Intangible asset management method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides an intangible asset management method and device, electronic equipment and a storage medium. The method comprises the steps of performing vectorization processing on obtained asset data information of intangible assets in an enterprise based on a word segmentation vectorization algorithm, and constructing an asset data model of the intangible assets; based on a technical factor method, performing financial index evaluation on the asset use state parameters of the intangible assets to obtain asset financial rating indexes of the intangible assets; performing model analysis on the asset data model according to the asset financial rating index, and predicting to obtain future asset value trend information of the intangible assets; and performing system management on the intangible assets based on the future asset value trend information. According to the embodiment of the invention, an intangible asset off-network evaluation standard can be effectively established, the intangible assets can be split and disposed according to functions, the tracking in-place rate of the intangible assets is improved, the accounting cost is reduced, and the value of fixed assets is quickly released.

Description

Technical Field

[0001] The present application relates to the field of asset management technology, and in particular to an intangible asset management method, device, electronic device and storage medium. Background Art

[0002] The proportion of software intangible assets such as IT (Internet Technology) systems and platforms in total assets increases year by year. Software updates and iterations are fast. The status of software and internal modules is accurately grasped, and intelligent inventory is implemented to check the degree of automation and work efficiency. Timely disposal and scrapping of retired software and modules is conducive to enterprises converting assets into cash flow, improving corporate performance and reducing waste.

[0003] The data asset management system contains the system, database, table, and field information of intangible assets, including project acceptance and audit status. The data management platform contains the execution of the classification and grading tasks of intangible assets, including the results of monthly data scanning and verification. In the asset management system, the intangible assets are marked with the corresponding relationship of the data asset management system and the corresponding relationship of the data management platform. By collecting the project acceptance and audit status in the data asset management system and the monthly verification results in the data management platform, it can be confirmed that the intangible assets are in use and active, achieving the effect of automatic inventory.

[0004] At present, when an enterprise conducts an inventory of its intangible assets, it is usually necessary to arrange relevant personnel to conduct the inventory. This inventory method has problems such as the lack of connection between technical management and financial management, incomplete cost accounting, and inadequate follow-up tracking management, and it is impossible to quickly release the value of fixed assets. Summary of the invention

[0005] The technical problem to be solved by the embodiments of the present application is to provide an intangible asset management method, device, electronic device and storage medium, so as to effectively establish an intangible asset delisting evaluation standard, split and dispose of intangible assets according to their functions, improve the tracking rate of intangible assets, reduce accounting costs, and quickly release the value of fixed assets.

[0006] In a first aspect, an embodiment of the present application provides an intangible asset management method, the method comprising:

[0007] Vectorizing the acquired asset data information of the intangible assets within the enterprise based on a word segmentation vectorization algorithm to construct an asset data model of the intangible assets;

[0008] Based on the technical factor method, a financial index evaluation is performed on the asset usage status parameters of the intangible asset to obtain the asset financial rating index of the intangible asset;

[0009] Performing model analysis on the asset data model according to the asset financial rating index to predict and obtain future asset value trend information of the intangible asset;

[0010] The intangible assets are systematically managed based on the future asset value trend information.

[0011] Optionally, the vectorization processing of the acquired asset data information of the intangible assets of the enterprise based on the word segmentation vectorization algorithm to construct an asset data model of the intangible assets includes:

[0012] Obtaining asset data information of intangible assets within the enterprise;

[0013] Splitting the asset data information based on a plurality of preset step sizes to obtain split asset phrases of the intangible assets;

[0014] Using the word segmentation vectorization algorithm to search for the phrase vector corresponding to the split asset phrase from a preset word library;

[0015] Performing recognition processing on the phrase vector to obtain asset keywords of the intangible asset;

[0016] The asset keywords and the asset data information are stored according to a preset mapping relationship to construct an asset data model of the intangible asset.

[0017] Optionally, the financial index evaluation of the asset usage status parameters of the intangible asset based on the technical factor method to obtain the asset financial rating index of the intangible asset includes:

[0018] A multi-process concurrent collection method is adopted to collect asset usage information of intangible assets in the enterprise in multiple dimensions;

[0019] Evaluate the usage status of the intangible asset based on asset usage information in multiple dimensions to obtain asset usage status parameters of the intangible asset;

[0020] The technical factor method is used to perform a financial index evaluation on the asset usage status parameters to obtain the asset financial rating index of the intangible asset.

