Technical Field

[0001] This disclosure relates to the field of artificial intelligence technology, and in particular to the fields of big data and cloud computing, specifically to a data processing system, method, apparatus, equipment, medium, and product. Background Technology

[0002] With the development of technology, there is an increasing amount of data and business systems. How to more efficiently utilize data to drive business execution is a problem that needs to be solved. Summary of the Invention

[0003] This disclosure provides a data processing system, method, apparatus, device, medium, and product.

[0004] According to one aspect of this disclosure, a data processing system is provided, comprising: a data platform, a tool platform, and an application platform, wherein the application platform includes multiple business systems; the data platform is configured to provide global tags of multiple dimensions; the tool platform is configured to combine the global tags to obtain tag combinations corresponding to each business system, and send the tag combinations to each business system; each business system is configured to filter multiple candidate objects according to the tag combinations to obtain target objects, and to provide services to the target objects.

[0005] According to another aspect of this disclosure, a data processing method is provided, comprising: acquiring global tags of multiple dimensions; combining the global tags of multiple dimensions to obtain tag combinations corresponding to each business system in multiple business systems; sending the tag combinations to each business system so that each business system can filter multiple candidate objects based on the tag combinations to obtain a target object; and providing services to the target object.

[0006] According to another aspect of this disclosure, a data processing apparatus is provided, comprising: an acquisition module for acquiring global tags of multiple dimensions; a combination module for combining the global tags of multiple dimensions to obtain tag combinations corresponding to each business system in multiple business systems; and a sending module for sending the tag combinations to each business system, so that each business system can filter multiple candidate objects based on the tag combinations to obtain a target object, and provide services to the target object.

[0007] According to another aspect of this disclosure, an electronic device is provided, comprising: at least one processor; and a memory communicatively connected to said at least one processor; wherein the memory stores instructions executable by said at least one processor, said instructions being executed by said at least one processor to enable said at least one processor to perform the method as described in any of the foregoing aspects.

[0008] According to another aspect of this disclosure, a non-transitory computer-readable storage medium is provided storing computer instructions, wherein the computer instructions are configured to cause the computer to perform the method according to any of the preceding aspects.

[0009] According to another aspect of this disclosure, a computer program product is provided, comprising a computer program that, when executed by a processor, implements the method according to any of the preceding aspects.

[0010] According to embodiments of this disclosure, data-driven capabilities can be enhanced.

[0011] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0012] The accompanying drawings are provided to better understand this solution and do not constitute a limitation of this disclosure. Wherein:

[0013] Figure 1 This is a schematic diagram based on the first embodiment of the present disclosure;

[0014] Figure 2 This is a schematic diagram according to the second embodiment of the present disclosure;

[0015] Figure 3 This is a schematic diagram of global tags according to an embodiment of this disclosure;

[0016] Figure 4 This is a schematic diagram according to the third embodiment of the present disclosure;

[0017] Figure 5 This is a schematic diagram according to the fourth embodiment of the present disclosure;

[0018] Figure 6 This is a schematic diagram according to the fifth embodiment of the present disclosure;

[0019] Figure 7 This is a schematic diagram of an electronic device used to implement the data processing method of the embodiments of this disclosure. Detailed Implementation

[0020] The exemplary embodiments of this disclosure are described below with reference to the accompanying drawings, including various details of the embodiments to aid understanding, and should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this disclosure. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0021] Taking e-commerce scenarios as an example, multiple business systems can be deployed, such as intelligent coupon issuance systems and traffic support systems.

[0022] In related technologies, the management of various business systems is relatively decentralized. For example, each system uses its own tag system to manage users, which results in poor data-driven capabilities.

[0023] Figure 1 This is a schematic diagram based on the first embodiment of the present disclosure, which provides a data processing system.

[0024] like Figure 1 As shown, the system 100 includes: a data platform 101, a tool platform 102, and an application platform 103. The application platform 103 includes multiple business systems, denoted by business systems A to N.

[0025] The data platform 101 is used to provide global tags in multiple dimensions;

[0026] The tool platform 102 is used to combine the global tags to obtain tag combinations corresponding to each business system, and send the tag combinations to each business system;

[0027] Each of the aforementioned business systems is used to filter multiple candidate objects based on the tag combination to obtain a target object, and to provide services to the target object.

[0028] In e-commerce scenarios, the object can specifically be a user. Therefore, the candidate object is specifically a candidate user, and the target object is specifically a target user. The target object is selected from the candidate objects; for example, one or more candidate objects can be used as the target object.

