Information Generation Method, Device, and Electronic Device Based on Transition Index

Abstract

Embodiments of the present disclosure disclose an information generation method, apparatus, and electronic device based on transition metrics. A specific implementation manner of this method includes: obtaining a set of business metric information for a target virtual item; for the business metric information, performing the following first processing steps: decomposing the business metrics corresponding to the business metric information into transition metrics according to the business metric information; updating the real-time metric values of the transition metrics corresponding to each transition metric information in the transition metric information group; restoring the metric values of the business metrics corresponding to the path diagram in real time according to the path diagram and the obtained updated set of transition metric information groups; generating real-time item information for the target virtual item according to the updated set of business metric information. This implementation manner effectively solves the problem that metric calculation cannot be performed in a timely and accurate manner due to computational bottlenecks.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technologies, and particularly to an information generation method, apparatus, and electronic device based on transition metrics. Background Art

[0002] In the financial industry, how to effectively and accurately manage virtual items (e.g., products with financial asset attributes) and hedge risks depends on various metrics in financial engineering for quantifying risks. For example, these metrics play a crucial role in core financial operations such as investment decision-making, position management, hedge risk analysis, financial asset allocation, risk warning, return evaluation, and strategy optimization.

[0003] However, the calculations of these metrics vary in complexity, and in addition, they may involve a large volume of data sets for participating in metric calculations. Especially when the position size is large, computing performance will become a bottleneck for real-time metric calculations, thus unable to calculate metrics timely and accurately, and further affecting the effective and accurate execution of the above operations.

[0004] The above information disclosed in this background art section is only used to enhance the understanding of the background of the inventive concept, and thus, it may include information that does not form the prior art known to those of ordinary skill in the art. Summary of the Invention

[0005] This summary of the disclosure is intended to introduce concepts in a brief form, which will be described in detail in the subsequent detailed implementation section. This summary of the disclosure is not intended to identify the key features or essential features of the claimed technical solution, nor is it intended to be used to limit the scope of the claimed technical solution.

[0006] Some embodiments of the present disclosure propose an information generation method, apparatus, and electronic device based on transition metrics to solve one or more of the technical problems mentioned in the above background art section.

[0007] In a first aspect, some embodiments of the present disclosure provide a method for generating information based on transition metrics. The method includes: obtaining a set of business metric information for a target virtual item, where the business metrics corresponding to the business metric information are metrics used to describe the state of the above-mentioned target virtual item; for each piece of business metric information in the set of business metric information, perform the following first processing step: according to the above-mentioned business metric information, decompose the business metric corresponding to the business metric information into transition metric information groups, where the transition metric information groups include: transition metric types, transition metric description information, and the transition metric types include: a first type of transition metric type and a second type of transition metric type; perform real-time metric value updates on the transition metrics corresponding to each piece of transition metric information in the above-mentioned transition metric information groups to generate updated transition metric information, obtaining an updated transition metric information group; according to a path diagram and the obtained set of updated transition metric information groups, perform real-time restoration on the metric values of the business metrics corresponding to the above-mentioned path diagram to obtain an updated set of business metric information, where the above-mentioned path diagram is a two-dimensional diagram recording at least one analysis path; according to the above-mentioned updated set of business metric information, generate real-time item information for the above-mentioned target virtual item, where the above-mentioned real-time item information includes: item description information and item recommendation information.

[0008] In a second aspect, some embodiments of the present disclosure provide an apparatus for generating information based on transition metrics. The apparatus includes: an obtaining unit configured to obtain a set of business metric information for a target virtual item, where the business metrics corresponding to the business metric information are metrics used to describe the state of the above-mentioned target virtual item; an execution unit configured to, for each piece of business metric information in the set of business metric information, perform the following first processing step: according to the above-mentioned business metric information, decompose the business metric corresponding to the business metric information into transition metric information groups, where the transition metric information groups include: transition metric types, transition metric description information, and the transition metric types include: a first type of transition metric type and a second type of transition metric type; perform real-time metric value updates on the transition metrics corresponding to each piece of transition metric information in the above-mentioned transition metric information groups to generate updated transition metric information, obtaining an updated transition metric information group; a real-time restoration unit configured to, according to a path diagram and the obtained set of updated transition metric information groups, perform real-time restoration on the metric values of the business metrics corresponding to the above-mentioned path diagram to obtain an updated set of business metric information, where the above-mentioned path diagram is a two-dimensional diagram recording at least one analysis path; a generating unit configured to, according to the above-mentioned updated set of business metric information, generate real-time item information for the above-mentioned target virtual item, where the above-mentioned real-time item information includes: item description information and item recommendation information.

[0009] In a third aspect, some embodiments of the present disclosure provide an electronic device, including: one or more processors; a storage device storing one or more programs thereon, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method described in any implementation manner of the first aspect above.

[0010] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium storing a computer program thereon, wherein when the program is executed by a processor, the method described in any implementation manner of the first aspect above is implemented.

