Global integration interest intelligent matching system and method based on digital identity graph

Abstract

The application discloses a global integral right and interest intelligent matching system and method based on a digital identity graph, and relates to the technical field of integral application. The system comprises a digital identity construction module, a joint positioning module, a multi-level coordination module and an evolution tracing module. The digital identity construction module is used for collecting data, forming a digital identity graph, dividing user node sets into logical partitions according to source domains, and generating partition envelope boundaries in each logical partition. The joint positioning module extracts cross-domain nodes existing between different logical partitions, generates joint positioning identifiers, and labels the joint positioning identifiers in edge connections of the digital identity graph. The multi-level coordination module calls the joint positioning identifiers, adjusts the partition envelope boundaries in each logical partition in linkage, forms multi-level envelopes, and performs coordinated matching on integrals inside and outside each logical partition according to integral trajectories of users, and outputs matching results. The evolution tracing module is used for writing the matching results into the digital identity graph, updating evolution chains of the multi-level envelopes, and establishing tracing indexes of the integrals through the evolution chains.

Description

Technical Field

[0001] This invention relates to the field of points application technology, and in particular to a full-domain points-based intelligent matching system and method for rights and interests based on digital identity graphs. Background Technology

[0002] With the rapid development of the digital economy and platform-based services, user identity management and the circulation of points-based benefits have gradually become important components of enterprise digital transformation. Traditional points systems are mostly based on the accumulation and redemption mechanisms within a single enterprise or a limited ecosystem. While these mechanisms can enhance user stickiness, their application scenarios are limited, and cross-domain interoperability is low. In recent years, with the development of technologies such as big data, blockchain, and knowledge graphs, user identity information has gradually evolved from static identifiers to dynamic profiles. Through comprehensive analysis of transaction behavior, points records, and cross-domain interaction data, multi-dimensional digital identity profiles can be constructed, providing support for personalized services and precision marketing. Furthermore, the combination of digital identity and points-based benefits not only enhances the circulation of points but also improves cross-platform and cross-industry resource integration capabilities, becoming an important research direction for smart finance, smart retail, and urban service systems. Especially driven by the concept of "full-domain points," how to break through the silo effect of a single points system and achieve the integration and intelligent matching of cross-domain points resources has become a key focus of the industry.

[0003] However, existing technologies still have significant shortcomings. Taking existing points management platforms as an example, solutions like CN mainly focus on centralized storage and transaction settlement of points, lacking comprehensive modeling at the identity level and failing to dynamically reflect users' multiple behavioral trajectories across platforms. Furthermore, cross-domain points matching largely relies on pre-defined mapping rules, making it difficult to adapt to the real-time evolution of user behavior and rights value, resulting in low matching efficiency and uneven resource allocation. Another type of solution based on blockchain or distributed identity (DID), while having advantages in data credibility and security, often only depicts points rights at the transaction record level, lacking structured modeling of points flow relationships and failing to form a traceable evolutionary chain, thus making it difficult to support complex multi-level collaborative matching.

[0004] In addition, existing points systems are generally limited to static mapping or single-point connection, failing to achieve joint positioning of cross-domain identity nodes and dynamic adjustment of envelope boundaries. This results in insufficient intelligence in matching cross-domain points benefits, making it difficult to meet the needs of full-domain points circulation and maximizing the value of benefits. Summary of the Invention

[0005] In view of the common problems existing in current points management and digital identity technologies, this invention is proposed.

[0006] Therefore, the problem to be solved by this invention is how to solve the problems of low matching efficiency of integrals between different domains, broken evolution chains, and difficulty in cross-domain tracing.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0008] In a first aspect, the present invention provides a global points-based intelligent matching system based on a digital identity graph, comprising: a digital identity construction module, used to collect user identity information, points records, and cross-domain transaction data to form a digital identity graph, and to divide the set of user nodes in the digital identity graph into logical partitions according to their source domains, generating partition envelope boundaries within each logical partition; a joint positioning module, used to extract cross-domain nodes existing between different logical partitions based on the partition envelopes, and generate joint positioning identifiers; and to label the joint positioning identifiers as input parameters in the edge connections of the digital identity graph; a multi-level collaboration module, used to invoke the joint positioning identifiers to perform coordinated adjustments to the partition envelope boundaries within each logical partition, forming multi-level envelopes, and to perform collaborative matching of points inside and outside each logical partition based on the user's points trajectory, outputting matching results; and an evolution tracing module, used to write the matching results into the digital identity graph, correspondingly updating the evolution chain of the multi-level envelopes; and to establish a points tracing index through the evolution chain.