[0029] Tags are used to identify categories of objects (such as users).

[0030] Global tags refer to unified tags shared by multiple business systems to avoid problems caused by each business system managing its own tags.

[0031] Global tags are multi-dimensional; for example, multiple dimensions may include: user basic attribute dimension, user value dimension, etc.

[0032] The collection, storage, use, processing, transmission, provision, and disclosure of any type of information, such as user personal information, in this technical solution comply with relevant laws and regulations and do not violate public order and good morals.

[0033] Tag combinations can include one or more global tags across dimensions, typically including multiple dimensions of global tags, and can be configured according to the needs of each business system.

[0034] For example, global tags include first-dimensional tags, second-dimensional tags, and third-dimensional tags. Then, for a specific business system, the combination of first-dimensional tags and second-dimensional tags can be used as the tag combination corresponding to that business system.

[0035] After obtaining the tag combinations of each business system, they are assigned to the corresponding business system. Each business system then selects the target object from the candidate objects based on its corresponding tag combination and provides services to the target object.

[0036] For example, for a certain business system, its tag combination is a combination of the first dimension tag and the second dimension tag, and the first dimension tag is "prefer clothing" and the second dimension tag is "like". Then, the candidate users who meet the criteria of "prefer clothing" and "like" will be the target users.

[0037] Next, services are provided to the target users, specifically by performing corresponding business operations for them. For example, if the business system is an intelligent coupon issuance system, then coupons are issued to the target users.

[0038] In this embodiment, the global tags of the data platform can be applied to multiple business systems through the tool platform, realizing the integrated construction of various business systems instead of decentralized construction, thereby improving the data-driven capability. Specifically, it can improve the accuracy of business systems in identifying target objects, and improve the timeliness and reliability of business processing.

[0039] Figure 2 This is a schematic diagram based on a second embodiment of the present disclosure, which provides a data processing system. This embodiment takes global tags for users as an example.

[0040] like Figure 2 As shown, the system 200 includes: a data platform, a tool platform, and an application platform.

[0041] For data platforms:

[0042] It is mainly used to provide global labels in multiple dimensions, and each dimension of labels can include one or more levels.

[0043] Figure 3 This is a schematic diagram of a global tag provided according to an embodiment of the present disclosure.

[0044] like Figure 3 As shown, the global labels 300 across multiple dimensions include: user basic attribute dimension labels, user value dimension labels, user segmentation dimension labels, user preference dimension labels, and user behavior dimension labels.

[0045] Taking user behavior dimension tags as an example, the first-level global tags include: access frequency tags and interaction behavior tags. For each first-level global tag, there can be further second-level global tags. For example, for the first-level access frequency tag, there can be two second-level global tags: high frequency and low frequency; for the first-level interaction behavior tag, there can be three second-level global tags: like, comment and share.

[0046] Specifically, global tags can be obtained by processing source data from multiple business systems using at least one preset processing method.

[0047] like Figure 2 As shown, the processing methods can specifically include at least one of the following: Extract-Transform-Load (ETL), real-time computation, weighted statistics, clustering algorithms, funnel models, etc.

[0048] Specifically:

[0049] User basic attribute dimension labels: These are used to represent user basic attribute data and can include demographic feature labels and device attribute labels.

[0050] This dimension label can be obtained through ETL methods, such as extracting user registration information, embedding data in applications (APPs), or using Global Positioning System (GPS) positioning.

[0051] User value dimension tags: These are used to characterize user value, which can be reflected in multiple aspects. Specific tags for this dimension may include: RFM level and user lifecycle. RFM refers to Recency-Frequency-Monetary (RFM), while user lifecycle includes, for example, new customers, active customers, and churned customers.

[0052] This dimension label is mainly based on users' historical transaction data and behavioral data, and is divided into value levels through operational business rules.

[0053] User segmentation dimension tags: These are used to represent user groups and can include: price-sensitive, quality-seeking, etc.

[0054] This dimension label is mainly based on user search and purchase data, and is obtained by clustering using a clustering algorithm.

[0055] User preference dimension tags: These are used to characterize user preferences and can include category preferences (such as clothing, beauty, or digital products) and brand preferences.

[0056] This dimension label is mainly obtained by processing user search, browsing, and click behavior data using a strategy model.

[0057] User behavior dimension tags: These are used to characterize user behavior and can include: access frequency, interaction behavior, etc.

[0058] This dimension label is mainly based on real-time event logs or offline data, and identifies user behavior patterns through funnel models and time series models.