[0011] The above - mentioned various embodiments of the present disclosure have the following beneficial effects: Through the information generation method based on transition indicators in some embodiments of the present disclosure, the problem that the indicator calculation cannot be carried out in a timely and accurate manner due to the computing bottleneck, which in turn affects the effective and accurate execution of the above - mentioned operations, is effectively solved. Specifically, the reasons for the above - mentioned problems are as follows: The complexity of indicator calculations varies, and in addition, it may also involve a large amount of data sets used for participating in indicator calculations. Especially when the position size is large, the computing performance will become the bottleneck of real - time indicator calculation. Based on this, in the information generation method based on transition indicators in some embodiments of the present disclosure, first, a set of business indicator information for a target virtual item is obtained, where the business indicators corresponding to the business indicator information are indicators used to describe the state of the above - mentioned target virtual item. Secondly, for each piece of business indicator information in the set of business indicator information, the following first processing step is performed: The first step is to decompose the business indicator corresponding to the business indicator information into transition indicators according to the business indicator information, obtaining a group of transition indicator information, where the group of transition indicator information includes: transition indicator type, transition indicator description information, and the transition indicator type includes: a first - type transition indicator type and a second - type transition indicator type. In practice, due to the complex calculation logic of business indicators, when any parameter involved in a business indicator changes, a full - volume recalculation of the business indicator will greatly increase the calculation delay. Therefore, indicator decomposition is convenient for subsequent recalculation of business indicators for the purpose of reducing calculation delay. The second step is to update the real - time indicator value of each transition indicator corresponding to the transition indicator information in the group of transition indicator information to generate updated transition indicator information, obtaining a group of updated transition indicator information. In practice, when the indicator value of a transition indicator changes, corresponding updates are made, and when the indicator value of a transition indicator does not change, no update is made. In this way, the update of local parameters is realized, which can effectively reduce subsequent calculation delay. Then, according to the path diagram and the obtained set of groups of updated transition indicator information, the indicator value of the business indicator corresponding to the path diagram is restored in real time, obtaining a set of updated business indicator information, where the above - mentioned path diagram is a two - dimensional diagram recording at least one analysis path. In practice, there are many business indicators for quantifying target virtual items, and in different scenarios, the business indicators participating in quantification are different. Therefore, by combining the path diagram and the set of groups of updated transition indicator information, the business indicators participating in quantification are restored to facilitate candidate quantification. Finally, according to the above - mentioned set of updated business indicator information, real - time item information for the above - mentioned target virtual item is generated, where the above - mentioned real - time item information includes: item description information and item recommendation information. In this way, by combining real - time updated business indicators, timely and effective description and recommendation of the target virtual item are realized. Through this method, the problem that the indicator calculation cannot be carried out in a timely and accurate manner due to the computing bottleneck, which in turn affects the effective and accurate execution of the above - mentioned operations, is effectively solved. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] In combination with the accompanying drawings and with reference to the following specific embodiments, the above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent. Throughout the drawings, the same or similar reference numerals denote the same or similar elements. It should be understood that the drawings are schematic and the elements and elements are not necessarily drawn to scale.

[0013] Figure 1 is a flowchart of some embodiments of an information generation method based on transition indicators according to the present disclosure;

[0014] Figure 2 is a schematic diagram of the tree structure of an index relationship tree;

[0015] Figure 3 is another schematic diagram of the tree structure of the index relationship tree;

[0016] Figure 4 is a schematic structural diagram of some embodiments of an information generation device based on transition indicators according to the present disclosure;

[0017] Figure 5 is a schematic structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure. Specific Embodiments

[0018] The embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.

[0019] In addition, it should be noted that for the sake of convenience of description, only parts related to the relevant invention are shown in the drawings. Without conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other.

[0020] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence relationship of the functions performed by these devices, modules or units.

[0021] It should be noted that the modifications of "one" and "plural" mentioned in the present disclosure are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly stated in the context, it should be understood as "one or more".

[0022] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are for illustrative purposes only and are not used to limit the scope of these messages or information.

[0023] The present disclosure will be described in detail below with reference to the accompanying drawings and in conjunction with embodiments.

[0024] Reference Figure 1 shows a flow 100 of some embodiments of an information generation method based on a transition index according to the present disclosure. The information generation method based on the transition index includes the following steps:

[0025] Step 101, obtaining a set of business metric information for a target virtual item.

[0026] In some embodiments, an execution entity (e.g., a computing device) of the information generation method based on the transition index may obtain a set of business metric information for a target virtual item. Among them, the business metric corresponding to the business metric information is an index used to describe the state of the above-mentioned target virtual item. In practice, the business metric information may include: metric type, metric description information, metric value, metric identifier. Among them, the metric description information can be used to describe the metric calculation logic of the business metric. The target virtual item may be a product with financial asset attributes. Products with financial asset attributes include, but are not limited to: stocks, bonds, futures, funds, options, trust products, etc. For example, the target virtual item may be "Stock A". In addition, the target virtual item may also be a combination of products with different financial asset attributes.

[0027] As an example, the above-mentioned execution entity may retrieve the business metrics corresponding to the above-mentioned target virtual item from the business metric library to obtain a set of business metric information. Among them, the business metric library is a database used to store defined business metrics. The business metric library can uniformly manage all business metrics through standardized management methods such as definition and modification. In addition, there are a large number of business metrics in the business metric library, and the number of times different business metrics are called varies. If all the business metrics in the business metric library are updated with the index value in combination with the transition index, it will consume a large amount of computing resources. In particular, when the call frequency of the business metric is extremely low, frequent updating of the index value of the business metric will cause unnecessary use of a large amount of computing resources. Therefore, the present disclosure starts from the perspective of the target virtual item and only updates the business metrics related to the target virtual item accordingly, so as to improve the use efficiency of computing resources.

[0028] It should be noted that the above computing device can be hardware or software. When the computing device is hardware, it can be implemented as a distributed cluster composed of multiple servers or terminal devices, or as a single server or a single terminal device. When the computing device is embodied as software, it can be installed in the above-listed hardware devices. It can be implemented as, for example, multiple software or software modules for providing distributed services, or as a single software or software module. Specific limitations are not made here.

[0029] Step 102: For each piece of business metric information in the set of business metric information, perform the following first processing steps, where the first processing steps include: Step 1021 and Step 1022:

[0030] Step 1021: Decompose the business metric corresponding to the business metric information into transition metric information groups according to the business metric information.

[0031] In some embodiments, the above execution entity can decompose the business metric corresponding to the business metric information into transition metric information groups according to the business metric information. Among them, the transition metric information group includes: transition metric type, transition metric description information. The transition metric type includes: a first type of transition metric type and a second type of transition metric type. Among them, the first type of transition metric type represents a business metric whose corresponding metric value can be calculated in a linear manner. The second type of transition metric type represents a business metric whose corresponding metric value can be calculated in a non-linear manner. The transition metric description information represents the metric calculation logic and metric value of the transition metric.