[0009] As a preferred embodiment of the intelligent matching system for full-domain points-based rights based on digital identity graphs described in this invention, the digital identity construction module includes: an identity collection submodule, which collects user identity information, points records, and cross-domain transaction data to form an initial data set; a graph generation submodule, which generates a digital identity graph based on the initial data set and maps user nodes and points edges into a graph-based structure; and a partition envelope submodule, which divides the user node set of the digital identity graph into logical partitions according to the source domain and generates a partition envelope within each logical partition to limit the local points range; the nodes of the digital identity graph are user identity units, and the edges are points flow relationships.

[0010] As a preferred embodiment of the intelligent matching system for full-domain points-based rights based on digital identity graphs described in this invention, the joint positioning module includes: a cross-domain node identification submodule, which retrieves edges connecting different logical partitions in the digital identity graph and records the corresponding user nodes as a candidate cross-domain node set; and adds nodes that exist in multiple logical partitions simultaneously to the cross-domain node set; an identifier generation submodule, which generates joint positioning identifiers based on the cross-domain nodes; and an identifier labeling submodule, which labels the joint positioning identifiers on the edge connections in the digital identity graph; the extraction of cross-domain nodes existing between different logical partitions includes: in the digital identity graph, calling the edge set of logical partitions, retrieving edges that simultaneously connect two or more different logical partitions, and recording the corresponding user nodes as a candidate cross-domain node set; and adding the candidate cross-domain node set to the cross-domain node set if it exists in multiple logical partitions simultaneously.

[0011] As a preferred embodiment of the intelligent matching system for full-domain points-based rights based on digital identity graphs described in this invention, the multi-level collaborative module includes: an envelope linkage submodule, which calls the joint positioning identifier to perform linkage adjustment on the boundaries of each partition envelope to generate a multi-level envelope; an points trajectory parsing submodule, which parses the user's points trajectory within the digital identity graph and maps it to the envelope level corresponding to the multi-level envelope; and a collaborative matching submodule, which performs points collaborative processing inside and outside the partitions within the multi-level envelope to generate matching results.

[0012] As a preferred embodiment of the intelligent matching system for full-domain points-based rights based on digital identity graphs described in this invention, the envelope linkage submodule includes: traversing each logical partition according to the joint positioning identifier, filtering out cross-domain nodes that have edge connections in multiple logical partitions, and storing them in a cross-domain node set; for each cross-domain node, indexing and aligning the partition envelope boundary of its logical partition with the partition envelope boundary of the adjacent logical partition, calculating the overlapping area of ​​each pair of partition envelopes, and recording the cross-domain nodes located within and outside the overlapping area, for determining the boundary segments that need to be linked for expansion or contraction; traversing all overlapping areas, adjusting the partition envelope boundary to cover the minimum boundary range of H% cross-domain nodes, while keeping the points of non-cross-domain nodes in the original logical partition within the envelope boundary, and generating an adjusted multi-level envelope.

[0013] As a preferred embodiment of the intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as described in this invention, the points trajectory parsing submodule includes: traversing each user node, extracting points change records according to time series to form the user's points trajectory; segmenting the user's points trajectory into points growth, decrease, or stable segments, and marking the logical partition to which each segment belongs, the corresponding envelope level in the multi-level envelope, and the participation of cross-domain nodes within the segment; mapping each points trajectory segment to the corresponding level of the multi-level envelope according to the segment markings, marking the points trajectories of cross-domain nodes in the adjusted boundary segments, and outputting the mapping results.

[0014] As a preferred embodiment of the intelligent matching system for full-domain points-based rights based on digital identity graphs described in this invention, the collaborative matching submodule includes: traversing user nodes and points trajectories in each logical partition; sorting user nodes falling within the same envelope level according to the difference in their current points values; marking user nodes whose point differences do not exceed a preset point threshold and have edge connections as collaborative matching groups; for cross-domain nodes, extracting point trajectory segments in different logical partitions, mapping them to the corresponding envelope levels, and generating cross-partition collaborative adjustment schemes based on whether there are cross-partition point overlaps and boundary conflicts, and outputting cross-partition matching information; summarizing the collaborative information inside and outside the logical partitions to generate the final matching result, including the point status of each user node in each logical partition and envelope level, cross-partition collaborative identifier, and envelope level.