[0059] In this embodiment, global tags are obtained by processing source data from multiple business systems, which can enrich the data volume and improve the comprehensiveness of global tags. By processing the source data to obtain global tags through the above processing method, appropriate processing methods can be selected according to different tag dimensions, improving the flexibility of processing methods and thus obtaining more accurate global tags.

[0060] For tool platforms:

[0061] It connects the data platform and the application platform, and is mainly used to provide tools to apply the global tags provided by the data platform to multiple business systems of the application platform.

[0062] like Figure 2 As shown, the tool platform mainly includes: grouping tools, tag management tools, quality monitoring tools, tag recommendation tools, and tag revenue display tools.

[0063] For grouping tools:

[0064] A grouping tool is used to receive combination instructions through an interactive interface, and to combine the global tags according to the combination instructions to obtain the tag combination.

[0065] Among them, combined instructions can include: drag instructions, setting instructions, or input instructions.

[0066] Drag-and-drop commands, for example, provide draggable global labels on the interactive interface, allowing users to drag one or more of them to create a label combination as needed.

[0067] Setting instructions, for example, providing a settings button on the interactive interface, allows users to select one or more global tags to form a tag combination according to their actual needs.

[0068] Users can input commands using natural language. The grouping tool extracts the natural language input and obtains tag combinations. For example, if the input command is "users in city X who added items to their cart but did not place an order in the last 30 days", the tags "orders placed in the last 30 days" and "city X" can be extracted.

[0069] In addition, the number of target objects corresponding to the tag combination can be obtained and displayed.

[0070] For example, for a user, the number of users covered by a tag combination can be calculated in real time, so that the use of the tag combination can be determined or the tag combination can be readjusted based on the number of users.

[0071] In addition, tag combinations can be adjusted based on new combination instructions. This allows for on-demand adjustments to tag combinations, and these adjustments can be made in real time, thereby improving the timeliness and accuracy of tag combinations.

[0072] After obtaining the tag combinations of each business system through the grouping tool, the tags can be sent to the corresponding business system through the Application Programming Interface (API) for the business system to use, thus realizing the application of global tags to business systems.

[0073] In this embodiment, the grouping tool obtains tag combinations based on the combination instructions of the interactive interface. Tag combinations can be obtained easily and efficiently through interactive means, which is convenient for users and improves ease of use and intuitiveness.

[0074] For tag management tools: used to manage global tags, specifically including at least one of the following: lifecycle management, access control, and version control.

[0075] Lifecycle management includes, for example, creating, updating, and deleting one or more global tags. Taking deletion as an example, one or more global tags can be deleted at a time, and batch processing can be achieved by deleting multiple global tags at once.

[0076] Access control, for example, upon receiving a combination command, first performs verification, and only after successful verification can the tags be combined. This verification process can be based on the tag permissions of the tags to be combined, or it can be based on the user permissions of the combination command, thereby improving data security.

[0077] Version control, such as recording the change history of global tags, can improve the traceability and security of changes.

[0078] In this embodiment, by managing global tags, the required tags can be created, updated, or deleted in a timely manner, thus ensuring the timely updating and effectiveness of tags. Access control can improve tag security, and version control can improve tag traceability.

[0079] For quality monitoring tools: used to manage the quality of global tags, specifically including at least one of the following: data integrity check, accuracy verification, and outlier monitoring.

[0080] Among these measures is data integrity checking, such as checking for missing fields or null values ​​in global tags, which can improve the integrity of global tags.

[0081] Accuracy verification, for example, can be performed by setting logical or business rules to verify the accuracy of global tags, thereby improving the accuracy of global tags.

[0082] Anomaly monitoring, for example, by setting monitoring thresholds such as data fluctuation range and indicator fluctuation range, can determine whether global tags are abnormal. This allows for the timely detection of abnormal global tags, which can then be deleted or isolated from business operations. This improves the overall accuracy and reliability of global tags and prevents interference with normal business operations.

[0083] In this embodiment, by monitoring the quality of global tags, the accuracy and completeness of global tags can be improved, and anomalies can be isolated in a timely manner to avoid interfering with normal business operations.

[0084] Tag recommendation tool: Used to recommend tags globally.

[0085] For example, for a specific user, relevant tags can be automatically recommended based on the user's historical behavior and preferences, which can reduce the screening cost.

[0086] In addition, it can analyze the relationships between global tags and recommend available tag combinations and their corresponding application scenarios.