[0021] Optionally, the use of the technical factor method to perform a financial index evaluation on the asset usage status parameter to obtain the asset financial rating index of the intangible asset includes:

[0022] Initializing the asset usage status parameter to obtain an initialization status parameter;

[0023] The initialization state parameters are stored in a one-dimensional array according to a set order to generate an asset state parameter array;

[0024] Processing the historical output value of the intangible asset and the asset status parameter array according to a first preset algorithm to obtain a net output technical factor of the intangible asset;

[0025] Processing the asset status parameter array according to a second preset algorithm to obtain a variance distribution technical factor of the cumulative asset investment of the intangible asset;

[0026] The financial index of the intangible asset is evaluated based on the net output technical factor and the variance distribution technical factor to obtain the asset financial rating index.

[0027] Optionally, performing model analysis on the asset data model according to the asset financial rating index to predict future asset value trend information of the intangible asset includes:

[0028] Performing model analysis on the asset data model based on the asset financial rating index of the intangible asset to obtain an asset life cycle index of the intangible asset;

[0029] Based on the asset life cycle index, a future asset value trend graph of the intangible asset is drawn, and the future asset value trend graph is used as future asset value trend information of the intangible asset.

[0030] Optionally, the systematic management of the intangible assets based on the future asset value trend information includes:

[0031] Performing data inventory verification on the intangible assets based on the future asset value trend information of the intangible assets and the asset financial rating index of the intangible assets to obtain asset inventory verification results;

[0032] Performing asset processing on the intangible assets based on the asset inventory verification results;

[0033] Generating an asset card of the intangible asset based on the future asset value trend information of the intangible asset and the asset financial rating index of the intangible asset;

[0034] The asset card, the asset inventory verification result and the asset number information of the intangible asset are associated and stored in an asset database.

[0035] In a second aspect, an embodiment of the present application provides an intangible asset management device, the device comprising:

[0036] An asset data model building module is used to vectorize the asset data information of the intangible assets of the enterprise obtained based on a word segmentation vectorization algorithm to build an asset data model of the intangible assets;

[0037] An asset rating index acquisition module is used to perform a financial index evaluation on the asset usage status parameters of the intangible asset based on a technical factor method to obtain an asset financial rating index of the intangible asset;

[0038] An asset value trend acquisition module is used to perform model analysis on the asset data model according to the asset financial rating index, and predict the future asset value trend information of the intangible asset;

[0039] The intangible asset management module is used to systematically manage the intangible assets based on the future asset value trend information.

[0040] Optionally, the asset data model building module includes:

[0041] An asset data information acquisition unit, used to acquire asset data information of intangible assets within the enterprise;

[0042] A split asset phrase acquisition unit, configured to split the asset data information based on a plurality of preset step sizes to obtain split asset phrases of the intangible assets;

[0043] A phrase vector acquisition unit, used to use the word segmentation vectorization algorithm to search for the phrase vector corresponding to the split asset phrase from a preset word library;

[0044] A keyword vector acquisition unit, used to perform recognition processing on the phrase vector to obtain asset keywords of the intangible asset;

[0045] The asset data model construction unit is used to store the asset keywords and the asset data information according to a preset mapping relationship to construct an asset data model of the intangible asset.

[0046] Optionally, the asset rating index acquisition module includes:

[0047] An asset usage information collection unit, used to collect asset usage information of the intangible assets in the enterprise in multiple dimensions by using a multi-process concurrent collection method;

[0048] An asset status parameter acquisition unit, used to evaluate the usage status of the intangible asset based on asset usage information in multiple dimensions to obtain asset usage status parameters of the intangible asset;

[0049] The asset rating index acquisition unit is used to use the technical factor method to perform financial index evaluation on the asset usage status parameters to obtain the asset financial rating index of the intangible asset.

[0050] Optionally, the asset rating index acquisition unit includes:

[0051] An initial state parameter acquisition subunit is used to initialize the asset usage state parameter to obtain the initialization state parameter;

[0052] An asset parameter array generation subunit, used to store the initialization state parameters in a one-dimensional array according to a set order, and generate an asset state parameter array;

[0053] A first technical factor acquisition subunit is used to process the historical output value of the intangible asset and the asset status parameter array according to a first preset algorithm to obtain the net output technical factor of the intangible asset;

[0054] A second technical factor acquisition subunit is used to process the asset status parameter array according to a second preset algorithm to obtain a variance distribution technical factor of the cumulative asset investment of the intangible asset;

[0055] The asset rating index acquisition subunit is used to evaluate the financial index of the intangible asset based on the net output technical factor and the variance distribution technical factor to obtain the asset financial rating index.

[0056] Optionally, the asset value trend acquisition module includes:

[0057] An asset life cycle index acquisition unit, used to perform model analysis on the asset data model based on the asset financial rating index of the intangible asset to obtain the asset life cycle index of the intangible asset;

[0058] The asset value trend acquisition unit is used to draw a future asset value trend chart of the intangible asset based on the asset life cycle index, and use the future asset value trend chart as the future asset value trend information of the intangible asset.