[0015] As a preferred embodiment of the intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as described in this invention, the evolution tracing module includes: a result writing submodule, which writes the matching results into the digital identity graph and updates the multi-level envelope; a chain construction submodule, which constructs an evolution chain based on the updated multi-level envelope and forms a points evolution link data structure; and a tracing index submodule, which, when an abnormal redemption occurs, locates the corresponding joint positioning identifier and partition envelope boundary based on the evolution chain to complete the rights and interests tracing.

[0016] As a preferred embodiment of the intelligent matching system for full-domain points-based rights based on digital identity graphs described in this invention, the step of constructing an evolutionary chain based on the updated multi-level envelope includes: traversing the updated multi-level envelope, associating user nodes at each envelope level with their corresponding logical partitions and points status, and generating a user node-envelope level mapping table; recording the points status and envelope level of each user node at different time points in the user node-envelope level mapping table according to the time sequence of the user's points trajectory, forming a time sequence mapping; traversing the user node records in the user node-envelope level mapping table, generating chain units for the envelope level changes of the same user node at consecutive time points, and connecting the chain units to form a complete evolutionary chain according to the association order of logical partitions and cross-domain nodes.

[0017] Secondly, this invention provides a method for intelligent matching of full-domain points-based benefits based on a digital identity graph, comprising: collecting user identity information, points records, and cross-domain transaction data to form a digital identity graph; dividing the set of user nodes in the digital identity graph into logical partitions according to their source domains, and generating a partition envelope within each logical partition; extracting cross-domain nodes existing between different logical partitions based on the partition envelopes, and generating a joint location identifier; using the joint location identifier as an input parameter and marking it in the edge connections of the digital identity graph; calling the joint location identifier to adjust the boundaries of the partition envelopes in each logical partition in a coordinated manner to form a multi-level envelope, and performing collaborative matching of points inside and outside each logical partition based on the user's points trajectory, and outputting the matching result; writing the matching result into the digital identity graph and updating the evolution chain of the multi-level envelope accordingly; and establishing a traceability index for points through the evolution chain.

[0018] Thirdly, the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, they implement the steps of the intelligent matching system for global points-based rights and interests based on digital identity graphs as described in the first aspect of the present invention.

[0019] Fourthly, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, they implement the steps of the intelligent matching system for global points-based rights and interests based on a digital identity graph as described in the first aspect of the present invention.

[0020] The beneficial effects of this invention are as follows: This invention establishes a logical partitioning and multi-level envelope structure based on user identity and points trajectory as two dimensions. This not only identifies cross-domain nodes and performs joint positioning, but also forms multi-level linkages across different partitions, overcoming the limitations of traditional points systems such as low cross-platform interoperability, rigid mapping relationships, and insufficient dynamic matching capabilities. Through a multi-level collaborative mechanism, this invention can automatically complete collaborative matching within and outside partitions based on the evolution trend of points trajectories, improving the liquidity and utilization efficiency of points resources in different scenarios. Simultaneously, the matching results are written into a digital identity graph, constructing a complete evolutionary chain, ensuring the transparency and traceability of the points transfer process, and effectively reducing the risks of abnormal redemption and resource mismatch.

[0021] Overall, this invention not only enhances the intelligent matching and dynamic adaptation capabilities of points-based benefits across the entire domain, but also provides unified technical support for cross-platform and cross-industry points interoperability. Attached Figure Description

[0022] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a structural diagram of a global points-based intelligent matching system for rights and interests based on digital identity graphs.

[0024] Figure 2 This is a flowchart of a method for intelligent matching of full-domain points-based rights and interests based on digital identity graphs. Detailed Implementation

[0025] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0026] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0027] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0028] Figure 1 This is a structural diagram of a global points-based intelligent matching system for rights and interests based on a digital identity graph, according to an embodiment of the present invention. Figure 1 As shown, the intelligent matching system for full-domain points-based rights and interests based on digital identity graphs includes:

[0029] In this embodiment of the invention, the digital identity construction module includes:

[0030] The identity collection submodule collects user identity information, points records, and cross-domain transaction data to form an initial data set.

[0031] The user identification information includes, but is not limited to, the user's unique identification code (such as user registration number, platform assigned ID), the marking information of the user's source domain (such as the bank, retail platform, e-commerce channel, etc.), and the user's registration time and status tag in the source domain.

