Information resource full life cycle management platform and method

Abstract

The invention discloses an information resource full life cycle management platform and method, and belongs to the field of information technology management. The method comprises the following steps: constructing a state orientation vector for each information resource in an information resource set to represent the evolution tendency of the information resource in a preset life cycle state space; receiving a lifecycle event related to the information resource; in response to the event, matching a preset diffraction operator for the information resource; applying a diffraction operator to update the state orientation vector; calculating a final state orientation based on the updated vector and the state orientations of other information resources in the neighborhood; and according to the final state orientation, determining a target state of the information resource and executing a corresponding life cycle management operation. According to the invention, intelligence, self-adaptability and overall efficiency of information resource full-life-cycle management are improved.

Description

Technical Field

[0001] This application relates to the field of information technology management, and in particular to an information resource lifecycle management platform and method. Background Technology

[0002] In modern society, information resources have become core assets for all types of organizations. Whether it's the circulation of official documents in government departments, the management of electronic medical records in medical institutions, project documents in enterprises, or resident files in communities, all involve the full lifecycle management of a large amount of information resources. The lifecycle of information resources typically includes multiple stages such as creation, modification, approval, publication, use, archiving, and destruction.

[0003] Existing information resource management systems, such as traditional office automation (OA) systems, content management systems (CMS), or electronic record systems, typically employ a fixed-process and discrete-state-machine model when handling the information resource lifecycle. In this model, the state transitions of information resources depend on explicit user actions or predefined, rigid workflow rules. For example, a document must be manually submitted by the user to enter the "approval" state, and every node and path in the approval process is predetermined.

[0004] However, this traditional management model has several problems. For example, the system itself lacks the "foresight" or "predictiveness" of state evolution. Management operations are entirely passively triggered by external events, causing management behavior to always lag behind actual needs and making it difficult to proactively address potential risks or opportunities. For instance, it cannot proactively identify sensitive documents that are about to expire and prompt them for archiving or destruction. The fixed workflow-based model is ill-suited to complex and ever-changing business scenarios. Information resources are treated as isolated entities within the process, their state changes determined entirely by their own process node, ignoring their inherent connections with other relevant information resources. For example, the state evolution of multiple related documents in a project (such as design documents, test cases, and budget sheets) cannot achieve effective collaboration and linkage. Traditional systems focus on the management of individual information resources, lacking the ability to perceive and control the overall macro-state of the entire information resource system. The system cannot identify collective behaviors or abnormal clusters formed by a large number of information resources in the state space; for example, it cannot detect systemic bottlenecks in the approval process (a large backlog of documents in the "pending review" state), thus missing opportunities for global process optimization or risk warning. Summary of the Invention

[0005] This application aims to improve the technical problems of existing information resource management systems, which are passive, rigid, and lack a global evolution perspective.

[0006] To achieve the above objectives, this application provides the following technical solutions:

[0007] Firstly, this application provides a method for full lifecycle management of information resources. The method includes: constructing a state orientation vector for each information resource in a set of information resources, the state orientation vector representing the evolutionary tendency of the information resource in a preset lifecycle state space; receiving lifecycle events related to the information resource; responding to the lifecycle events, matching a preset diffraction operator to the information resource; applying the diffraction operator to update the state orientation vector of the information resource to generate a new state orientation vector; calculating the final state orientation of the information resource based on the new state orientation vector and the state orientation vectors of other information resources within the neighborhood of the information resource; determining the target state of the information resource in the lifecycle state space according to the final state orientation, and performing lifecycle management operations corresponding to the target state. This solution abstracts information resources into vectors with evolutionary tendencies and introduces diffraction operators and neighborhood alignment mechanisms, making the change of resource states no longer passive and isolated, but an active, collaborative, and self-organizing evolutionary process, thereby solving the fundamental defects of existing technologies.

[0008] In one possible implementation of the first aspect, the lifecycle state space includes at least two lifecycle state dimensions selected from the following: creation state, draft state, internal review state, legal review state, effective state, shared state, archived state, or destruction state.

[0009] In one possible implementation of the first aspect, the step of constructing a state orientation vector specifically includes: discretizing the lifecycle state space into an N-dimensional vector space, where N is the number of dimensions of the lifecycle state; mapping the initial state or current state of the information resource to a unit vector in the N-dimensional vector space as the state orientation vector of the information resource.

[0010] In one possible implementation of the first aspect, the diffraction operator is a transformation matrix, and the step of applying the diffraction operator to update the state orientation vector of the information resource specifically includes: combining the transformation matrix corresponding to the diffraction operator with the state orientation vector of the information resource to obtain an intermediate state orientation vector.

[0011] In one possible implementation of the first aspect, the step of calculating the final state orientation of the information resource specifically includes: obtaining the state orientation vectors of all neighboring information resources within the neighborhood of the information resource; calculating the average orientation of the state orientation vectors of all neighboring information resources; and combining the intermediate state orientation vectors of the information resource with the average orientation to generate the final state orientation.

[0012] In one possible implementation of the first aspect, the neighborhood range is determined based on at least one of the attribute similarity, business relevance, or user interaction relevance of the information resources.

[0013] In one possible implementation of the first aspect, the method further includes: introducing a random noise vector into the update process of the state orientation vector, the random noise vector being used to simulate the uncertainty disturbance in the evolution process of the information resource state.