[0032] Example 1: Business metric A1 = Parameter B1 × Business metric A2 + Parameter B2. At this time, there is a mapping from Business metric A2 to Business metric A1 between Business metric A1 and Business metric A2. Therefore, Business metric A2 can be a transition metric of the first type of transition metric type.

[0033] Example 2: Taking the Greek letter sensitivity index (business metric) corresponding to option-like virtual products as an example, the sensitivity index generally measures the sensitivity of a system or financial instrument to changes in external environmental factors. Specifically, the Greek letter sensitivity index is a set of indicators used to measure the risks and sensitivities corresponding to financial derivatives (such as option-like virtual items). For example, the "Delta index" represents the sensitivity of the option price to changes in the price of the underlying asset. Specifically, it represents the ratio of the change in the option price to the change in the price of the underlying asset. For example, the index value of the "Delta index" of option-like virtual item A is 0.5, indicating that when the price of the underlying asset of option-like virtual item A increases by 1 yuan, the price of option-like virtual item A increases by 0.5 yuan. Therefore, the sensitivity indices are all transition metrics of the first type of transition metric type.

[0034] Example 3: Taking stress test metrics as an example, stress test metrics characterize the risk status under different simulation scenarios (such as macroeconomic shock test scenarios, market risk test scenarios, credit risk test scenarios, liquidity risk test scenarios, etc.). Specifically, taking the stress test metrics including: interest rate volatility metrics, exchange rate volatility metrics, and stock market crash metrics as examples. Among them, the interest rate volatility metric characterizes the impact on the fixed-income portfolio after changing K basis points from the current level. The exchange rate volatility characterizes the impact on the foreign exchange exposure after the exchange rate of major currencies (such as the RMB, euro, US dollar, British pound, Swiss franc, etc.) changes by M%. The stock market crash metric characterizes the loss situation of the portfolio after simulating a change of F% in the stock market index. Therefore, the above stress test metrics are all transition metrics of a type of transition metric type.

[0035] Example 4: Business metric A1 = F1 ( F2 ((Business metric A2))), at this time, there is a non-linear mapping from business metric A2 to business metric A1 between business metric A1 and business metric A2. Therefore, F2 ((Business metric A2)) can be a transition metric of a type of transition metric type. Among them, F1 () and F2 () both characterize the calculation logic. Further analysis finds that the combination of a transition metric of a type of transition metric type and a transition metric of a type of transition metric type is still a transition metric of a type of transition metric type. The combination of a transition metric of a type of transition metric type and a transition metric of a type of transition metric type is a transition metric of a type of transition metric type. The combination of a transition metric of a type of transition metric type and a transition metric of a type of transition metric type is still a transition metric of a type of transition metric type.

[0036] Example 5: Taking the value-at-risk metric as an example, among them, the value-at-risk metric measures the maximum possible loss that a financial asset (a single virtual item) or a portfolio of financial assets (multiple virtual items) may occur within a future time window at a certain confidence level. Specifically, value-at-risk metric = Percentile (({PnL})). Among them, Percentile () characterizes the specific quantile value of the loss distribution. Among them, since the value-at-risk metric has subadditivity, PnL is selected as its effective metric. The calculation of PnL can be obtained through the definition of the original metric, such as through the Monte Carlo simulation method, in order to simplify and accelerate the calculation of the value-at-risk metric. At this time, it can be considered that the value-at-risk metric is a transition metric of a type of transition metric type.

[0037] Example 6. Taking the (counterparty) credit risk exposure indicator as an example, where the (counterparty) credit risk exposure indicator is an indicator used to measure the credit risk within a specific future time period, specifically referring to the potential losses that an institution may suffer in the event of a counterparty's default. It manifests as follows: when the counterparty fails to fulfill the payment obligation stipulated in the contract, this risk will arise. For example, in the event of a default, the non-defaulting party needs to liquidate its position and further seek alternative transactions to maintain its market position, and the costs associated with this are defined as the exposure. In practice, the (counterparty) credit risk exposure includes indicators such as Expected exposure EE(t), Potential future exposure PFEa(t), Expected shortfall, etc. Among them, Expected exposure EE(t) refers to the expected value of the positive part of the expected market value of a trading portfolio or a single transaction to the counterparty at a certain future time point t. In other words, it represents the risk measure of the amount exposed to the counterparty at time point t. Potential future exposure PFEa(t) refers to the maximum potential loss generated by a trading portfolio or a single transaction to the counterparty at a certain future time point t. In other words, it represents the maximum amount that a trading party needs to pay to the counterparty under adverse but reasonable market conditions. Expected shortfall refers to the average expected loss at a given confidence level when the loss exceeds the value at risk at that confidence level. Further taking Potential future exposure PFEa(t) as an example, the Monte Carlo method can be used to simulate different scenarios and calculate the slippage to generate the (counterparty) credit risk exposure. At this time, it can be considered that the (counterparty) credit risk exposure indicator is a transition indicator of the second type of transition indicator type.

[0038] In some optional implementation manners of some embodiments, the above-mentioned execution entity decomposes the service indicator corresponding to the above-mentioned service indicator information into transition indicators according to the above-mentioned service indicator information, and obtains a group of transition indicator information, including:

[0039] First step, construct an indicator relationship tree according to the above-mentioned service indicator information.

[0040] Among them, the above-mentioned indicator relationship tree is a logical tree with the service indicator corresponding to the above-mentioned service indicator information as the root node, which represents the indicator settlement logic of the service indicator corresponding to the above-mentioned service indicator information.

[0041] As an example, the calculation logic of service indicator A corresponding to service indicator information A can be: Service indicator A1 = Parameter B1 × Service indicator A2 + Parameter B2 × Service indicator A3 + Parameter B3. The corresponding indicator relationship tree can be seen in Figure 2Schematic diagram of the tree structure of the indicator relationship tree shown.