[0032] Unlike conventional single-identity data collection, this invention further incorporates cross-domain transaction data, such as records of points transfers, points redemptions, and rights exchanges between users in different source domains, to form data entries with cross-domain characteristics. By collecting cross-domain transaction data in the initial stage, potential cross-domain relationships can be established in advance, providing data support for subsequent cross-node identification and joint positioning, avoiding the shortcomings of existing technologies that require secondary supplementation or manual intervention to identify cross-domain relationships.

[0033] Cross-domain transaction data includes not only the accumulated points and spending value of users in a single source domain, but also the time of point changes, the direction of changes (increase or decrease), the transaction scenario (consumption, redemption, transfer, etc.), as well as the validity period and frozen status of points. The complete collection of this data enables a more comprehensive and dynamic edge structure in the subsequent graph generation stage, reflecting the flow of user points and benefits.

[0034] The graph generation submodule generates a digital identity graph based on the initial data set and maps user nodes and integral edges into a graph-based structure; where the nodes of the digital identity graph are user identity units and the edges are integral flow relationships.

[0035] It should be noted that when establishing the edge structure, this invention uses points and benefits records and cross-domain transaction data as input to generate a set of edges between nodes. Each edge is defined as a points and benefits transfer relationship, representing the path for points transfer, exchange, and use between user nodes or between a user and a source domain. Edge attributes include transfer direction, transfer quantity, occurrence time, and the associated source domain identifier. Through this structural mapping method, the graph can simultaneously display the points transfer situation within a domain and the benefits exchange situation across domains.

[0036] The partition envelope submodule divides the set of user nodes in the digital identity graph into logical partitions according to the source domain, and generates a partition envelope within each logical partition to limit the local integration range.

[0037] Specifically, the generation of the partition envelope includes:

[0038] Within the logical partition, the integral values ​​of all user nodes are retrieved, and the set of integral values ​​is aggregated to obtain a statistical feature vector. ,in, The mean, Standard deviation The range is used to describe the overall equity distribution characteristics of a logical partition.

[0039] Based on statistical feature vectors Generate the envelope boundary function:

[0040]

[0041] in, and This is the adjustment coefficient.

[0042] The output is the acceptable integration boundary interval within the logical partition, used to limit the integration range of the logical partition. This interval not only reflects the concentration range of the overall integration equity of the partition, but can also be adjusted by parameters. and It balances tolerance for abnormal fluctuations with tightness of boundaries.

[0043] Combine the scores of all user nodes within the logical partition with... In contrast, if the node is within the boundary of the integral, its rights are considered to be within the effective range of the partition; otherwise, the node is considered to be marked as an off-boundary node for subsequent cross-domain collaboration or anomaly handling.

[0044] As can be seen, unlike conventional single-point threshold detection, the boundary comparison operation of this invention is not an isolated judgment, but rather an interval function generated based on statistical feature vectors. In this way, the criteria for marking nodes outside the boundary not only consider the average level but also incorporate discreteness and extreme differences, thus significantly reducing the risk of misjudgment caused by a single threshold. Simultaneously, nodes outside the boundary will be given focused attention as input in subsequent cross-domain collaboration or anomaly handling stages. For example, in cross-domain collaboration, nodes outside the boundary are more likely to appear at the intersection of multiple partitions, thereby affecting the coordinated adjustment of the partition envelope.

[0045] It should be noted that in conventional user group segmentation operations, domains are often directly segmented based solely on business logic. However, this invention divides nodes into sets within a graph-based structure, enabling the partitions to not only have set meanings but also retain topological information about their relationships with edges, thus providing structured data input for subsequent boundary calculations.

[0046] In this embodiment of the invention, the joint positioning module includes:

[0047] The cross-domain node identification submodule retrieves edges connecting different logical partitions in the digital identity graph and records the corresponding user nodes as a candidate cross-domain node set; it also adds nodes that exist in multiple logical partitions to the cross-domain node set.

[0048] Specifically, in the digital identity graph, the edge set of logical partitions is called to retrieve the edges that connect two or more different logical partitions at the same time, and the corresponding user nodes are recorded as a candidate cross-domain node set; based on the candidate cross-domain node set, the nodes that exist in multiple logical partitions at the same time are confirmed to form a cross-domain node set, which is used as the unique node input for cross-domain interaction.

[0049] For example, for each logical partition, the edge set is traversed to check if there are edges connecting to other logical partitions. If an edge starts in logical partition A and ends in logical partition B, and A and B belong to different source domains, then the user node associated with the edge is marked as a candidate cross-domain node. For a candidate cross-domain node, it is necessary to further determine whether it exists in the node sets of multiple logical partitions: select a node in the candidate set, retrieve the partition affiliation record in the graph structure, and if the node appears in two or more logical partitions, then add it to the cross-domain node set.