[0059] Optionally, the intangible asset management module includes:

[0060] An asset inventory result acquisition unit, used to perform data inventory verification on the intangible assets based on the future asset value trend information of the intangible assets and the asset financial rating index of the intangible assets, and obtain an asset inventory verification result;

[0061] An asset processing unit, configured to perform asset processing on the intangible assets based on the asset inventory verification result;

[0062] An asset card generating unit, configured to generate an asset card of the intangible asset based on the future asset value trend information of the intangible asset and the asset financial rating index of the intangible asset;

[0063] The asset information storage unit is used to associate and store the asset card, the asset inventory verification result and the asset number information of the intangible asset in an asset database.

[0064] In a third aspect, an embodiment of the present application provides an electronic device, including:

[0065] A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, any of the above-mentioned intangible asset management methods is implemented.

[0066] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute any of the intangible asset management methods described above.

[0067] Compared with the prior art, the embodiments of the present application have the following advantages:

[0068] In an embodiment of the present application, the asset data information of the intangible assets in the enterprise obtained is vectorized based on the word segmentation vectorization algorithm to construct an asset data model of the intangible assets. Based on the technical factor method, the asset usage status parameters of the intangible assets are evaluated by financial index to obtain the asset financial rating index of the intangible assets. The asset data model is analyzed according to the asset financial rating index to predict the future asset value trend information of the intangible assets. Intangible assets are systematically managed based on future asset value trend information. By constructing an asset data model of intangible assets, the embodiment of the present application evaluates the financial index of intangible assets based on the asset usage status, and predicts the future value trend of intangible assets, it is possible to effectively establish an intangible asset delisting evaluation standard, split and dispose of intangible assets according to their functions, improve the tracking rate of intangible assets, and reduce accounting costs and quickly release the value of fixed assets compared to manual inventory.

[0069] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] Figure 1 A flowchart of the steps of an intangible asset management method provided in an embodiment of the present application;

[0071] Figure 2 A schematic diagram of an asset data splitting process provided in an embodiment of the present application;

[0072] Figure 3 A schematic diagram of a concurrent phrase comparison process provided in an embodiment of the present application;

[0073] Figure 4 A schematic diagram of an asset data collection process provided in an embodiment of the present application;

[0074] Figure 5 A schematic diagram of trends in different probability intervals provided in an embodiment of the present application;

[0075] Figure 6 A schematic diagram of a business system architecture provided in an embodiment of the present application;

[0076] Figure 7 A schematic diagram of the structure of an intangible asset management device provided in an embodiment of the present application;

[0077] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0078] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0079] The terms used in the embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to limit the present application. The singular forms "a", "said" and "the" used in the embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates other meanings.

[0080] Reference Figure 1 , shows a flowchart of the steps of an intangible asset management method provided by an embodiment of the present application, such as Figure 1 As shown, the intangible asset management method may include: step 101, step 102, step 103 and step 104.

[0081] Step 101: vectorize the acquired asset data information of the intangible assets within the enterprise based on a word segmentation vectorization algorithm to construct an asset data model of the intangible assets.

[0082] In this embodiment, intangible assets refer to identifiable non-monetary assets without physical form. Intangible assets are identifiable non-monetary assets without physical form. They include social intangible assets, such as patents, trademarks, copyrights, etc., as well as natural intangible assets, such as natural resources such as natural gas that do not have physical form.

[0083] When managing intangible assets, the asset data information of the intangible assets in the enterprise can be obtained, and the asset data information of the intangible assets can be vectorized using a word segmentation vectorization algorithm, thereby constructing an asset data model of the intangible assets. The implementation process can be described in detail in conjunction with the following specific implementation methods.

[0084] In a specific implementation of the present application, the above step 101 may include:

[0085] Sub-step A1: Obtain asset data information of intangible assets within the enterprise.

[0086] In this embodiment, when performing intangible asset management, the asset data information of the intangible assets in the enterprise can be obtained. The classification of asset data information includes application system name, project name, small and micro achievements, patents, trade secrets, intellectual property rights, technology research and development, etc.

[0087] After acquiring the asset data information of the intangible assets within the enterprise, execute sub-step A2.

[0088] Sub-step A2: splitting the asset data information based on a plurality of pre-set step sizes to obtain split asset phrases of the intangible assets.

[0089] After acquiring the asset data information of the intangible assets in the enterprise, the asset data information can be split based on a plurality of pre-set steps to obtain split asset phrases of the intangible assets.