[0042] As another example, the calculation logic of the business indicator A corresponding to the business indicator information A may be: business indicator A1= F2 ( F1 (Business indicator A2)). The corresponding indicator relationship tree can be found in Figure 3 Another tree structure diagram of the indicator relationship tree shown.

[0043] The second step is to deeply traverse the above indicator relationship tree to obtain at least one indicator relationship path.

[0044] The indicator relationship path is a path with the business indicator corresponding to the above business indicator information as the first node.

[0045] As an example, see further Figure 2 The tree structure diagram of the indicator relationship tree shown in FIG. Figure 2 The indicator relationship tree shown contains only two indicator relationship paths, namely, the first path is from "business indicator A2" to "business indicator A1". The second path is from "business indicator A3" to "business indicator A1".

[0046] As yet another example, see Figure 3 Another tree structure diagram of the indicator relationship tree shown in FIG. Figure 3 The indicator relationship tree shown contains only one indicator relationship path, namely: F1 (Business Indicator A2)” points to “Business Indicator A1”.

[0047] In the third step, for each indicator relationship path in the at least one indicator relationship path, the following second processing step is performed:

[0048] The first sub-step is to remove the first node included in the above indicator relationship path to generate an updated indicator relationship path.

[0049] As an example, Figure 2 The corresponding two updated indicator relationship paths are "business indicator A2" and "business indicator A3".

[0050] As yet another example, Figure 3 The corresponding updated indicator relationship path is " F1 (Business Indicator A2)”.

[0051] The second sub-step is to determine the transition indicator description information included in the transition indicator information corresponding to the first node in the updated indicator relationship path.

[0052] In practice, the above-mentioned execution entity may obtain the calculation logic of the indicator corresponding to the first node in the updated indicator relationship path as the transitional indicator description information.

[0053] The third sub-step: in response to the indicator types of the business indicators corresponding to the nodes other than the first node in the above-mentioned updated indicator relationship path all being a type of transitional indicator type, update the transitional indicator type included in the transitional indicator information corresponding to the first node in the above-mentioned updated indicator relationship path to a type of transitional indicator type.

[0054] The fourth sub-step: in response to the indicator types of the business indicators corresponding to the nodes other than the first node in the above-mentioned updated indicator relationship path having a second type of transitional indicator type, update the transitional indicator type included in the transitional indicator information corresponding to the first node in the above-mentioned updated indicator relationship path to a second type of transitional indicator type.

[0055] Step 1022: Perform real-time update of the indicator values of the transitional indicators corresponding to each transitional indicator information in the transitional indicator information group to generate updated transitional indicator information, and obtain an updated transitional indicator information group.

[0056] In some embodiments, the above-mentioned execution entity may perform real-time update of the indicator values of the transitional indicators corresponding to each transitional indicator information in the transitional indicator information group to generate updated transitional indicator information, and obtain an updated transitional indicator information group. In practice, the above-mentioned execution entity may perform real-time update of the indicator values of the transitional indicators corresponding to the transitional indicator information to update the indicator values included in the transitional indicator description information included in the transitional indicator information, and obtain updated transitional indicator information.

[0057] As an example, for a data processing platform such as a distributed one, there is a hardware foundation with a large memory. To improve the update speed of indicator values, the update of indicator values may be implemented in the large memory corresponding to the distributed system (to avoid the speed bottleneck caused by data exchange between memory and external storage, thereby improving the update speed). For example, the indicator value update is performed through message processing. Specifically, for example, when the indicator value is updated in the memory, an update completion message is generated to notify the update of the indicator value included in the transitional indicator description information included in the transitional indicator information. Another example is to monitor the change of the Bit position where the indicator value is located in the memory. When a change occurs, the indicator value included in the transitional indicator description information included in the transitional indicator information is updated to obtain updated transitional indicator information.

[0058] In some embodiments, the above-mentioned execution entity performs real-time update of the indicator values of the transitional indicators corresponding to each transitional indicator information in the above-mentioned transitional indicator information group to generate updated transitional indicator information, including:

[0059] First step: Create an indicator value update trigger for the transition indicator corresponding to the above transition indicator information.

[0060] Among them, the indicator value update trigger is used to monitor the change of the indicator value of the business indicator that constitutes the transition indicator.

[0061] As an example, taking " F1 (Business Indicator A2)" as an example, when the indicator value of "Business Indicator A2" changes, " F1 (Business Indicator A2)" changes accordingly, thereby triggering the indicator value update trigger.

[0062] Second step: In response to the triggering of the above indicator value update trigger, perform real-time indicator value update on the transition indicator corresponding to the above transition indicator information, so as to update the transition indicator description information included in the above transition indicator information, and obtain the updated transition indicator information corresponding to the above transition indicator information.

[0063] In practice, the above execution subject can update the indicator value included in the transition indicator description information to obtain the updated transition indicator information corresponding to the transition indicator information.

[0064] In some optional implementation manners of some embodiments, after the above execution subject performs real-time indicator value update on the transition indicator corresponding to each transition indicator information in the above transition indicator information group to generate updated transition indicator information and obtain an updated transition indicator information group, the method further includes:

[0065] First step: Obtain the virtual item identifier corresponding to the above target virtual item.

[0066] Among them, the virtual item identifier may be the unique identifier corresponding to the target virtual item.

[0067] Second step: For each updated transition indicator information in the above updated transition indicator information group, perform the following third processing step:

[0068] First sub-step: Generate transition indicator features according to the transition indicator description information included in the above updated transition indicator information.

[0069] Among them, the above transition indicator features include: transition indicator identifier and quantization feature identifier.

[0070] In practice, the transition indicator identifier is the unique identifier corresponding to the transition indicator. For example, when the transition indicator is a business indicator, the transition indicator identifier may be the business identifier corresponding to the transition indicator. When the transition indicator is a composite indicator composed of business indicators, the transition indicator identifier corresponding to the transition indicator can be reallocated. The quantization feature identifier may be the feature identifier of the preference feature.