[0087] In this embodiment, by recommending global tags, the cost for users to filter or combine tags can be reduced, and the efficiency of tag filtering and combination can be improved.

[0088] This is a tool for displaying tag revenue, used to show the revenue corresponding to each tag globally.

[0089] Specifically, this may include: determining and displaying the popularity value of global tags based on their usage frequency and user coverage; and / or determining and displaying the improvement value (such as the percentage improvement of business metrics) of global tags for specific business indicators (such as conversion rate, retention rate, etc.) through comparative experiments.

[0090] The aforementioned popularity and growth values ​​can be displayed intuitively and visually through charts, dashboards, and other means.

[0091] In this embodiment, by displaying the benefits of global tags, clear reference information can be provided to users, such as popularity value or improvement value, reducing the user's selection cost and improving the efficiency of tag combination.

[0092] For application platforms:

[0093] The application platform includes multiple business systems, such as Figure 2 As shown, the multiple business systems include: intelligent coupon issuance system, traffic support system, intelligent outreach system, and A / B testing system.

[0094] Each business system uses the combination of tags obtained from the tool platform to filter out target objects and provide services to those target objects.

[0095] For example, with an intelligent coupon distribution system, users can configure tag combinations for the system through a tool platform, such as "users who have newly registered and added items to their cart within the last 7 days but have not placed an order," and then send these to the intelligent coupon distribution system. The system uses these tag combinations to filter users and identify target users. If it identifies a user who simultaneously meets the rules of "new customer" and "added items to cart but did not pay," it sends that user the corresponding coupon. The user then makes a purchase after receiving the coupon.

[0096] Based on this, the intelligent coupon issuance system improves the accuracy of identifying target users, thereby improving the accuracy of business processing.

[0097] Similarly, traffic support systems can improve the accuracy of identifying target users for target merchants and provide them with more traffic.

[0098] Intelligent outreach systems can improve the accuracy of identifying target users, thereby enabling the precise delivery of messages to them.

[0099] The AB test system can accurately match the experimental subjects, improving the accuracy of control experiment results.

[0100] Furthermore, each business system can be specifically used to: in response to the achievement of the preset conditions corresponding to each business system, filter the multiple candidate objects according to the tag combination to obtain a target object, and provide services to the target object.

[0101] Different business systems can correspond to different preset conditions.

[0102] For example, for an intelligent coupon distribution system, the preset conditions can be real-time conditions, that is, responding to the tag combinations sent by the tool platform, filtering target objects and providing services to target object providers. Alternatively, for an intelligent outreach system, the preset conditions can be non-real-time set time points (such as a set time before a certain promotional activity), and after reaching the set time point, filtering target objects and providing services to target objects.

[0103] In this embodiment, target object screening and subsequent services are performed based on preset conditions corresponding to each business system. Business processing can be carried out when the preset conditions of each business system are met, thereby improving the accuracy and effectiveness of business processing.

[0104] Figure 4 This is a schematic diagram based on a third embodiment of the present disclosure, which provides a data processing system.

[0105] like Figure 4 As shown, the system 400 includes: a data platform 401, a tool platform 402, an application platform 403, the application platform 403 including multiple business systems, denoted by business systems A to N, and a control platform 404.

[0106] For details regarding the data platform, tool platform, and application platform, please refer to the relevant descriptions in the above embodiments.

[0107] The control platform 404 is used to obtain the business processing results of each business system for the target object, and update the global tag and / or the tag combination based on the business processing results.

[0108] For example, after obtaining the business processing results from the business system, if they do not meet expectations, global tags for other dimensions can be generated based on the actual situation, or other tags can be provided for a certain dimension. For example, for a certain business system, if the business metrics do not meet expectations, the tags for that dimension can be adjusted. For example, for interactive behavior tags, a "favorite" tag can be added to better meet business needs.

[0109] In this embodiment, closed-loop control can be achieved by updating global tags or tag combinations based on the business processing results of the business system through the control platform. That is, the business system processes according to the tag combinations, realizing the application of global tags and tag combinations to the business system. Since global tags or tag combinations can also be updated according to the business processing results, the application of business processing results to global tags or tag combinations can be realized. This interaction can realize the continuous updating of global tags, tag combinations and the business system, improving the accuracy, timeliness and reliability of business processing results.

[0110] Figure 5 This is a schematic diagram based on the fourth embodiment of the present disclosure, which provides a data processing method. For example... Figure 5 As shown, the method includes:

[0111] 501. Obtain global tags from multiple dimensions.