[0090] For example, the asset data information obtained may be: "Intangible Asset Management System", "202302", "172.*.*.*".

[0091] Split the first element of the basic data. Split it using the built-in splitting algorithm of the basic system. The initial step size of the splitting setting is 2. Based on the step size information and the maximum length of the phrase, the storage format after splitting with different step sizes is shown in the following table:

[0092] Table 1: Data splitting results with a step size of 2

[0093] — 0 1 2 i 0 none shape 1 Funding Produce 2 Tube reason j Tie System

[0094] Table 2: Data splitting results with a step size of 3

[0095] — 0 1 2 i 0 none shape Funding 1 Produce Tube reason 2 Tie System j

[0096] Table 3: Data splitting results with a step size of 4

[0097] — 0 1 2 i 0 none shape Funding Produce 1 Tube reason Tie System 2 j

[0098] The split array is stored in "row priority order", a[i][j] is an element of A, and the split words are stored in an array, where i is the row and j is the column.

[0099] It can be understood that the above Tables 1, 2 and 3 are only three splitting methods listed for a better understanding of the technical solution of the embodiment of the present application. In a specific implementation, other step-size splitting methods can also be used to split the asset data information. This embodiment does not limit the splitting method.

[0100] After the asset data information is split based on a plurality of pre-set step sizes to obtain split asset phrases of the intangible assets, sub-step A3 is executed.

[0101] Sub-step A3: using the word segmentation vectorization algorithm to search for the phrase vector corresponding to the split asset phrase in a preset vocabulary.

[0102] After the asset data information is split based on multiple pre-set step sizes to obtain the split asset phrases of the intangible assets, the word segmentation vectorization algorithm can be used to find the phrase vector corresponding to the split asset phrase from the preset word library. That is, the word library comparison method: the word library comparison is performed based on the phrases after being split with multiple different step sizes. The phrase a[i][j] obtained in the previous step is matched with the system's built-in word segmentation vectorization algorithm. Load a[i][j] into memory, and the concurrent pipeline handler scans the data. The system will generate the word vector length N that needs to be concurrent based on the step size, and generate threads based on the N value for multi-process scanning. The word vector of the central word is calculated using the words a[i-1] and a[i+1] before and after a[i] in the array row, and i*j is the dictionary length.

[0103] The data splitting comparison and search method can be as follows Figure 2 As shown, the input is the asset data information of the intangible asset, and the intangible asset data information is split into several asset phrases. Then, the word library comparison method can be used to sequentially search for vector representations corresponding to different asset phrases from word library 1, word library 2, word library 3, ... as output.

[0104] Sub-step A4: performing recognition processing on the phrase vector to obtain asset keywords of the intangible asset.

[0105] After obtaining the phrase vector corresponding to the split asset phrase, the phrase vector can be identified to obtain the asset keyword of the intangible asset. In this example, the asset keyword can be the intangible asset name of the intangible asset.

[0106] Sub-step A5: storing the asset keywords and the asset data information according to a preset mapping relationship, and constructing an asset data model of the intangible asset.

[0107] Finally, the asset keywords of the intangible assets and the asset data information of the intangible assets can be stored according to the preset mapping relationship to construct an asset data model of the intangible assets. That is, the asset data model can be mapped and stored for the asset keywords (such as the asset name of the intangible asset, etc.) and the asset data information to generate the asset data model.

[0108] The above process can be combined with Figure 3 Describe. Figure 3 As shown, after the asset data is split, multiple arrays can be obtained, namely array 1, array 2, array 3, ..., and then the vocabulary comparison can be performed in a concurrent pipeline manner.

[0109] In practical applications, asset data can be stored in "row priority order". Let a[i][j] be the first element of A and t be the number of storage bytes. The address of element a[m][n] is calculated as: L(a[m][n])+((im)*n+(jn))*t.

[0110] The vectorized data performs matching, verification, and hit work in the concurrent pipeline. This embodiment adopts a CPU pipeline, and a pipeline is divided into 4 parts, each of which can work independently, so it can process multiple data streams. The system will parse the input metadata corresponding to the specific data format, merge the Block (phrase) into a non-spanning file input fragment Inputsplit, and generate specific Tasks for these input fragments. InputSplit and Task are one-to-one. The back-end management system will manage the execution matching of each Task, and the result of each Task execution is to generate the target value r. Based on the execution of the task, the number of tasks T, and the hit value R, the basic hit data is obtained. When R / T=1, a perfect match is obtained. If R / T<=0.5, the step size is adjusted and re-verified. The hit value after verification gradually approaches 1. The laboratory value can be obtained based on the experience of the business personnel, and the intended hit value is matched to gradually improve the accuracy of the model.