[0071] The second sub-step is to splice the above virtual item identifier and the above transition index feature to generate a candidate string.

[0072] In practice, candidate string = virtual item identifier + transition index feature.

[0073] The third sub-step is to perform a hashing process on the above candidate string to generate a hash string.

[0074] In practice, the MD5 algorithm can be used to perform a hashing process on the above candidate string to generate a hash string. Among them, the length of the hash string is 32 bits. For example, the hash string can be "1e46db7ff54e80771611d526cf2c2c19".

[0075] The fourth sub-step is to generate a data storage tree corresponding to the above updated transition index information according to the above hash string and the updated transition index information.

[0076] In practice, the data storage tree adopts a B+ tree structure. Specifically, the hash string of each transition index and the index value included in the updated transition index information are stored in the data storage tree. In particular, the index value of the transition index is continuously updated over time, showing a time series structure. Therefore, the form of the B+ tree can well support the long-term storage and fast query of time series data.

[0077] The fifth sub-step is to generate a tree index address corresponding to the above data storage tree according to the above hash string.

[0078] In practice, although there are links between the leaf nodes of the B+ tree to speed up the query speed, there is still a certain search delay when the tree structure is complex. Therefore, a Bloom filter can be adopted on the basis of the hash string to construct an index for the data in the data storage tree to facilitate further accelerating the retrieval. Specifically, the value in the Bloom filter can quickly determine whether the corresponding data is stored in the B+ tree. When it exists, fast search can be realized through the pre-linked address.

[0079] Step 103: According to the path diagram and the obtained set of updated transition index information groups, perform real-time restoration on the index value of the business index corresponding to the path diagram to obtain a set of updated business index information.

[0080] In some embodiments, the above-mentioned execution entity may perform real-time restoration on the metric values of the service metrics corresponding to the path diagram based on the path diagram and the obtained set of updated transition metric information groups, so as to obtain a set of updated service metric information. The path diagram is a two-dimensional diagram recording at least one analysis path. In practice, since there is a calculation logic relationship between the transition metrics and the service metrics, on the basis that the transition metrics are updated, the calculation logic of the service metrics can be restored through the calculation logic between the transition metrics and the service metrics, and the metric values of the service metrics can be updated.

[0081] In some optional implementation manners of some embodiments, the above-mentioned execution entity performs real-time restoration on the metric values of the service metrics corresponding to the above-mentioned path diagram based on the path diagram and the obtained set of updated transition metric information groups, so as to obtain a set of updated service metric information, including:

[0082] The first step is to construct a multi-dimensional analysis tree for the above-mentioned target virtual item.

[0083] Among them, the multi-dimensional analysis tree may be a drill-down structure tree. In practice, a stack structure can be used to construct the multi-dimensional analysis tree, including: First, define the hierarchical structure, that is, determine that the layer structure is the drill-down element. Among them, the drill-down elements in the stack structure form a subordination relationship from the bottom to the top of the stack. Then, according to the subordination relationship between the nodes, assign the corresponding data to the drill-down elements, such as company information, department information, asset type, account information, etc. Finally, connect the nodes corresponding to the drill-down elements according to the subordination relationship to form a tree structure, and obtain the multi-dimensional analysis tree.

[0084] The second step is to determine the analysis dimensions.

[0085] Among them, the analysis dimensions may be two key dimensions set in advance. The two dimensions are derived from the root node and the leaf node of the multi-dimensional analysis tree.

[0086] The third step is to determine at least one analysis path matching the above-mentioned analysis dimensions to obtain the above-mentioned path diagram.

[0087] In practice, by means of depth-first traversal, determine the analysis path with the two dimensions included in the analysis dimensions as the root node and the end node to obtain the above-mentioned path diagram. Among them, the path diagram is stored in the form of a two-dimensional matrix, the abscissa dimension corresponds to the analysis path, and the ordinate dimension corresponds to the tree nodes included in the analysis path.

[0088] The fourth step is to perform real-time restoration on the metric values of the service metrics corresponding to the above-mentioned path diagram according to the above-mentioned path diagram and the data storage tree corresponding to the updated transition metric information, so as to obtain the above-mentioned set of updated service metric information.

[0089] In practice, according to the leaf nodes in the analysis path, the corresponding metric values in the data storage tree are located, and combined with the metric calculation logic between the business metrics and the transition metrics, the metric values of the business metrics are restored and updated to obtain the updated business metric information.

[0090] Step 104, generate real-time item information for the target virtual item according to the updated business metric information set.

[0091] In some embodiments, the above-mentioned execution entity may generate real-time item information for the target virtual item according to the updated business metric information set. Among them, the above-mentioned real-time item information includes: item description information and item recommendation information. The real-time item information table is a dynamically changing item portrait for the target virtual item. The item recommendation information is the reason for recommending the item for the target virtual item.

[0092] In some optional implementation manners of some embodiments, the above-mentioned execution entity generates real-time item information for the above-mentioned target virtual item according to the above-mentioned updated business metric information set, including:

[0093] The first step is to extract metric features from each updated business metric information in the above-mentioned updated business metric information set to generate business metric information features, and obtain a business metric information feature set.

[0094] In practice, since the metric values included in the updated business metric information are sequence-structured data, therefore, a time series model, such as an RNN (Recurrent Neural Network) model, can be used to extract metric features from each updated business metric information in the above-mentioned updated business metric information set to generate business metric information features.

[0095] The second step is to determine whether there is historical item information for the above-mentioned target virtual item.

[0096] In practice, the historical item information may be the item information corresponding to the target virtual item within the previous time window. Specifically, by determining whether the item information corresponding to the target virtual item information was generated in the previous time window, it is determined whether there is historical item information for the above-mentioned target virtual item.