[0014] In one possible implementation of the first aspect, the method further includes: periodically or in response to a preset triggering condition, calculating a global order parameter of the state orientation vector of all information resources in the information resource set; when the global order parameter exceeds a first preset threshold, identifying the formation of a macro-collective state and triggering a global strategy adjustment or risk warning; when the global order parameter is lower than a second preset threshold, identifying that the system is in a disordered state and triggering a strategy intervention to enhance alignment.

[0015] Secondly, this application provides an information resource lifecycle management platform, which includes functional modules for implementing the method described in the first aspect.

[0016] Thirdly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method described in the first aspect. Attached Figure Description

[0017] Figure 1 This is a flowchart illustrating a method for managing the entire lifecycle of information resources, as provided in an embodiment of this application. Detailed Implementation

[0018] The technical solutions of the embodiments of this application will be described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments.

[0019] In the following description, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0020] Furthermore, in this application, directional terms such as "upper," "lower," "left," and "right" may be defined relative to the orientation of the components shown in the accompanying drawings. It should be understood that these directional terms can be relative concepts, used for relative description and clarification, and may change accordingly depending on the orientation of the components in the accompanying drawings.

[0021] In this application, unless otherwise expressly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral part; it can be a direct connection or an indirect connection through an intermediate medium. Furthermore, the term "electrical connection" can refer to the manner in which an electrical connection is used to achieve signal transmission.

[0022] As used herein, “about,” “approximately,” or “approximately” includes the stated value and a reference value within an acceptable range of deviation from the given value, characterized in that the acceptable range of deviation is determined by a person skilled in the art taking into account the measurement under discussion and the error associated with the measurement of the given quantity (i.e., the limitations of the measurement method).

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only for explaining this application and are not intended to limit this application.

[0024] This application provides an information resource lifecycle management platform. This platform aims to overcome the shortcomings of existing information management processes, which are rigid, passive, and lack a global evolutionary perspective. By introducing a dynamic and adaptive state evolution model, it achieves intelligent management of massive information resources throughout their entire lifecycle. The core idea of ​​this platform is to abstract each information resource as a "self-driven information particle" with an inherent evolutionary tendency, and guide the entire information resource system to spontaneously and orderly manage itself through a diffraction mechanism.

[0025] The platform may include multiple logical or physical modules that work together to implement the methods described in this application. In this embodiment, the platform includes a vector construction module, an event receiving module, an operator matching module, a vector update module, an orientation calculation module, and a state execution module.

[0026] The vector construction module is used to construct a state orientation vector for each information resource in the information resource set. This vector is not a simple data label, but a mathematical representation of the evolutionary tendency of the information resource in a predefined lifecycle state space. Within the framework of this application, the lifecycle state space is a multi-dimensional abstract space, where each dimension corresponds to a key lifecycle state. The lifecycle state space covers the entire process of an information resource from its birth to its destruction, and its dimensions may include, but are not limited to, creation state, draft state, pending review state, active state, shared state, archived state, sealed state, or destroyed state. These dimensions together constitute a coordinate system in which the state of any information resource can be located and described.

[0027] For example, suppose the lifecycle state space of official document resources in a government office system can be defined as a 4-dimensional space, with each dimension corresponding to: (Draft state) (Pending review) (Active / Released), and (Archived State). The vector construction module maps a newly created document resource, initially in draft state, to a state orientation vector in this 4-dimensional space. Specifically, the vector construction module can discretize the lifecycle state space into an N-dimensional vector space, where... This refers to the number of dimensions in the lifecycle state. The current state of an information resource is mapped to an N-dimensional unit vector. For example, for the document in the draft state mentioned above, its initial state orientation vector... It can be represented as This clearly indicates that the current evolutionary trend of this resource is focused on the "draft" dimension.

[0028] The event receiving module is responsible for monitoring and capturing all lifecycle events related to information resources in real time. These events are external inputs that drive the evolution of the information resource state. The sources of events are diverse, including direct user operations (such as editing, saving, and submitting for approval), automatically triggered actions by the system (such as scheduled scans and policy checks), and interactions with other systems (such as receiving external data and responding to API calls). For example, in a medical information system, a lifecycle event could be "Doctor A modified the electronic medical record numbered XYZ" or "The system detected that medical record XYZ has not been accessed for more than 7 years."

[0029] Upon receiving a lifecycle event, the operator matching module responds to the lifecycle event by matching a preset diffraction operator to the information resource that triggered the event.

[0030] Upon receiving a lifecycle event, the operator matching module executes a refined matching process to ensure that the most suitable diffraction operator is matched for events with different business implications. In a preferred embodiment, this operator matching module can be internally implemented as a "diffraction operator selector," and its working mechanism is as follows:

[0031] This module parses the inherent attributes of received lifecycle events, including but not limited to: the event type (e.g., "process advancement," "process backtracking," or "state overlay"), the event trigger source (e.g., "user manual operation," "system automatic trigger," or "external API call"), and any additional business parameters carried by the event (e.g., the specific "rejection reason" in a rejection event). This module accesses a pre-defined "diffraction operator strategy library." This library stores a series of diffraction operator matrices in a structured manner, binding each operator to one or more sets of activation rules for event attributes. Based on the parsed event attributes, it searches the strategy library for a perfectly matching activation rule. Once a matching rule is found, the diffraction operator matrix bound to that rule is selected as the processing tool for this operation and output to the vector update module. In this way, the operator matching module accurately translates complex business logic into specific mathematical transformation operations.