[0111] The data after word segmentation and structure is further converted into data recognized by the system for storage. The stored data uses a relational database and stores data in a structured manner. Each data table must define each field. In order to avoid duplication, standardize data and make full use of storage space, the backend management system stores data in the form of a minimum relational table.

[0112] After vectorizing the acquired asset data information of the intangible assets within the enterprise based on the word segmentation vectorization algorithm and constructing an asset data model of the intangible assets, execute step 102.

[0113] Step 102: Based on the technical factor method, a financial index evaluation is performed on the asset usage status parameters of the intangible asset to obtain an asset financial rating index of the intangible asset.

[0114] The technical factor method is a method of quantitative investment analysis based on technical indicators, which focuses on inferring the price trend through market behavior indicators such as stock price and turnover rate in the market. Technical factors predict future asset value trends by analyzing the historical data of intangible assets, such as the moving average system and MACD indicators.

[0115] After the asset data information of the intangible assets in the enterprise is vectorized based on the word segmentation vectorization algorithm and the asset data model of the intangible assets is constructed, the technical factor method can be used to evaluate the financial index of the asset usage status parameters of the intangible assets to obtain the asset financial rating index of the intangible assets. The implementation process can be described in detail in combination with the following specific implementation methods.

[0116] In a specific implementation of the present application, the above step 102 may include:

[0117] Sub-step B1: adopting a multi-process concurrent collection method to collect asset usage information of the intangible assets within the enterprise in multiple dimensions.

[0118] In this embodiment, a multi-process concurrent collection method can be used to collect asset usage information of intangible assets in the enterprise in multiple dimensions.

[0119] In the specific implementation, the business data middle platform can be used to connect to external systems and equipment to obtain the asset usage status. To enter the intangible asset information stored in the system, it is necessary to verify the validity of the asset, that is, whether the asset is in normal use, whether it is an effective asset of the enterprise, the frequency of use, etc. This embodiment adopts the method of connecting to the peripheral resource data system, connecting to external resources, obtaining data of various dimensions, and comprehensively assessing the use of assets to obtain the final status of the assets. The external systems involved are implemented through the built-in business data middle platform, which uniformly processes the data and performs corresponding data pulling work according to the built-in business logic. The specific implementation process is as follows:

[0120] 1. Data source connection: First, it is necessary to clearly obtain the basic data source (level asset data information) obtained in step 101, and obtain the asset name, asset type, asset category, validity period, asset use department, asset value, etc. The obtained data is placed in the memory database, and the data is preset with a validity period T. Within the preset validity period, the data can be stored, and the storage data format is data, that is, array{,[{,,}{,,}{,,}{,,}...{,,}]}.

[0121] 2. Device access: Connect external devices to the business data center to realize the collection and transmission of device data.

[0122] When external devices and systems are connected to the middle platform, relevant configuration work needs to be performed according to the built-in configuration files. The information format involved in the configuration is shown in Table 4 below:

[0123] Table 4: Configuration information

[0124]

[0125]

[0126] The interface parameters are configured in the memory and stored according to the interface ID value. The storage format can be: ID 1 interface configuration parameters.

[0127] 3. Data collection: The back-end management system starts the data center, loads a unified interface configuration file, and the center system performs multi-process concurrent collection and stores the device data in the data storage area of ​​the business data center to ensure data integrity and reliability. The execution process can be as follows: Figure 4 As shown. The middle platform loads the interface, based on the content of the configuration file, calls each network element or resource interface, sends the interface data request and obtains the result. To adapt to the task processing of the enterprise's distributed environment, the thread and process levels establish the corresponding mapping relationship in advance.

[0128] During the distribution and scheduling process, when a new ready process i appears in the system, its priority Pi is compared with the priority Pj of the executing process j. If Pi≤Pj, the original process Pj continues to execute. If Pi>Pj, the execution of Pj is stopped immediately, and the process is switched to put the i process into execution. The system has multiple levels of ready queues, which queue up to be allocated time slices according to the principle of high to low priority and small to large time slices at each level. If the process has not ended after the time slice is used up, the process enters the end of the next level queue. The task processor only processes tasks that have a corresponding relationship with it. For a single processor, it is just a serial task processor. In this way, the construction of the entire concurrent model has strong flexibility and stability.

[0129] 4. Data cleaning and processing: Clean and process the device data stored in the business data center, including data deduplication and removal of outliers, to facilitate subsequent processing and analysis.

[0130] 5. Data display and analysis: The back-end management system displays and analyzes the results of analysis and calculation through the visualization tools of the business data center, and stores the acquired intangible asset data status.