[0050] As can be seen, this invention does not simply rely on duplicate identities for judgment, but uses a two-level processing method of edge connection cross-domain detection → candidate node confirmation to locate cross-domain nodes based on the graph structure relationship, thus ensuring the accuracy and uniqueness of cross-domain interaction recognition.

[0051] The identifier generation submodule generates joint location identifiers based on cross-domain nodes.

[0052] Specifically, the generation process uses a combination of partition identifier concatenation and node unique identifier. For example, if a node exists in both partition A and partition B, the joint location identifier will be recorded as "node ID + {A, B} + cross-domain edge index". The identifier generated in this way is different from the regular user ID number. The additional cross-domain structure information allows the identifier to be directly called in subsequent cross-domain path retrieval without having to traverse the original graph structure again.

[0053] As can be seen, this invention structurally binds the identity features of nodes with cross-domain connection relationships, avoiding the inefficient processing method of simply relying on repeated comparisons of identity attributes in traditional methods. Simultaneously, by embedding cross-domain edge indexes in the identifier, the corresponding cross-domain edge connection can be directly located based on the identifier in subsequent matching calculations, improving the indexing speed and query efficiency of cross-domain paths.

[0054] The identification and labeling submodule labels the joint location identifier in the edge connections of the digital identity graph, serving as an indication parameter for the cross-domain integral matching path.

[0055] In this embodiment of the invention, the multi-level collaborative module includes:

[0056] The envelope linkage submodule calls the joint positioning identifier to adjust the envelope boundaries of each partition in a linked manner, generating a multi-level envelope.

[0057] In this embodiment of the invention, the envelope linkage submodule specifically includes the following operation steps:

[0058] 101: Based on the joint location identifier, traverse each logical partition, filter out cross-domain nodes that are connected by edges in multiple logical partitions, and store them in the cross-domain node set.

[0059] Unlike existing technologies that directly merge duplicate identities, this invention identifies nodes through cross-domain edge connections, avoiding misjudgments caused by data anomalies or forgery, and improving the structural accuracy of cross-domain identification.

[0060] 102: For each cross-domain node, align the index of the partition envelope boundary of the logical partition where it is located with the partition envelope boundary of the adjacent logical partition, calculate the overlapping area of ​​each pair of partition envelopes, and record the cross-domain nodes located within and outside the overlapping area to determine the boundary segments that need to be expanded or contracted in a coordinated manner.

[0061] It should be noted that by comparing the indexes, the overlapping area between the envelope boundaries of the two partitions can be calculated, and the cross-domain nodes within and outside the overlapping area can be recorded separately. That is, by extracting the boundary overlap parameters, not only can the differences in the integral distribution of cross-domain nodes in the two logical partitions be identified, but also the boundary segments that need to be expanded or contracted can be located.

[0062] 103: Traverse all overlapping regions and adjust the partition envelope boundary to cover the minimum boundary range of H% (which can be set according to actual needs) of cross-domain nodes, while keeping the integrals of non-cross-domain nodes within the original logical partition within the envelope boundary, generating an adjusted multi-level envelope. This envelope adjustment rule, which is based on the dual conditions of minimum coverage of cross-domain nodes and stability of internal nodes, differs from existing single expansion or single compression methods and has the advantage of taking into account both cross-domain adaptability and partition robustness.

[0063] The integral trajectory parsing submodule parses the user's integral trajectory within the digital identity graph and maps it to the corresponding envelope level of the multi-level envelope.

[0064] In this embodiment of the invention, the integral trajectory analysis submodule includes:

[0065] 201: Traverse each user node, extract the change records of points according to the time series, and form a set of user point trajectories.

[0066] 202: Divide the user's points trajectory into segments based on points growth, decrease, or stabilization. Mark the logical partition to which each segment belongs, the corresponding range in the multi-level envelope, and the participation of cross-domain nodes within the segment to determine the landing point of the trajectory in the envelope set.

[0067] 203: Based on the segment markings, map each integral trajectory segment to the corresponding level of the multi-level envelope, mark the cross-domain node trajectories on the linked adjustment boundary segments, and output the mapping results.