[0097] The third step is to, in response to the existence, extract features from the above-mentioned historical item information to generate historical item description information features and historical item recommendation information features.

[0098] In practice, the TextRNN model can be used as the backbone network to extract features from the above historical item information, so as to generate the feature of historical item description information and the feature of historical item recommendation information. Among them, on the basis of the TextRNN model, 2 sub-recurrent neural network structures are respectively connected to output the feature of historical item description information and the feature of historical item recommendation information.

[0099] Fourth, according to the above historical item description information feature, the above historical item recommendation information feature and the above set of business indicator information features, generate the item description information and item recommendation information included in the above real-time item information.

[0100] In practice, on the basis of the time series model, the TextRNN model and the sub-recurrent neural network structure, there is a feature fusion layer connected, which is used to fuse the feature of historical item description information, the above historical item recommendation information feature and the above set of business indicator information features. Then, after the feature fusion layer, there are 2 predictors, namely the item description information predictor and the item recommendation information predictor, to output the item description information and item recommendation information included in the real-time item information respectively.

[0101] Fifth, in response to the non-existence, obtain the reference item information corresponding to the above target virtual item.

[0102] Among them, the above reference item information is the historical item information or real-time item information of virtual items of the same item type as the target virtual item.

[0103] Sixth, pull the reference item information feature corresponding to the above reference item information from the feature cache pool.

[0104] Among them, the feature cache pool is used to store the item information features corresponding to the historically generated item information. By setting up the feature cache pool, repeated calculation of features can be avoided. In addition, cache release timers are set for the item information features stored in the feature cache pool. When the cache timer is cleared, the cache space corresponding to the item information feature is released. When the item information feature is called, the corresponding cache timer is refreshed to further improve the usage efficiency of the feature cache pool. In addition, the pool space of the feature cache pool is dynamically scaled. Specifically, by setting the shrinkage coefficient and the basic cache pool size, when the occupancy rate of the feature cache pool is greater than the upper threshold, the feature cache pool is enlarged through the shrinkage coefficient and the basic cache pool size, that is, new cache resources are applied for and allocated to the feature cache pool. When the occupancy rate of the feature cache pool is less than the lower threshold, the feature cache pool is reduced through the shrinkage coefficient and the basic cache pool size, that is, part of the cache resources of the feature cache pool are released. In this way, the usage efficiency of the feature cache pool is further improved.

[0105] Step 7: Generate the item description information and item recommendation information included in the above real-time item information according to the above reference item information features and the above business indicator information feature set.

[0106] In practice, the above execution entity can perform feature fusion on the above reference item information features and the above business indicator information feature set through a feature fusion layer. Then, there are 2 predictors connected after the feature fusion layer, namely an item description information predictor and an item recommendation information predictor, to respectively output the item description information and item recommendation information included in the real-time item information.

[0107] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: Through the information generation method based on transition indicators in some embodiments of the present disclosure, the problem that the indicator calculation cannot be carried out in a timely and accurate manner due to computational bottlenecks, thereby affecting the effective and accurate execution of the above operations, is effectively solved. Specifically, the reasons for the above problems are as follows: The computational complexities of indicators vary, and in addition, it may also involve a large volume of data sets used for participating in indicator calculations. Especially when the position size is large, computational performance will become a bottleneck for real-time indicator calculations. Based on this, the information generation method based on transition indicators in some embodiments of the present disclosure first obtains a set of business indicator information for a target virtual item, where the business indicator corresponding to the business indicator information is an indicator used to describe the state of the above target virtual item. Secondly, for each piece of business indicator information in the above set of business indicator information, the following first processing step is performed: The first step is to decompose the business indicator corresponding to the above business indicator information into transition indicator information groups according to the above business indicator information, where the transition indicator information groups include: transition indicator types, transition indicator description information, and the transition indicator types include: first-class transition indicator types and second-class transition indicator types. In practice, due to the complex calculation logic of business indicators, when any parameter involved in the business indicator changes, the full recalculation of the business indicator will greatly increase the calculation delay. Therefore, indicator decomposition is convenient for subsequent recalculation of business indicators for the purpose of reducing calculation delay. The second step is to update the real-time indicator values of the transition indicators corresponding to each piece of transition indicator information in the above transition indicator information group to generate updated transition indicator information, and obtain an updated transition indicator information group. In practice, when the indicator value of the transition indicator changes, corresponding updates are made, and when the indicator value of the transition indicator does not change, no updates are made. In this way, the update of local parameters is achieved, thereby effectively reducing subsequent calculation delays. Then, according to the path diagram and the obtained set of updated transition indicator information groups, the indicator value of the business indicator corresponding to the above path diagram is restored in real time to obtain an updated set of business indicator information, where the above path diagram is a two-dimensional diagram recording at least one analysis path. In practice, there are many business indicators used to quantify target virtual items, and in different scenarios, the business indicators involved in quantification are different. Therefore, by combining the path diagram and the set of updated transition indicator information groups, the business indicators involved in quantification are restored to facilitate candidate quantification. Finally, according to the above updated set of business indicator information, real-time item information for the above target virtual item is generated, where the above real-time item information includes: item description information and item recommendation information. In this way, by combining real-time updated business indicators, timely and effective description and recommendation of target virtual items are achieved. Through this method, the problem that the indicator calculation cannot be carried out in a timely and accurate manner due to computational bottlenecks, thereby affecting the effective and accurate execution of the above operations, is effectively solved.

[0108] Further reference is made to Figure 4 , as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of an information generation device based on transition metrics, and these device embodiments correspond to Figure 1 the method embodiments shown, and the information generation device based on transition metrics can be specifically applied to various electronic devices.