[0131] Sub-step B2: Evaluate the usage status of the intangible asset based on the asset usage information in multiple dimensions to obtain asset usage status parameters of the intangible asset.

[0132] After obtaining the asset usage information of the intangible asset in multiple dimensions, the usage status of the intangible asset can be evaluated based on the asset usage information in multiple dimensions to obtain the asset usage status parameters of the intangible asset.

[0133] In the above sub-step B1, the data is stored in a structured manner. This step will conduct financial analysis on the data involved and conduct financial evaluation of the assets from a financial perspective. The data involved include the name of the asset data, investment year, annual investment amount, output amount, value-added tax, budget occupation, etc.

[0134] After evaluating the usage status of the intangible asset based on the asset usage information in multiple dimensions and obtaining the asset usage status parameters of the intangible asset, sub-step B3 is executed.

[0135] Sub-step B3: Using the technical factor method, perform a financial index evaluation on the asset usage status parameters to obtain the asset financial rating index of the intangible asset.

[0136] Asset financial rating is a professional evaluation method that comprehensively evaluates a company's financial status and credit rating by collecting and analyzing information such as the company's financial data, operating results, market conditions and future development trends.

[0137] After evaluating the use status of intangible assets based on asset use information under multiple dimensions and obtaining the asset use status parameters of the intangible assets, the technical factor method can be used to evaluate the asset use status parameters for financial indexes to obtain the asset financial rating index of the intangible assets. The specific evaluation method can be: first, the asset use status parameters are initialized to obtain the initialization status parameters. The initialization status parameters are stored in a one-dimensional array according to the set order to generate an asset status parameter array. The historical output values ​​of the intangible assets and the asset status parameter array are processed according to the first preset algorithm to obtain the net output technical factor of the intangible assets. The asset status parameter array is processed according to the second preset algorithm to obtain the variance distribution technical factor of the cumulative asset input of the intangible assets. Finally, the financial index of the intangible assets can be evaluated based on the net output technical factor and the variance distribution technical factor to obtain the asset financial rating index.

[0138] Specifically, the acquired data can be initialized and stored in M[i], where M is the one-dimensional array and i is the column position. m[i] is M original variables, which are standardized variables with a mean of zero and a standard deviation of 1. After dimensionality reduction, they are integrated into n (n is the number) new indicators.

[0139] Then, based on Get the cumulative investment of this asset, It is the laboratory experience value, which is obtained according to the historical output value of intangible assets. According to the cumulative input and the total output of intangible assets, the net output of intangible assets can be obtained. This net output can be used as the technical factor T1, that is, the net output technical factor.

[0140] The sum of the squares of the elements in each row of the matrix M is the contribution of all common factors to the total variance of the variable, and the common factor variance is obtained. The cumulative variance distribution of asset investment is obtained. α is a fixed value, which can be preset manually. This value can modify the parameters. The cumulative variance distribution of asset investment obtained is the technical factor T2, that is, the variance distribution technical factor.

[0141] There are differences in the actual model data and position offsets. The system uses the traditional displacement and vector displacement δ of T1 and T2, and corrects the parameters through the system vector δ, so that the created model can be repaired by system-level linear transformation preprocessing. The formula is as follows:

[0142] T( ɑ x,βy)=ɑ T1(i)+βT2(i) (1)

[0143] Among them, δ is the empirical value, which is obtained by business personnel based on statistical analysis of historical data. ɑ and β are the backend parsing program parameter values, that is, weight values.

[0144] By dividing the number of correct predictions by the total number of predictions made by the model, multiple sample data need to be verified, and the model algorithm is combined to correct the deviation of the check value. At present, the accuracy of the system test data has been improved to nearly 99.8, confirming that there is no "overfitting" phenomenon, proving that the model is good.

[0145] After obtaining the technical factors, the assets are rated in combination with the vector data of the assets. The rating work is performed by the back-end management system, and the results are obtained by calling the corresponding parameters. After inputting the cumulative investment T, annual investment R1, asset value R2, authorization period n, discount rate r, etc., the asset value trend cost P is obtained. Based on the expected P obtained, a linear correction is performed to correct the expected P value of each intangible asset to a linear table, and the final rating is obtained by calling the built-in segmented value function.

[0146] After performing a financial index evaluation on the asset usage status parameters of the intangible asset based on the technical factor method to obtain the asset financial rating index of the intangible asset, step 103 is executed.

[0147] Step 103: Perform model analysis on the asset data model according to the asset financial rating index to predict future asset value trend information of the intangible asset.