[0032] The "diffraction operator" is one of the core concepts of this application. It does not directly manipulate the content of information resources, but rather serves as a mathematical transformation tool to change the "direction" of the information resource's state towards a vector. Each diffraction operator is associated with a class or a specific lifecycle event and contains management strategies and business rules.

[0033] The vector update module is responsible for performing the actual mathematical operations. It applies the diffraction operator provided by the operator matching module to update the state orientation vector of the information resource, thereby generating a new, temporary state orientation vector. Specifically, if the diffraction operator is a transformation matrix... The orientation vector of the current state of the information resource is The vector update module then calculates an intermediate state orientation vector by combining the two. For example, this combination could be a matrix multiplication operation: This new vector This reflects the ideal evolutionary direction of this isolated information resource after experiencing a specific event.

[0034] The orientation calculation module introduces the concept of collective behavior from an "information colloidal system," meaning that the state evolution of an information resource is not isolated but influenced by its "neighbors." Therefore, this module calculates the final state orientation of the information resource by combining the intermediate state orientation vector generated by the vector update module with the state orientation vectors of other information resources within its neighborhood.

[0035] This module first needs to determine the "neighborhood" of an information resource. This neighborhood is not a physical proximity, but a logical connection. The neighborhood can be determined based on at least one of the following: attribute similarity of information resources (e.g., all documents belonging to the same project), business relevance (e.g., all evidence files related to the same case), or user interaction relevance (e.g., materials frequently accessed by the same group of users). Once the neighborhood is determined, the orientation calculation module retrieves all neighboring information resources within the neighborhood (assuming it is a set). ) state orientation vectors, and calculate their average orientation. This average orientation represents the "mainstream" evolutionary trend of the local environment. Subsequently, the module will assign the intermediate state orientation vector of the information resource itself. Combined with this local average orientation, the final state orientation is generated. This combination process ensures that information resources, while following their own evolutionary logic, also maintain coordination with the surrounding environment, avoiding disorderly oscillations in the system state.

[0036] The state execution module is the endpoint of the entire process. Based on the final state orientation produced by the orientation calculation module, it determines the target state of the information resource in the lifecycle state space and executes the specific lifecycle management operations corresponding to that target state. The final state orientation vector is an N-dimensional vector, where the magnitude of each component represents the "potential energy" or "probability" of the resource evolving towards the corresponding dimensional state. The state execution module identifies the dimension with the largest component and uses it as the most appropriate target state for the information resource to migrate to. For example, if the final state orientation vector calculation result of a document is... If the target state is determined to be "active", the state execution module will then call the underlying system services to perform specific management operations, such as setting file permissions to read-only, adding a "published" watermark, moving the file to a specified directory on the public service server, and notifying relevant personnel.

[0037] Optionally, to make the model more closely resemble the complexity of the real world, this platform may also include a noise introduction mechanism. A random noise vector can be introduced during vector updates or orientation calculations. This noise vector is used to simulate the uncertainty disturbances in the evolution of information resource states.

[0038] In a preferred embodiment, the platform further includes a noise introduction module. This module can be a sub-unit of the vector update module or the orientation calculation module. Its function is to introduce a controlled random noise vector during the update process of the state orientation vector. It is used to simulate unpredictable, minute disturbances that exist in the real world, such as state deviations caused by human error or subtle changes in the external environment.

[0039] For example, this noise introduction module can be implemented as a random rotation matrix generator. Each time the final state orientation is calculated, this module generates a tiny, multidimensional random rotation matrix. This matrix represents the rotation angle. In a noise intensity hyperparameter Defined interval The internal random rotation matrix is ​​applied to the combined state orientation vector, introducing a small random deflection without significantly altering its principal direction. This effectively prevents the system from falling into rigid local optima, enhancing the robustness of the entire evolutionary model.

[0040] Furthermore, this platform may include a global status monitoring and adjustment module to achieve macro-level situational awareness and adaptive control of the entire information resource system. This module periodically (e.g., hourly) or in response to preset triggering conditions (e.g., the total number of pending tasks in the system exceeds a threshold) performs the following operations:

[0041] All in the computational information resource set The average vector of the state orientation vectors of each information resource is used, and its magnitude is taken as the global order parameter. .Right now This parameter The range of values ​​is The larger the value, the higher the overall orderliness and state consistency of the system.

[0042] Calculated With two preset thresholds—high threshold and low-bit threshold — To make comparisons.

[0043] like If the module identifies that the system may have an excessive aggregation of macro-level collective states (e.g., business process bottlenecks), it will trigger a global strategy adjustment or risk warning.

[0044] like If the module identifies that the system is in a highly disordered or chaotic state, it will trigger an intervention strategy designed to enhance alignment.

[0045] For example, suppose that in a high-load government approval system, this module detects a global order parameter. It exceeded the preset high threshold. Analysis revealed that this high degree of orderliness was due to the fact that the state orientation vectors of a large number of official documents all pointed to the "legal review state" (…). This is due to [the issue]. Accordingly, the module can automatically trigger a global policy: temporarily increase the maximum work queue capacity of users with the "Legal Review" role by 20%, and send a warning to the system administrator that "there may be a backlog risk in the legal review process."

[0046] This application also provides a method for managing the entire lifecycle of information resources. This method can run on the aforementioned platform or be implemented on any device with corresponding computing capabilities. The specific steps of this method will be described in detail below. (Refer to...) Figure 1 The method includes:

[0047] S100, Construct the state orientation vector.