[0109] As shown in Figure 4 , some embodiments of the information generation device 400 based on transition metrics include: an acquisition unit 401, an execution unit 402, a real-time restoration unit 403, and a generation unit 404. Among them, the acquisition unit 401 is configured to acquire a set of service metric information for a target virtual item, where the service metric corresponding to the service metric information is a metric for describing the state of the above target virtual item; the execution unit 402 is configured to, for each service metric information in the set of service metric information, perform the following first processing steps: decompose the service metric corresponding to the service metric information into transition metric information groups according to the service metric information, where the transition metric information groups include: transition metric types, transition metric description information, and the transition metric types include: first-class transition metric types and second-class transition metric types; update the real-time metric values of the transition metrics corresponding to each transition metric information in the transition metric information groups to generate updated transition metric information, and obtain an updated transition metric information group; the real-time restoration unit 403 is configured to, according to a path diagram and the obtained set of updated transition metric information groups, perform real-time restoration on the metric values of the service metrics corresponding to the path diagram to obtain an updated set of service metric information, where the path diagram is a two-dimensional diagram recording at least one analysis path; the generation unit 404 is configured to generate real-time item information for the target virtual item according to the updated set of service metric information, where the real-time item information includes: item description information and item recommendation information.

[0110] It can be understood that the units described in the information generation device 400 based on transition metrics correspond to the respective steps in the method described in reference to Figure 1 . Thus, the operations, features, and beneficial effects described above for the method also apply to the information generation device 400 based on transition metrics and the units included therein, and will not be elaborated herein.

[0111] Next, reference is made to Figure 5 , which shows a schematic structural diagram of an electronic device (e.g., a computing device) 500 suitable for implementing some embodiments of the present disclosure. Figure 5 The electronic device shown is merely an example and should not impose any limitations on the functions and usage scope of the embodiments of the present disclosure.

[0112] As Figure 5 shown, the electronic device 500 may include a processing device (such as a central processing unit, a graphics processing unit, etc.) 501, which may perform various appropriate actions and processes according to a program stored in the read-only memory 502 or a program loaded from the storage device 508 into the random access memory 503. In the random access memory 503, various programs and data required for the operation of the electronic device 500 are also stored. The processing device 501, the read-only memory 502, and the random access memory 503 are connected to each other through a bus 504. The input / output interface 505 is also connected to the bus 504.

[0113] Generally, the following devices may be connected to the input / output interface 505: an input device 506 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 507 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 508 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 509. The communication device 509 may allow the electronic device 500 to communicate with other devices wirelessly or wiredly to exchange data. Although Figure 5 the electronic device 500 with various devices is shown, it should be understood that it is not required to implement or have all the shown devices. More or fewer devices may be implemented or had alternatively. Figure 5 Each block shown in

[0114] particular, according to some embodiments of the present disclosure, the process described above with reference to the flowchart may be implemented as a computer software program. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes program codes for performing the method shown in the flowchart. In such some embodiments, the computer program may be downloaded and installed from the network through the communication device 509, or installed from the storage device 508, or installed from the read-only memory 502. When the computer program is executed by the processing device 501, the above functions defined in the method of some embodiments of the present disclosure are executed.

[0115] It should be noted that the computer-readable media described in some embodiments of the present disclosure may be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program, which can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted by any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0116] In some embodiments, the client and the server can communicate using any currently known or future-developed network protocol such as HTTP (Hyper Text Transfer Protocol), and can be interconnected with digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include local area networks ("LAN"), wide area networks ("WAN"), the Internet (e.g., the Internet), and end-to-end networks (e.g., ad hoc end-to-end networks), as well as any currently known or future-developed networks.

[0117] The above computer-readable medium may be included in the above electronic device; or it may exist independently without being assembled into the electronic device. The above computer-readable medium carries one or more programs. When the above one or more programs are executed by the electronic device, the electronic device is caused to: obtain a set of service metric information for a target virtual item, where the service metric corresponding to the service metric information is a metric used to describe the state of the above target virtual item; for each piece of service metric information in the set of service metric information, perform the following first processing steps: decompose the service metric corresponding to the service metric information into transition metric information groups according to the service metric information, where the transition metric information groups include: transition metric types, transition metric description information, and the transition metric types include: type-one transition metric types and type-two transition metric types; update the real-time metric values of the transition metrics corresponding to each piece of transition metric information in the transition metric information groups to generate updated transition metric information, and obtain an updated transition metric information group; according to the path diagram and the obtained set of updated transition metric information groups, restore the metric value of the service metric corresponding to the path diagram in real time to obtain an updated set of service metric information, where the above path diagram is a two-dimensional diagram recording at least one analysis path; according to the updated set of service metric information, generate real-time item information for the above target virtual item, where the above real-time item information includes: item description information and item recommendation information.

[0118] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages or combinations thereof. The above programming languages include object-oriented programming languages - such as Java, Smalltalk, C++; and also include conventional procedural programming languages - such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network - including a local area network (LAN) or a wide area network (WAN) - or may be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0119] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions noted in the blocks may occur in a different order than that noted in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, and combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0120] The units described in some embodiments of the present disclosure can be implemented in software or in hardware. The described units can also be provided in a processor. For example, it can be described as: a processor includes an acquisition unit, an execution unit, a real-time restoration unit, and a generation unit. Among them, the names of these units do not constitute a limitation on the unit itself in some cases. For example, the generation unit can also be described as "generating real-time item information for the above-mentioned target virtual item according to the above-mentioned updated set of business metric information, where the above-mentioned real-time item information includes: item description information and item recommendation information".

[0121] The functions described above can be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), and so on.