[0148] After the asset financial rating index of the intangible asset is obtained by conducting a financial index evaluation on the asset usage status parameters of the intangible asset based on the technical factor method, the asset data model can be analyzed based on the asset financial rating index to predict the future asset value trend information of the intangible asset. Specifically, the asset data model can be analyzed based on the asset financial rating index of the intangible asset to obtain the asset life cycle index of the intangible asset. Based on the asset life cycle index, a future asset value trend chart of the intangible asset is drawn, and the future asset value trend chart is used as the future asset value trend information of the intangible asset.

[0149] In the specific implementation, the back-end management system conducts model analysis on the asset financial rating index, and the analysis derives the life cycle of the asset. The mid-life conclusion covers the formation period, development period, maturity period, and decline period. Based on the above four dimensions, the back-end management system calls the model analysis algorithm to make cycle judgments. Six indicators with a greater impact on the development of the enterprise, such as main business income x, main business profit y, net cash flow growth rate r1, scale expansion rate r2, and market share growth rate r3, are selected for measurement and judgment.

[0150]

[0151] The average value of f = (r1+r2+r3) / 3 is calculated by subtracting fi-1 from the year and adding fi+1 to get the value of fi. The system distributes the fi value in probability and obtains trend charts of different probability intervals, such as Figure 5 shown.

[0152] The F[i] value is transmitted to the back end, and in this embodiment, the sequential storage structure of the linear list is used for access. That is, the storage position of the data element F differs from the starting position of the linear list by a constant n that is proportional to the position of the data element in the linear list. In order to improve storage efficiency, the data structure is directly accessed through the subscript [i]. That is, when accessing the Nth data, there is no need to access the previous (N-1) data. After data processing, the data needs to be stored, and the back-end management system securely authorizes the data to ensure the security and privacy of the data. In this process, a system synchronizes data with the data docking interface and other peripheral systems. After this step is completed, the back-end management system generates a multi-dimensional future asset value trend chart and derives the life cycle of the intangible asset.

[0153] After the asset data model is analyzed according to the asset financial rating index and the future asset value trend information of the intangible asset is predicted, step 104 is executed.

[0154] Step 104: Systematically manage the intangible assets based on the future asset value trend information.

[0155] After the asset data model is analyzed according to the asset financial rating index and the future asset value trend information of the intangible asset is predicted, the intangible asset can be systematically managed based on the future asset value trend information. Specifically, the intangible asset can be checked and verified based on the future asset value trend information of the intangible asset and the asset financial rating index of the intangible asset to obtain the asset inventory verification result, and the intangible asset can be processed based on the asset inventory verification result. At the same time, the asset card of the intangible asset can be generated based on the future asset value trend information of the intangible asset and the asset financial rating index of the intangible asset, and the asset card, the asset inventory verification result and the asset number information of the intangible asset can be associated and stored in the asset database.

[0156] Specific system management methods may include:

[0157] 1. The back-end management system generates asset card management, completes data interaction and regular data audit and inventory verification. Based on the system's future asset value trend data and financial analysis data, data audit and verification are carried out to dispose of inefficient assets.

[0158] 2. The backend management system manages the warehousing of intangible asset data, including system name, asset name, asset code, inventory status, data asset system unique identifier, data asset system name, and data management platform.

[0159] 3. Establish intangible asset delisting evaluation standards, split and dispose of intangible assets according to their functions, and quickly release the value of fixed assets. Establish asset disposal procedures and conduct relevant business approvals.

[0160] 4. Establish automatic inventory verification standards for intangible assets to reduce the workload of manual inventory and reduce the difficulty of inventory. The inventory system associates intangible assets with the name and code of the data asset management system and the name of the data management security platform system.

[0161] 5. The inventory system connects the data audit status and audit effectiveness time with the data asset management system, and synchronizes the system hierarchical scanning and verification results of the digital management security platform, ultimately achieving effective management of intangible assets.

[0162] Through the management of intangible assets, the embodiments of the present application can realize the filing of intangible assets, complete the information gathering of provincial construction and maintenance, support experts to realize analysis, evaluation, splitting, disposal and inventory, and record the results of various work. The evaluation standard for the withdrawal of intangible assets from the network has been established, and the intangible assets can be split and disposed of according to their functions, and the value of fixed assets can be quickly released. The automatic inventory verification standard for intangible assets has been established to reduce the workload of manual inventory and reduce the difficulty of inventory.

[0163] The above implementation process can be combined with Figure 6 The following description is given.

[0164] like Figure 6 As shown, the data center can be connected to external systems (external system 1, external system 2, external system 3, ...) to obtain asset data, load the interface configuration file through the pre-established task MAP mapping relationship, send the interface data request in a distributed scheduling manner, and obtain the corresponding results. Then, the technical factor method can be used to conduct a financial evaluation of intangible assets and obtain a financial rating. The model analysis algorithm is called to form a comprehensive opportunity map (i.e., the future asset value trend map in this embodiment) and update the life cycle. The asset card of the intangible asset generated by combining the above information is stored in the database to achieve systematic management of intangible assets.