[0048] This step constructs a state orientation vector for each information resource in the information resource set. Used to characterize the information resource In time Evolutionary tendencies within a predefined lifecycle state space.

[0049] The lifecycle state space It is a collection of An abstract space of orthogonal dimensions, each dimension This corresponds to a key lifecycle state.

[0050] For example, for an enterprise's internal contract management system, its lifecycle state space can be defined as follows: Dimensions, the dimensions are as follows: (Grass mimicry) (Internal review status) (Legal review status) (Pending signing) (Effective state) (Archived status) (Shared state), that is .

[0051] Subsequently, the current state of the information resource is mapped to a vector in this space. For computational convenience, it is usually mapped to a unit vector.

[0052] For example, a newly created contract has an initial state of "draft state" and its initial state orientation vector. Constructed as This means that all of its "evolutionary momentum" is directed towards drafting this state.

[0053] S200, Receive lifecycle events. Continuously monitor and receive lifecycle events related to information resources. These events are external signals that drive state evolution.

[0054] In this step, the system, as a continuously running entity, monitors and receives in real time various lifecycle events related to information resources that can drive changes in their lifecycle state. The sources and nature of these events are diverse. In this embodiment, the lifecycle events may include user-driven process advancement events, user-driven process backtracking events, system-triggered automation events, and linkage events triggered by external systems.

[0055] The user-driven process advancement events are events generated by deterministic operations performed by users on the user interface that aim to advance the lifecycle state of information resources.

[0056] For example, when a sales manager completes the drafting of "Contract A", they click the "Submit for Internal Review" button on the system interface. At this time, the system receives a process progress event associated with "Contract A". This event clearly expresses the business intention to advance "Contract A" from the "draft state" to the "internal review state".

[0057] User-driven process backtracking events are events generated by user-executed actions aimed at reverting the lifecycle state of information resources to a previous stage. These events are typically associated with rejection, cancellation, or correction phases within a process.

[0058] For example, a legal counsel, while reviewing "Contract A," discovers significant legal risks and clicks the "Reject" button on the interface. The system receives this process reversal event, which includes not only the rejection action but also the specific reasons for the rejection, such as "significant legal risks exist" or "the format does not conform to regulations." This information is crucial for choosing the appropriate handling method subsequently.

[0059] The automated events triggered by the system are automatically generated by the system's backend service based on preset business rules, time strategies, or data conditions. Their purpose is to achieve automated and intelligent management and reduce manual intervention.

[0060] For example, the system is configured with a rule: "For all contracts that are 'signed and in effect,' automatically archive them five years after their effective date." When the system detects that "Contract B" meets this condition through daily routine scanning, it will automatically generate an archiving event associated with "Contract B" internally.

[0061] The linkage events triggered by the external system are events that occur when this system is called by other independent business systems (such as customer relationship management systems or financial systems) through application programming interfaces (APIs).

[0062] For example, when the financial system updates a customer's credit rating to "high risk," the financial system can notify this contract management system via API. This system then generates a "risk identifier" linkage event for all ongoing contracts associated with that customer. This event itself may not directly change the lifecycle status of the contract, but it will affect its subsequent evolution path and approval priority.

[0063] S300, matching diffraction operator.

[0064] In response to received lifecycle events The system will match a diffraction operator for the information resource from a preset strategy library. This operator encapsulates business rules and defines the impact of events on state orientation.

[0065] In this step, the system needs to match a diffraction operator that best reflects the business implications of the lifecycle event received in S200, based on the event's inherent attributes. This is not a simple search process, but a configurable rule matching process that includes business logic, designed to achieve differentiated processing for different scenarios.

[0066] This embodiment implements this function through a "diffraction operator selector". The core of this module is to access and parse a "diffraction operator policy library". The policy library is a structured data storage that binds specific diffraction operator matrices with one or more sets of event attribute activation rules.

[0067] The workflow of the "diffraction operator selector" is as follows: when a lifecycle event is received, it analyzes the key attributes of the event. These key attributes include, but are not limited to: the type of the event (e.g., whether it is "process advancement" or "process backtracking"), the triggering source of the event (e.g., whether it is "user action" or "system automatic trigger"), and the additional business parameters carried by the event (e.g., the "rejection reason" in a rejection event).

[0068] Based on these attributes, the selector searches the policy library for an activation rule that perfectly matches them. Once a matching rule is found, the diffraction operator matrix bound to that rule is selected as the processing tool for this operation. This mechanism enables the system to exert completely different effects on events that appear similar but have different business implications.

[0069] For example, let's take the handling of "rejection" events as an example to illustrate this selection mechanism:

[0070] Scenario 1: Rejected due to significant legal risks

[0071] When the system receives a process backtracking event of type "rejection" with attached business parameters indicating that the reason for rejection is "significant legal risk," the "diffraction operator selector" will match it with a rule preset for this specific scenario in the strategy library. This rule may be bound to a severe rejection operator. This operator will completely and forcibly revert the contract's state to the initial "draft state," and may also attach a strong risk flag.

[0072] Scenario 2: Rejected due to document formatting errors

[0073] When the system receives a "rejection" event with the attached business parameters specifying the rejection reason as "document format does not meet specifications," the selector will match a different rule. The diffraction operator bound to this rule might be much milder. For example, it might simply change the status from "legal review status" (…). Return to "internal audit state" This allows submitters to quickly resubmit after formatting corrections without having to go through the entire process again. This "mild" rejection operator, in matrix form, might simply be a single... The matrix for the reverse rotation of a subplane.