[0112] 502. Combine the global tags of the multiple dimensions to obtain the tag combinations corresponding to each business system in the multiple business systems.

[0113] 503. Send the tag combination to each of the business systems so that each of the business systems can filter multiple candidate objects based on the tag combination to obtain a target object, and provide services to the target object.

[0114] In this embodiment, the global tags of the data platform can be applied to multiple business systems through the tool platform, realizing the integrated construction of various business systems instead of decentralized construction, thereby improving the data-driven capability. Specifically, it can improve the accuracy of business systems in identifying target objects, and improve the timeliness and reliability of business processing.

[0115] In some embodiments, combining the global tags of the multiple dimensions to obtain the tag combinations corresponding to each business system in the multiple business systems includes:

[0116] The system receives combination instructions through an interactive interface and combines the global tags according to the combination instructions to obtain the tag combination.

[0117] In this embodiment, the grouping tool obtains tag combinations based on the combination instructions of the interactive interface. Tag combinations can be obtained easily and efficiently through interactive means, which is convenient for users and improves ease of use and intuitiveness.

[0118] In some embodiments, the method further includes at least one of the following:

[0119] Manage the global tags;

[0120] Perform quality monitoring on global tags;

[0121] The recommended global tags;

[0122] Display the revenue corresponding to the global tag.

[0123] In this embodiment, by managing global tags, required tags can be created, updated, or deleted in a timely manner, ensuring timely updates and effectiveness. Access control enhances tag security, while version control improves tag traceability. Quality monitoring of global tags improves their accuracy and completeness, and allows for timely isolation of anomalies to prevent disruption to normal business operations. Recommending global tags reduces the cost for users to filter or combine tags, improving the efficiency of tag selection and combination. Displaying the benefits of global tags provides users with clear reference information, such as popularity or improvement values, reducing user selection costs and improving tag combination efficiency.

[0124] In some embodiments, the method further includes:

[0125] Update the global tag and / or the tag combination based on the business processing results of each business system for the target object.

[0126] In this embodiment, closed-loop control can be achieved by updating global tags or tag combinations based on the business processing results of the business system through the control platform. That is, the business system processes according to the tag combinations, realizing the application of global tags and tag combinations to the business system. Since global tags or tag combinations can also be updated according to the business processing results, the application of business processing results to global tags or tag combinations can be realized. This interaction can realize the continuous updating of global tags, tag combinations and the business system, improving the accuracy, timeliness and reliability of business processing results.

[0127] This method can be applied to the aforementioned tool platforms, and details can be found in the relevant descriptions above.

[0128] Figure 6 This is a schematic diagram based on the fifth embodiment of the present disclosure, which provides a data processing apparatus. For example... Figure 6 As shown, the device 600 includes: an acquisition module 601, a combination module 602, and a transmission module 603.

[0129] Module 601 is used to obtain global labels from multiple dimensions;

[0130] The combination module 602 is used to combine the global tags of the multiple dimensions to obtain the tag combination corresponding to each business system in the multiple business systems.

[0131] The sending module 603 is used to send the tag combination to each of the business systems, so that each of the business systems can filter multiple candidate objects based on the tag combination to obtain a target object, and provide services to the target object.

[0132] In some embodiments, the combination module 602 is further configured to:

[0133] The system receives combination instructions through an interactive interface and combines the global tags according to the combination instructions to obtain the tag combination.

[0134] In some embodiments, the device further includes:

[0135] The processing module is configured to perform at least one of the following: manage the global tags; perform quality monitoring on the global tags; recommend the global tags; and display the benefits corresponding to the global tags.

[0136] In some embodiments, the device further includes:

[0137] The update module is used to update the global tag and / or the tag combination based on the business processing results of each business system for the target object.

[0138] This method can be applied to the aforementioned tool platforms, and details can be found in the relevant descriptions above.

[0139] It is understood that the same or similar content in different embodiments of this disclosure can be referred to each other.

[0140] It is understood that the terms "first" and "second" in the embodiments of this disclosure are only used for distinction and do not indicate the degree of importance or the order of events.

[0141] It is understandable that, unless otherwise specified, the order of steps in the process indicates that the temporal relationship between these steps is not limited.