[0068] For example, when a trajectory segment is within the overlapping area of ​​a cross-domain boundary, it is mapped to the adjusted boundary level; if the trajectory segment is entirely within a partition, it is mapped to the partition's internal level. For trajectories of cross-domain nodes, the boundary segments need to be marked during mapping to facilitate cross-domain conflict detection during subsequent collaborative matching.

[0069] Through this mapping, a segment-by-segment correspondence is established between the user's integral trajectory and the multi-level envelope set, providing intuitive trajectory landing points and boundary labels for subsequent collaborative processing inside and outside the partition.

[0070] The collaborative matching submodule performs integrated collaborative processing within and outside the partition in a multi-level envelope to generate matching results.

[0071] In this embodiment of the invention, the collaborative matching submodule includes:

[0072] 301: Traverse the user trajectory of each logical partition, sort the user nodes that fall in the same envelope level according to the difference of their current scores, and mark the user node pairs whose score difference does not exceed the preset score threshold and are connected by an edge in the graph as collaborative matching groups.

[0073] As can be seen, this invention combines three conditions for matching: envelope level consistency, integral difference threshold, and edge connection existence, rather than judging whether a match is possible based solely on similar integral values, thereby ensuring that the matching result has both level consistency and structural rationality.

[0074] 302: For cross-domain nodes, extract the integral trajectory segments in different logical partitions, map them to the corresponding envelope level, and generate a cross-partition collaborative adjustment scheme based on whether there is cross-partition integral overlap and boundary conflict, and output cross-partition matching information.

[0075] For example, if a large overlap of integral intervals is found between cross partitions, a cross-partition collaborative adjustment scheme is generated, such as assigning cross weights between the boundaries of two logical partitions to mark collaborative interests; if a boundary conflict is found, such as a node's trajectory increasing in partition A and decreasing in partition B, the conflict is recorded and cross-partition matching information is output.

[0076] This approach avoids simple cross-partition integration merging, emphasizes preserving differences in boundary conflicts, and explicitly marks the processing status of cross-domain nodes through scheme output.

[0077] 303: Summarize the collaborative information inside and outside the logical partition to generate the final matching result, including the integral status of each node in each logical partition and level, cross-partition collaborative identifier and envelope level.

[0078] In this embodiment of the invention, the evolution tracing module includes:

[0079] The result writing submodule writes the matching results into the digital identity graph and updates the multi-level envelope.

[0080] The chain construction submodule constructs an evolution chain based on the updated multi-level envelope and forms an integral evolution link data structure.

[0081] In this embodiment of the invention, the chain construction submodule includes:

[0082] 401: Traverse the updated multi-level envelope, associate each node at each envelope level with its corresponding logical partition and integral state, and generate a user node-envelope level mapping table.

[0083] 402: Based on the time series of the user's integral trajectory, the integral status and envelope level of each user node at different time points are recorded in the user node-envelope level mapping table to form a time series mapping, which facilitates tracing the integral change path.

[0084] 403: Traverse the user node records in the user node-envelope hierarchy mapping table, generate chain units for the envelope hierarchy changes of the same user at consecutive time points, and connect the chain units to form a complete evolution chain according to the logical partition and the association order of cross-domain nodes.

[0085] That is, if an envelope level change occurs, a chain unit is generated, and the chain units are connected in sequence according to the logical partition and cross-domain nodes to form a complete evolution chain.

[0086] All evolutionary chains are integrated to generate a unified data structure for the points evolution chain, including: identity node identifier, time period, logical partition and envelope level, points status, and cross-partition interaction identifier. This data structure is used to support full-domain tracing of points, cross-partition query, and subsequent strategy analysis.

[0087] The traceability index submodule, when an abnormal exchange occurs, completes the rights and interests traceability based on the joint location identifier and partition envelope boundary corresponding to the evolution chain.

[0088] The specific steps are as follows: Input an abnormal redemption request, retrieve the corresponding user node's evolution chain in the points evolution chain data structure based on the timestamp; locate the associated joint location identifier and partition envelope boundary in the evolution chain, extract the corresponding user node's points status and cross-domain interaction path before and after the abnormal time point, and construct an abnormal traceability report.

[0089] Furthermore, such as Figure 2 As shown, this embodiment also provides a method for intelligent matching of full-domain points-based rights and interests based on digital identity graphs, including:

[0090] S1: Collect user identity information, points records and cross-domain transaction data to form a digital identity graph, and divide the set of user nodes in the digital identity graph into logical partitions according to the source domain, and generate a partition envelope in each logical partition.