[0074] Through this event-attribute-based refined matching mechanism, this invention enables the encoding of complex, multi-dimensional business logic into the selection process of diffraction operators. Examples of various operator types are as follows:

[0075] Example 1: Advancing diffraction operator (Sequential evolution of states)

[0076] This operator aims to simulate the most typical business process progression, where an information resource smoothly and deterministically moves from one stage of its lifecycle to the next. Specifically, it corresponds to the "submit for internal review" event, with the goal of changing the state from "draft" to "preliminary." ) to "internal audit status" )deflection.

[0077] This smooth transition is simulated using a two-dimensional rotation matrix. The rotation operation can change the direction of the vector from one base axis (source state) to another base axis (target state) while keeping the vector magnitude (i.e., "total energy") constant. Rotation angle. It allows for precise control over the degree of transformation, enabling either "soft" or "hard" transformation.

[0078] exist In 3D space, this operator is represented as a... The matrix for rotating a subplane.

[0079]

[0080] in, This is the rotation angle. When a complete, irreversible state switch is required, it can be set to... If the business logic allows for withdrawal under certain conditions after submission, a smaller value can be set, such as... This ensures that the new state vector still retains some components of the original state. For example, this embodiment uses... .

[0081] It should be understood that what is shown here Subplane rotation is merely an example. The principles disclosed in this invention also apply to the sequential evolution between any two adjacent or specified states in the lifecycle. For example, when an event is "Legal review approved, submit for financial review", the system will match a... A diffraction operator that performs a rotation-like operation on a subplane (or, by definition, other corresponding audit state dimensions). This is achieved by adjusting the rotation angle. It can control the "hard" or "soft" degree of state transitions, thus providing a unified and flexible mathematical modeling framework for all forward processes.

[0082] Example 2: Rejection-type diffraction operator (State backtracking)

[0083] Simulate rejection or rollback operations in the process, such as the "legal review rejection" event, requiring the status to change from "legal review status" ( Forced to revert to "draft state" ( ).

[0084] A permutation matrix can be used to directly remap vector components by exchanging rows or columns of the identity matrix, thus accurately simulating the backtracking of states.

[0085] The matrix will Dimensional input mapping to Dimensional output.

[0086]

[0087] Note that the original A row set to zero indicates a complete transition out of that state. Permutation matrices typically do not contain variable parameters; their structure itself defines definite transition rules.

[0088] Here Backtracking is another exemplary example. The principle of this permutation or reverse rotation can be widely applied to any scenario requiring state rollback. For example, a state starting from a "financial audit state" ( The case was rejected under the "legal review status" ( The event ) will have its corresponding diffraction operator constructed as a... Dimension input mapping to The output dimension is a matrix-like structure. In this way, all backtracking operations are unified into a deterministic, precisely modelable mathematical transformation.

[0089] Example 3: Shared diffraction operator (Superposition of non-mutually exclusive states)

[0090] Handling non-mutually exclusive states, such as "shared" events. A "signed and effective state" ( A contract, once shared, should possess both the attributes of "effectiveness" and "sharing." Its state should not be a transition, but rather the addition of a new state dimension to the existing state. A non-norm-preserving linear transformation is employed. This transformation, while preserving the original state components, copies or projects a portion of the "energy" onto the new state dimension. This is no longer a simple rotation or permutation.

[0091] When a is in When a vector of states passes through this operator, we expect it to... A component is obtained in the (shared state) dimension.

[0092]

[0093] It is a shared weighting factor, one between A constant. For example, Can be set to This means that when an effective contract is shared, its new state vector will be... Obtain a value in dimension The components (before normalization). This allows subsequent systems to simultaneously recognize both its "active" and "shared" identities.

[0094] The design principle of this "sharing" operator reveals the core mechanism of this invention for handling the superposition of non-mutually exclusive states, and its application is not limited to "sharing" events. Any event that requires adding a new state attribute while maintaining the original state (e.g., adding a "pinned" or "urgent" flag to an "effective" contract) can be achieved by constructing a similar non-normative transformation matrix. Simply set a suitable weighting factor at the intersection of the row corresponding to the target state dimension (e.g., "pinned state") and the column corresponding to the source state dimension. That's it. This greatly expands the ability of this invention to handle complex combinations of states.

[0095] S400, Apply the diffraction operator to update the state orientation vector.

[0096] This step is the core of performing the mathematical transformation. It involves matching a unique diffraction operator for a specific lifecycle event in S300. This step then applies it to the current state orientation vector of the information resource. The goal is to generate an intermediate state orientation vector. This intermediate vector represents the purest individual evolutionary intention of an information resource, driven solely by the event it experiences, without considering any external environmental influences.

[0097] This update process is performed using standard linear algebra operations, specifically matrix-vector multiplication. Its mathematical expression is:

[0098]

[0099] To visualize this abstract computation process, the following will continue the scenario from S300 and provide detailed examples of the application effects of different types of events and their diffraction operators.

[0100] Example Scenario 1: Applying the forward diffraction operator

[0101] The sales manager submitted a draft (or similar document) Contract A of ) has a current state orientation vector of . The system matched a forward diffraction operator to it in S300. The operator is designed to be used in Subplane A 90-degree rotation.