[0142] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0143] Figure 7 A schematic block diagram of an example electronic device 700 that can be used to implement embodiments of the present disclosure is shown. The electronic device 700 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0144] like Figure 7 As shown, the electronic device 700 includes a computing unit 701, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 702 or a computer program loaded from a storage unit 707 into a random access memory (RAM) 703. The RAM 703 may also store various programs and data required for the operation of the electronic device 700. The computing unit 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0145] Multiple components in electronic device 700 are connected to I / O interface 705, including: input unit 706, such as keyboard, mouse, etc.; output unit 707, such as various types of displays, speakers, etc.; storage unit 708, such as disk, optical disk, etc.; and communication unit 709, such as network card, modem, wireless transceiver, etc. Communication unit 709 allows electronic device 700 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0146] The computing unit 701 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 701 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 701 performs the various methods and processes described above, such as data processing methods. For example, in some embodiments, the data processing method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 708. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 700 via ROM 702 and / or communication unit 709. When the computer program is loaded into RAM 703 and executed by the computing unit 701, one or more steps of the data processing method described above may be performed. Alternatively, in other embodiments, the computing unit 701 may be configured to perform data processing methods by any other suitable means (e.g., by means of firmware).

[0147] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0148] The program code used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable task processing device, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0149] In the context of this disclosure, a machine-readable medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0150] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0151] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as a data server), or computing systems that include middleware components (e.g., an application server), or computing systems that include frontend components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., a communication network). Examples of communication networks include local area networks (LANs), wide area networks (WANs), and the Internet.

[0152] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service system that addresses the shortcomings of traditional physical hosts and VPS (Virtual Private Server) services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0153] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0154] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A data processing system, including: Data platform, tool platform and application platform, wherein the application platform includes multiple business systems; The data platform is used to provide global tags in multiple dimensions; The tool platform is used to combine the global tags to obtain tag combinations corresponding to each business system, and send the tag combinations to each business system; Each of the aforementioned business systems is used to filter multiple candidate objects based on the tag combination to obtain a target object, and to provide services to the target object.

2. The system according to claim 1, wherein, The tool platform includes: A grouping tool is used to receive combination instructions through an interactive interface, and to combine the global tags according to the combination instructions to obtain the tag combination.

3. The system according to claim 2, wherein, The tool platform also includes at least one of the following: Tag management tools, quality monitoring tools, tag recommendation tools, and tag revenue display tools; The tag management tool is used to manage the global tags; The quality monitoring tool is used to monitor the quality of global tags; The tag recommendation tool is used to recommend the global tags; The tag revenue display tool is used to display the revenue corresponding to the global tag.

4. The system according to claim 1, wherein, The data platform is specifically used for: The source data corresponding to the multiple business systems are processed using at least one preset processing method to obtain the global tag.

5. The system according to claim 1, wherein, The various business systems are specifically used for: In response to the achievement of preset conditions corresponding to each of the business systems, the target object is obtained by filtering the multiple candidate objects according to the tag combination, and services are provided to the target object.

6. The system according to any one of claims 1-5, further comprising: A control platform is used to obtain the business processing results of each business system for the target object, and update the global tag and / or the tag combination based on the business processing results.

7. A data processing method, comprising: Retrieve global tags from multiple dimensions; The global tags of the multiple dimensions are combined to obtain the tag combinations corresponding to each business system in the multiple business systems; The tag combination is sent to each of the business systems so that each business system can filter multiple candidate objects based on the tag combination to obtain the target object and provide services to the target object.

8. The method according to claim 7, wherein, The step of combining the global tags of the multiple dimensions to obtain the tag combinations corresponding to each business system in the multiple business systems includes: The system receives combination instructions through an interactive interface and combines the global tags according to the combination instructions to obtain the tag combination.

9. The method of claim 8, further comprising at least one of the following: Manage the global tags; Perform quality monitoring on global tags; The recommended global tags; Display the revenue corresponding to the global tag.

10. The method according to any one of claims 7-9, further comprising: Update the global tag and / or the tag combination based on the business processing results of each business system for the target object.

11. A data processing apparatus, comprising: The acquisition module is used to acquire global tags from multiple dimensions; The combination module is used to combine the global tags of the multiple dimensions to obtain the tag combinations corresponding to each business system in the multiple business systems. The sending module is used to send the tag combination to each of the business systems, so that each business system can filter multiple candidate objects based on the tag combination to obtain the target object, and provide services to the target object.

12. An electronic device, comprising: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the method of any one of claims 7-10.

13. A non-transitory computer-readable storage medium storing computer instructions, wherein, The computer instructions are used to cause the computer to perform the method according to any one of claims 7-10.

14. A computer program product comprising a computer program that, when executed by a processor, implements the method according to any one of claims 7-10.

Images