[0122] The above description is only some preferred embodiments of the present disclosure and an explanation of the technical principles applied. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, technical solutions formed by mutually replacing the above features with (but not limited to) technical features having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A method for generating information based on transition indicators, comprising: Acquire a set of business indicator information for a target virtual item, wherein the business indicator corresponding to the business indicator information is an indicator used to describe the state of the target virtual item; For each piece of business indicator information in the business indicator information set, the following first processing step is performed: According to the business indicator information, the business indicator corresponding to the business indicator information is decomposed into transition indicators to obtain a transition indicator information group, wherein the transition indicator information group includes: a transition indicator type and transition indicator description information, and the transition indicator type includes: a first-class transition indicator type and a second-class transition indicator type; Performing real-time indicator value updates on the transition indicators corresponding to each transition indicator information in the transition indicator information group to generate updated transition indicator information, thereby obtaining an updated transition indicator information group; According to the path diagram and the obtained updated transition indicator information group set, the indicator value of the business indicator corresponding to the path diagram is restored in real time to obtain the updated business indicator information set, wherein the path diagram is a two-dimensional diagram recording at least one analysis path, and the two-dimensional diagram is stored in a two-dimensional matrix, the horizontal axis dimension corresponds to the analysis path, and the vertical axis dimension corresponds to the tree nodes included in the analysis path; Generating real-time item information for the target virtual item according to the updated business indicator information set, wherein the real-time item information includes: item description information and item recommendation information; The method of restoring the indicator value of the business indicator corresponding to the path map in real time according to the path map and the updated transition indicator information group set obtained to obtain the updated business indicator information set includes: Constructing a multidimensional analysis tree for the target virtual item; Determine the dimensions of analysis; Determine at least one analysis path matching the analysis dimension to obtain the path map; According to the data storage tree corresponding to the path map and the updated transition indicator information, the indicator values ​​of the business indicators corresponding to the path map are restored in real time to obtain the updated business indicator information set.

2. The method according to claim 1, wherein: The step of performing transition indicator decomposition on the business indicator corresponding to the business indicator information according to the business indicator information to obtain a transition indicator information group includes: According to the business indicator information, construct an indicator relationship tree, wherein the indicator relationship tree is a logic tree with the business indicator corresponding to the business indicator information as a root node and representing the indicator calculation logic of the business indicator corresponding to the business indicator information; Performing a deep traversal on the indicator relationship tree to obtain at least one indicator relationship path, wherein the indicator relationship path is a path with the business indicator corresponding to the business indicator information as the first node; For each indicator relationship path in the at least one indicator relationship path, the following second processing step is performed: Eliminating the first node included in the indicator relationship path to generate an updated indicator relationship path; Determine transition indicator description information included in transition indicator information corresponding to the first node in the updated indicator relationship path; In response to the indicator types of the business indicators corresponding to the nodes other than the first node in the updated indicator relationship path being all first-class transition indicator types, updating the transition indicator type included in the transition indicator information corresponding to the first node in the updated indicator relationship path to first-class transition indicator type; In response to the existence of two types of transition indicator types in the indicator types of business indicators corresponding to nodes other than the first node in the updated indicator relationship path, the transition indicator type included in the transition indicator information corresponding to the first node in the updated indicator relationship path is updated to the second type of transition indicator type.

3. The method according to claim 2, wherein: The updating of the transition indicator corresponding to each transition indicator information in the transition indicator information group in real time to generate updated transition indicator information includes: Creating an indicator value update trigger for a transition indicator corresponding to the transition indicator information; In response to the indicator value update trigger being triggered, the transition indicator corresponding to the transition indicator information is updated in real time to update the transition indicator description information included in the transition indicator information to obtain updated transition indicator information corresponding to the transition indicator information.

4. The method according to claim 3, wherein: After updating the transition indicator corresponding to each transition indicator information in the transition indicator information group in real time to generate updated transition indicator information and obtaining the updated transition indicator information group, the method further includes: Obtaining a virtual item identifier corresponding to the target virtual item; For each updated transition indicator information in the updated transition indicator information group, the following third processing step is performed: Generate a transition indicator feature according to the transition indicator description information included in the updated transition indicator information, wherein the transition indicator feature includes: a transition indicator identifier and a quantitative feature identifier; Concatenating the virtual item identifier and the transition indicator feature to generate a candidate character string; Performing hashing on the candidate character string to generate a hash character string; Generate a data storage tree corresponding to the updated transition indicator information according to the hash string and the updated transition indicator information; A tree index address corresponding to the data storage tree is generated according to the hash character string.

5. An information generation device based on a transition indicator, comprising: An acquisition unit is configured to acquire a set of business indicator information for a target virtual item, wherein the business indicator corresponding to the business indicator information is an indicator for describing a state of the target virtual item; The execution unit is configured to perform the following first processing step for each business indicator information in the business indicator information set: according to the business indicator information, perform transition indicator decomposition on the business indicator corresponding to the business indicator information to obtain a transition indicator information group, wherein the transition indicator information group includes: a transition indicator type and transition indicator description information, and the transition indicator type includes: a first-class transition indicator type and a second-class transition indicator type; perform real-time indicator value update on the transition indicator corresponding to each transition indicator information in the transition indicator information group to generate updated transition indicator information, and obtain an updated transition indicator information group; A real-time restoration unit is configured to restore the indicator value of the business indicator corresponding to the path diagram in real time according to the path diagram and the obtained updated transition indicator information group set to obtain the updated business indicator information set, wherein the path diagram is a two-dimensional diagram recording at least one analysis path, and the two-dimensional diagram is stored in a two-dimensional matrix, the horizontal axis dimension corresponds to the analysis path, and the vertical axis dimension corresponds to the tree nodes included in the analysis path; A generating unit, configured to generate real-time item information for the target virtual item according to the updated business indicator information set, wherein the real-time item information includes: item description information and item recommendation information; Wherein, the real-time restoration unit is further configured to: Constructing a multidimensional analysis tree for the target virtual item; Determine the dimensions of analysis; Determine at least one analysis path matching the analysis dimension to obtain the path map; According to the data storage tree corresponding to the path map and the updated transition indicator information, the indicator values ​​of the business indicators corresponding to the path map are restored in real time to obtain the updated business indicator information set.

6. An electronic device comprising: one or more processors; a storage device having one or more programs stored thereon; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 4.

7. A computer readable medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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