[0102] Calculation process:

[0103]

[0104]

[0105] The resulting intermediate state orientation vector is This result indicates that, after the "submission for internal review" event, the individual evolutionary intention of Contract A has completely and unambiguously pointed to the "internal review state" (…). ).

[0106] Example Scenario 2: Applying a strict rejection diffraction operator

[0107] After a series of procedures, "Contract A" reached the "legal review stage" (…). ), whose current vector is The legal counsel rejected it due to identified significant legal risks, and the system matched it with a stringent rejection operator in S300. The operator is designed to change the state from Forced replacement .

[0108] Calculation process:

[0109]

[0110]

[0111] The resulting intermediate state orientation vector is This precisely simulates a business scenario where the initial state is reverted, and the evolutionary intent of Contract A is forcibly reset back to its original "draft state" (or "simulated state"). All intermediate efforts are reset to zero.

[0112] Example Scenario 3: Applying Shared Diffraction Operators

[0113] Contract C has been signed and is in effect, currently in the "signed and effective" state. ), whose vector is At this point, the project manager shared it with other departments for review. The system then matched it with a shared diffraction operator. Shared weighting factor Set as .

[0114] Calculation process:

[0115]

[0116]

[0117] The resulting intermediate vector (unnormalized) is This vector maintains its original state. While keeping the quantity constant, A new component has been added to the (shared state) dimension. This indicates that the evolutionary intent of contract C is to superimpose a "shared" identity on top of maintaining the "effective" identity. Subsequent normalization operations will adjust the component size, but this multi-state coexistence characteristic will be preserved.

[0118] S500, calculate the final orientation.

[0119] This step introduces the influence of the local environment, using an alignment mechanism to smooth and coordinate state evolution. Its core technical idea is that the lifecycle evolution of information resources is not an isolated process driven solely by its own events, but rather embedded within its business context. Specifically, the "average orientation" calculated from the state orientation of other information resources in the neighborhood does not directly determine the current state of the information resource, but rather acts as a "cooperative deflection force" or "context adjustment factor." It is used to regulate and correct the evolutionary tendencies caused by the information resource's own events. When the collective state of the neighborhood aligns with the individual's evolutionary direction, it accelerates and enhances the process; when they are inconsistent, it slows down and weakens it. This allows for the proactive identification of individual behaviors that are inconsistent with the overall business situation, triggering corresponding risk warnings or dynamic priority adjustments. By introducing the concept of "cooperative deflection force," this step considers the evolution of a single information resource within its broader business context, thereby shifting from passive "process management" to proactive "situation management."

[0120] This embodiment constructs a "Business Relevance Score" (BCS) model to determine the neighborhood of information resources. Two information resources... and Business relevance between Defined as:

[0121]

[0122] in, It is a collection of key metadata fields, for example, . It is a field The corresponding weight reflects the importance of this field in measuring business relevance. The weight values ​​must meet a normalization condition, i.e. For example, it can be set , .

[0123] It is an indicator function; when the condition within the parentheses is true (i.e., information resource), it indicates that the information resource is true. and In the field When the metadata values ​​are equal, the function value is 1; when the condition is false, the function value is 0.

[0124] If and only if its business relevance score Exceeding the preset correlation threshold (For example, Can be set to ), information resources It is considered The neighbors.

[0125] The formula for calculating the final state orientation is:

[0126]

[0127] in, It is the intermediate state orientation vector obtained after the diffraction operator is applied. Information resources neighborhood In time The average state orientation. It is a random noise vector whose components are from a uniform distribution. Mid-sampling, where noise intensity Can be set to .

[0128] It is a dynamic neighborhood influence weight, the value of which depends on the neighborhood. The internal state consistency. Its calculation method is as follows:

[0129]

[0130] in, These are the basic weights, which are system hyperparameters (such as...). ).

[0131] This is the neighborhood consistency factor, which is the magnitude of the average orientation vector of the neighborhood. The range of this factor is... When all neighbors in the neighborhood have the same direction, The weight is the largest; when the directions cancel each other out completely randomly, It has the smallest weight.

[0132] In this application, the stated The function represents the vector normalization operation. This operation aims to transform a non-zero vector of arbitrary length into a unit vector with the same direction but a Euclidean norm (i.e., modulus or length) of 1.

[0133] Specifically, for an arbitrary N-dimensional vector The normalization operation calculation process includes:

[0134] 1. Calculate vectors model ;

[0135] 2. Convert the vector Each component Divide all by their modulus The normalized vector is obtained. .

[0136] In the technical solution of this invention, the normalization operation is performed to ensure that, after each iteration of calculation, the generated final state orientation vector is correct. It is always a unit vector. This maintains the mathematical consistency of the "state orientation vector" as a purely directional representation and ensures the stability and logical self-consistency of the model during its continuous evolution.

[0137] For example, let the noise intensity be... Radius. After calculating the combined vector of the intermediate vector and the average orientation of the neighborhood, the system generates a random angle. And perform an angle-wise rotation on the combined vector in a randomly selected two-dimensional subplane. The tiny rotations are used as a noise application process. For example, a pre-normalized vector pointing to the "internal audit state" is determined. It may become after noise is applied. This, while maintaining its main evolutionary trend, endows it with a small degree of uncertainty that is more in line with reality.

[0138] Scenario 1: Business scenario of collaborative acceleration

[0139] Contract A was submitted for review. Its neighbors, "Technical Specifications C" and "Quotation D", are both under "internal review".

[0140] Neighborhood state evaluation and calculation:

[0141] .