[0091] S2: Based on the partition envelope, extract cross-domain nodes existing between different logical partitions and generate a joint location identifier; the joint location identifier is used as an input parameter and labeled in the edge connection of the digital identity graph.

[0092] S3: Call the joint positioning identifier, adjust the boundary of the partition envelope in each logical partition in a coordinated manner to form a multi-level envelope, and perform collaborative matching of the points inside and outside each logical partition based on the user's points trajectory, and output the matching results.

[0093] S4: Write the matching results into the digital identity graph and update the evolution chain of the multi-level envelope accordingly; establish a traceability index for points through the evolution chain to ensure that when abnormal redemption occurs, the corresponding joint positioning identifier and partition envelope boundary can be located based on the same parameter system.

[0094] This embodiment also provides a computer device applicable to the intelligent matching system for full-domain points-based rights and interests based on digital identity graphs, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as proposed in the above embodiment.

[0095] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0096] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements the intelligent matching system for full-domain points-based rights and interests based on a digital identity graph as proposed in the above embodiments.

[0097] In summary, this invention establishes a logical partitioning and multi-level envelope structure based on user identity and points trajectory as two dimensions. This not only identifies cross-domain nodes and performs joint positioning, but also forms multi-level linkages across different partitions, overcoming the limitations of traditional points systems such as low cross-platform interoperability, rigid mapping relationships, and insufficient dynamic matching capabilities. Through a multi-level collaborative mechanism, this invention can automatically complete collaborative matching within and outside partitions based on the evolution trend of points trajectories, improving the liquidity and utilization efficiency of points resources in different scenarios. Simultaneously, by writing the matching results into a digital identity graph and constructing a complete evolutionary chain, it ensures the transparency and traceability of the points transfer process, effectively reducing the risks of abnormal redemption and resource mismatch.

[0098] Overall, this invention not only enhances the intelligent matching and dynamic adaptation capabilities of points-based benefits across the entire domain, but also provides unified technical support for cross-platform and cross-industry points interoperability.

[0099] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A comprehensive points-based intelligent matching system for rights and interests based on digital identity graphs, characterized in that: include: The digital identity construction module is used to collect user identity information, points records and cross-domain transaction data to form a digital identity graph. The user node set in the digital identity graph is divided into logical partitions according to the source domain, and a partition envelope boundary is generated in each logical partition. The joint location module is used to extract cross-domain nodes existing between different logical partitions based on the partition envelope and generate a joint location identifier; the joint location identifier is used as an input parameter and labeled in the edge connection of the digital identity graph; The multi-level coordination module is used to call the joint positioning identifier, adjust the boundary of the partition envelope in each logical partition in a coordinated manner to form a multi-level envelope, and perform coordinated matching of the points inside and outside each logical partition based on the user's points trajectory, and output the matching results. The evolutionary tracing module is used to write the matching results into the digital identity graph and update the evolutionary chain of the multi-level envelope accordingly; and to establish a tracing index for the integral through the evolutionary chain. The multi-level collaboration module includes: an envelope linkage submodule, which calls the joint positioning identifier to perform linkage adjustment on the envelope boundaries of each partition to generate a multi-level envelope; an integral trajectory parsing submodule, which parses the user's integral trajectory in the digital identity graph and maps it to the envelope level corresponding to the multi-level envelope; and a collaborative matching submodule, which performs integral collaborative processing inside and outside the partition in the multi-level envelope to generate matching results. The collaborative matching submodule includes: traversing the user nodes and integral trajectories of each logical partition; sorting user nodes falling within the same envelope level according to the difference in their current integral values; marking user nodes whose integral difference does not exceed a preset integral threshold and have edge connections as collaborative matching groups; for cross-domain nodes, extracting integral trajectory segments in different logical partitions, mapping them to the corresponding envelope levels, and generating cross-partition collaborative adjustment schemes based on whether there are cross-partition integral overlaps and boundary conflicts, and outputting cross-partition matching information; summarizing the collaborative information inside and outside the logical partitions to generate the final matching result, including the integral status of each user node in each logical partition and envelope level, cross-partition collaborative identifier, and envelope level.

2. The intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as described in claim 1, characterized in that: The digital identity construction module includes: The identity collection submodule collects user identity information, points records, and cross-domain transaction data to form an initial dataset. The graph generation submodule generates a digital identity graph based on the initial data set and maps user nodes and integral edges into a graph-based structure. The partition envelope submodule divides the set of user nodes in the digital identity graph into logical partitions according to the source domain, and generates a partition envelope in each logical partition to limit the local integration range. The nodes of the digital identity graph are user identity units, and the edges are integral flow relationships.