[0142] The average orientation of the neighborhood indicates that the project's business context is highly mature and healthy. Therefore .but:

[0143]

[0144] Strong neighborhood cooperation reinforces the evolutionary trend, and the final state purely points to the "internal audit state".

[0145] Scenario 2: Business scenarios with risks and delayed collaboration

[0146] Contract A was submitted for review. However, its neighbors C and D are still in the "grass mimicry" state.

[0147] Neighborhood state evaluation and calculation:

[0148]

[0149] The average orientation of the neighborhood constitutes a strong warning sign, indicating that the project is unstable. Therefore .

[0150]

[0151]

[0152]

[0153] Although the main direction of the final evolutionary tendency remains However, its weight was weakened, and in It carries significant weight, accurately capturing the conflict between individual intentions and the collective situation.

[0154] S600: Determine the target status and perform management operations.

[0155] This step is the decision-making and execution phase of the entire evolutionary process. The system analysis calculates the final state orientation vector in S500. It determines the target state it points to and triggers a series of automated lifecycle management operations bound to that target state.

[0156] Typically, the target state identified as The dimension with the largest numerical component. Its determination is given by the following rules:

[0157]

[0158] in, It is the nth direction vector of the final state Each component. Once the target state is determined, the system will invoke the underlying services to execute the corresponding atomic operations.

[0159] The following will elaborate on the execution process of this step, based on two typical business scenarios described in S500:

[0160] Scenario 1 Execution: Handling the "Collaboration Acceleration" business scenario

[0161] In the S500 "cooperative acceleration" scenario, due to the highly mature neighborhood environment of Contract A, the calculated final state orientation vector is... .

[0162] The system performs the argmax operation on the vector and identifies the dimension with the largest component (value 1) as the second dimension. Therefore, the system determines that the target state of contract A is "internal review state".

[0163] Subsequently, the system automatically executes the standard atomic operations bound to the "internal audit state," including but not limited to:

[0164] Update the status label of Contract A document to "Under Internal Review".

[0165] Lock the document to prevent the original submitter from editing it, in order to ensure the consistency of the reviewed content.

[0166] Through the internal messaging system, a new approval task is pushed to the "internal review" role pool or the task queue of a designated person, along with an access link to Contract A.

[0167] The management log of Contract A records in detail the event, time, and final status of this status change.

[0168] Scenario 2 Execution: Handling the business risk scenario of "collaboration delays"

[0169] In the "cooperative hysteresis" scenario of S500, due to the immaturity of the neighborhood environment of contract A, the calculated final state orientation vector is... .

[0170] The system first performs the argmax operation again, determining that the dimension with the largest component (approximately 0.82) is still the second dimension. Therefore, the target state of Contract A is nominally still defined as "internal review state" and will execute the standard atomic operations in Scenario 1 above (such as updating tags, pushing tasks, etc.).

[0171] However, the advantage of this invention lies in the fact that the system does not stop there. It further analyzes the complete component characteristics of the vector and performs more advanced management operations linked to situational awareness based on this. Specifically, the system detects... In the first dimension ( The model has a significantly non-zero component (value approximately 0.57) on the (draft) form. This component is interpreted by the model as a strong risk signal of "immaturity" or "should be reverted".

[0172] Based on this risk signal, the system will trigger additional dynamic adjustment and early warning operations:

[0173] A risk warning is triggered, and a system alert is automatically sent to the submitter and project manager of Contract A: "Note: Key documents associated with this contract (such as technical specifications and quotations) are not yet ready or are in a rejected state. The approval process for this submission may be delayed or rejected. Please check in time."

[0174] The system dynamically adjusts priorities, automatically setting the initial priority of this approval task to "low" in the task queue of the "Internal Review" department. Simultaneously, a monitoring link is established to track when the status of neighboring documents evolves to a more mature stage (e.g., the average orientation of the neighboring documents changes). Consistency factor If the threshold is exceeded, the priority of the task will be automatically increased.

[0175] Through the iterative processes from S100 to S600, combined with this refined execution strategy based on the complete characteristics of the final state orientation vector, this method enables the entire information resource system to exhibit a dynamic, self-organizing, and risk-self-regulating evolutionary behavior. The state transitions of each resource are no longer isolated and predetermined, but rather a result of a combination of its own event-driven processes and the influence of its local environment. This achieves refined and intelligent management of the entire lifecycle of complex information systems.

[0176] S700 performs global status monitoring and adjustment.

[0177] In addition to the lifecycle evolution cycle (S200-S600) for individual information resources, this method also includes a macro-level monitoring and adjustment cycle for the entire system. This step can be configured to be executed periodically or triggered by specific events.

[0178] S710, Calculate the global order parameter.

[0179] The system iterates through all information resources in the current time set. Each information resource is used to obtain its respective state orientation vector. Subsequently, the arithmetic mean of all vectors is calculated, and the Euclidean norm (modulus) of this average vector is taken as the global order parameter to measure the macroscopic order of the system. .

[0180]

[0181] S720: Analyze the macro-level situation of the system and implement adjustment strategies.

[0182] The calculated global order parameter The system is compared with a preset threshold to determine the system status and execute the corresponding global adjustment strategy.

[0183] For example, suppose there is an enterprise project management system containing 10,000 information resources, and a high threshold is set. Low threshold .

[0184] Scenario 1: System bottleneck identified.

[0185] One afternoon, the system calculated Further analysis revealed that over 90% of the resource vectors were highly aligned to the "internal audit state" ( ).because The system detected a systemic bottleneck in the "internal review" process. Subsequently, the system executed a pre-set global adjustment strategy: automatically sending a system notification to all project manager role groups: "The current internal review process is busy; newly submitted review tasks are expected to experience longer waiting times. Please manage your work accordingly."

[0186] Scenario 2: System disorder is detected.

[0187] At the beginning of the quarter, a large number of new projects are launched, and document statuses are scattered across multiple early stages such as "draft" and "internal review," with no complete correlation established. At this time, the system calculates... .because The system determined that it was in a highly disordered state. To guide the system to quickly form an orderly collaborative workflow, the system implemented an intervention strategy: for the next 24 hours, the influence weights of all neighboring domains in S500 were temporarily adjusted. Basic weights From the default Upgraded to This enhances collective alignment and accelerates the system's evolution from chaos to order.

[0188] Those skilled in the art will understand that the above embodiments are illustrative and not restrictive. Various modifications of form and detail can be made without departing from the spirit and scope of this application, and all such modifications should fall within the protection scope of this application. For example, the specific form of the diffraction operator, the definition of the neighborhood, and the calculation formula for the final orientation can all be adjusted and optimized according to specific application scenarios. Furthermore, the platform and method described in this application can be applied to various fields requiring information resource management, such as government offices, medical information systems, enterprise knowledge bases, project management, and smart community archive management.

[0189] Through the above description of the embodiments, those skilled in the art can clearly understand that, for the sake of convenience and brevity, only the division of the above functional modules is used as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above.

[0190] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another apparatus, or some features may be ignored or not executed. Furthermore, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0191] The units described as separate components may or may not be physically separate. A component shown as a unit can be one physical unit or multiple physical units; that is, it can be located in one place or distributed in multiple different places. Depending on actual needs, some or all of the units can be selected to achieve the purpose of this embodiment.

[0192] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit described above can be implemented in hardware.

[0193] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A method for managing the entire lifecycle of information resources, characterized in that, The method includes: For each information resource in the information resource set, a state orientation vector is constructed, which represents the evolution tendency of the information resource in a preset life cycle state space. Receive lifecycle events related to the information resource; In response to the lifecycle event, a preset diffraction operator is matched to the information resource; The diffraction operator is applied to update the state orientation vector of the information resource to generate a new state orientation vector; Based on the new state orientation vector and the state orientation vectors of other information resources within the neighborhood of the information resource, the final state orientation of the information resource is calculated. Based on the final state orientation, determine the target state of the information resource in the lifecycle state space, and perform lifecycle management operations corresponding to the target state.

2. The method according to claim 1, characterized in that, The lifecycle state space includes at least two lifecycle state dimensions selected from the following: draft state, internal review state, legal review state, pending signature state, effective state, archived state, and shared state.

3. The method according to claim 1, characterized in that, The step of constructing a state orientation vector specifically includes: The lifecycle state space is discretized into an N-dimensional vector space, where N is the number of dimensions of the lifecycle state. The initial or current state of the information resource is mapped to a unit vector in the N-dimensional vector space, which serves as the state orientation vector of the information resource.

4. The method according to claim 1, characterized in that, The diffraction operator is a transformation matrix, and the step of applying the diffraction operator to update the state orientation vector of the information resource specifically includes: The transformation matrix corresponding to the diffraction operator is combined with the state orientation vector of the information resource to obtain an intermediate state orientation vector.

5. The method according to claim 1 or 4, characterized in that, The step of calculating the final state orientation of the information resource specifically includes: Obtain the state orientation vectors of all neighboring information resources within the neighborhood of the information resource; Calculate the average orientation of the state orientation vectors of all neighboring information resources; The intermediate state orientation vector of the information resource is combined with the average orientation to generate the final state orientation.

6. The method according to claim 5, characterized in that, The neighborhood range is determined based on at least one of the following: attribute similarity, business relevance, or user interaction relevance of the information resources.

7. The method according to claim 1, characterized in that, The method further includes: A random noise vector is introduced into the update process of the state orientation vector. The random noise vector is used to simulate the uncertainty disturbance in the evolution process of information resource state.

8. The method according to claim 1, characterized in that, The method further includes: Periodically or in response to preset triggering conditions, calculate the global order parameter of the state orientation vector of all information resources in the information resource set; When the global order parameter exceeds the first preset threshold, the formation of the macro-collective state is identified, and a global strategy adjustment or risk warning is triggered. When the global order parameter is lower than the second preset threshold, the system is identified as being in a disordered state, and a strategy intervention to enhance alignment is triggered.

9. An information resource lifecycle management platform, characterized in that, The platform includes: The vector construction module is used to construct a state orientation vector for each information resource in the information resource set. The state orientation vector represents the evolution tendency of the information resource in a preset life cycle state space. An event receiving module is used to receive lifecycle events related to the information resource; The operator matching module is used to match a preset diffraction operator for the information resource in response to the lifecycle event; The vector update module is used to apply the diffraction operator to update the state orientation vector of the information resource to generate a new state orientation vector; An orientation calculation module is used to calculate the final state orientation of the information resource based on the new state orientation vector and the state orientation vectors of other information resources within the neighborhood of the information resource. The state execution module is used to determine the target state of the information resource in the lifecycle state space based on the final state orientation, and to perform lifecycle management operations corresponding to the target state.

10. A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in any one of claims 1 to 8.

Images