3. The intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as described in claim 2, characterized in that: The joint positioning module includes: a cross-domain node identification submodule, which retrieves edges connecting different logical partitions in the digital identity graph and records the corresponding user nodes as a candidate cross-domain node set; and adds nodes that exist in multiple logical partitions at the same time to the cross-domain node set; The identifier generation submodule generates joint location identifiers based on cross-domain nodes; The identification and labeling submodule labels the joint location identifiers on the edge connections of the digital identity graph; The extraction of cross-domain nodes existing between different logical partitions includes: In the digital identity graph, the edge set of logical partitions is called to retrieve the edges that connect two or more different logical partitions at the same time, and the corresponding user nodes are recorded as candidate cross-domain node sets. If a candidate cross-domain node exists in multiple logical partitions, it is added to the cross-domain node set.

4. The intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as described in claim 3, characterized in that: The envelope linkage submodule includes: Based on the joint location identifier, traverse each logical partition, filter out cross-domain nodes that are connected by edges in multiple logical partitions, and store them in the cross-domain node set; For each cross-domain node, the partition envelope boundary of the logical partition it belongs to and the partition envelope boundary of the adjacent logical partition are indexed and aligned. The overlapping area of ​​each pair of partition envelopes is calculated, and the cross-domain nodes located within and outside the overlapping area are recorded to determine the boundary segments that need to be expanded or contracted in a coordinated manner. Traverse all overlapping regions, adjust the partition envelope boundary to cover the minimum boundary range of cross-domain nodes with a preset proportion, while keeping the integral of non-cross-domain nodes within the original logical partition within the envelope boundary, and generate the adjusted multi-level envelope.

5. The intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as described in claim 4, characterized in that: The integral trajectory analysis submodule includes: Iterate through each user node and extract the change records of points according to the time series to form the user's point trajectory; The user's points trajectory is segmented according to the points growth, decrease or stable range, and each segment is marked with its logical partition, the corresponding envelope level in the multi-level envelope, and the participation of cross-domain nodes within the segment. Based on the segment markings, each integral trajectory is segmented and mapped to the corresponding level of the multi-level envelope. The integral trajectories of cross-domain nodes are marked on the boundary segments after linkage adjustment, and the mapping results are output.

6. The intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as described in claim 5, characterized in that: The evolution tracing module includes: The result writing submodule writes the matching results into the digital identity graph and updates the multi-level envelope. The chain construction submodule constructs an evolutionary chain based on the updated multi-level envelope and forms an integral evolutionary link data structure; The traceability index submodule, when an abnormal exchange occurs, completes the rights and interests traceability based on the joint location identifier and partition envelope boundary corresponding to the evolution chain.

7. The intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as described in claim 6, characterized in that: The evolutionary chain constructed based on the updated multi-level envelope includes: Traverse the updated multi-level envelope, associate the user node of each envelope level with the corresponding logical partition and integration status, and generate a user node-envelope level mapping table; Based on the time series of the user's points trajectory, the points status and envelope level of each user node at different time points are recorded in the user node-envelope level mapping table to form a time series mapping; Traverse the user node records in the user node-envelope hierarchy mapping table, generate chain units for the envelope hierarchy changes of the same user node at consecutive time points, and connect the chain units to form a complete evolution chain according to the logical partition and the association order of cross-domain nodes.

8. A method for intelligent matching of full-domain points-based rights and interests based on digital identity graphs, applied to the intelligent matching system for full-domain points-based rights and interests based on digital identity graphs as described in any one of claims 1-7, characterized in that: Also includes: Collect user identification information, points records and cross-domain transaction data to form a digital identity graph, and divide the set of user nodes in the digital identity graph into logical partitions according to the source domain, and generate a partition envelope in each logical partition. Based on the partition envelope, cross-domain nodes existing between different logical partitions are extracted to generate a joint location identifier; the joint location identifier is used as an input parameter and labeled in the edge connection of the digital identity graph. The joint positioning identifier is invoked to adjust the boundary of the partition envelope in each logical partition in a coordinated manner to form a multi-level envelope. Based on the user's points trajectory, the points inside and outside each logical partition are matched collaboratively, and the matching results are output. The matching results are written into the digital identity graph, and the evolutionary chain of the multi-level envelope is updated accordingly; a traceability index for the integral is established through the evolutionary chain.

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