[0165] The intangible asset management method provided in the embodiment of the present application performs vector processing on the asset data information of the intangible assets in the enterprise obtained based on the word segmentation vectorization algorithm, and constructs an asset data model of the intangible assets. Based on the technical factor method, the asset usage status parameters of the intangible assets are evaluated by financial index to obtain the asset financial rating index of the intangible assets. The asset data model is analyzed according to the asset financial rating index to predict the future asset value trend information of the intangible assets. Intangible assets are systematically managed based on future asset value trend information. By constructing an asset data model of intangible assets, the embodiment of the present application performs financial index evaluation on intangible assets based on the asset usage status, and predicts the future value trend of intangible assets, so as to effectively establish an intangible asset delisting evaluation standard, split and dispose of intangible assets according to their functions, and improve the tracking rate of intangible assets. Compared with the manual inventory method, it can reduce accounting costs and quickly release the value of fixed assets.

[0166] Reference Figure 7 , showing a schematic diagram of the structure of an intangible asset management device provided by an embodiment of the present application, such as Figure 7 As shown, the intangible asset management device 700 may include the following modules:

[0167] The asset data model building module 710 is used to vectorize the acquired asset data information of the intangible assets of the enterprise based on the word segmentation vectorization algorithm to build an asset data model of the intangible assets;

[0168] The asset rating index acquisition module 720 is used to perform a financial index evaluation on the asset usage status parameter of the intangible asset based on the technical factor method to obtain the asset financial rating index of the intangible asset;

[0169] The asset value trend acquisition module 730 is used to perform model analysis on the asset data model according to the asset financial rating index, and predict the future asset value trend information of the intangible asset;

[0170] The intangible asset management module 740 is used to systematically manage the intangible assets based on the future asset value trend information.

[0171] Optionally, the asset data model building module includes:

[0172] An asset data information acquisition unit, used to acquire asset data information of intangible assets within the enterprise;

[0173] A split asset phrase acquisition unit, configured to split the asset data information based on a plurality of preset step sizes to obtain split asset phrases of the intangible assets;

[0174] A phrase vector acquisition unit, used to use the word segmentation vectorization algorithm to search for the phrase vector corresponding to the split asset phrase from a preset word library;

[0175] A keyword vector acquisition unit, used to perform recognition processing on the phrase vector to obtain asset keywords of the intangible asset;

[0176] The asset data model construction unit is used to store the asset keywords and the asset data information according to a preset mapping relationship to construct an asset data model of the intangible asset.

[0177] Optionally, the asset rating index acquisition module includes:

[0178] An asset usage information collection unit, used to collect asset usage information of the intangible assets in the enterprise in multiple dimensions by using a multi-process concurrent collection method;

[0179] An asset status parameter acquisition unit, used to evaluate the usage status of the intangible asset based on asset usage information in multiple dimensions to obtain asset usage status parameters of the intangible asset;

[0180] The asset rating index acquisition unit is used to use the technical factor method to perform financial index evaluation on the asset usage status parameters to obtain the asset financial rating index of the intangible asset.

[0181] Optionally, the asset rating index acquisition unit includes:

[0182] An initial state parameter acquisition subunit is used to initialize the asset usage state parameter to obtain the initialization state parameter;

[0183] An asset parameter array generation subunit, used to store the initialization state parameters in a one-dimensional array according to a set order, and generate an asset state parameter array;

[0184] A first technical factor acquisition subunit is used to process the historical output value of the intangible asset and the asset status parameter array according to a first preset algorithm to obtain the net output technical factor of the intangible asset;

[0185] A second technical factor acquisition subunit is used to process the asset status parameter array according to a second preset algorithm to obtain a variance distribution technical factor of the cumulative asset investment of the intangible asset;

[0186] The asset rating index acquisition subunit is used to evaluate the financial index of the intangible asset based on the net output technical factor and the variance distribution technical factor to obtain the asset financial rating index.

[0187] Optionally, the asset value trend acquisition module includes:

[0188] An asset life cycle index acquisition unit, used to perform model analysis on the asset data model based on the asset financial rating index of the intangible asset to obtain the asset life cycle index of the intangible asset;

[0189] The asset value trend acquisition unit is used to draw a future asset value trend chart of the intangible asset based on the asset life cycle index, and use the future asset value trend chart as the future asset value trend information of the intangible asset.

[0190] Optionally, the intangible asset management module includes:

[0191] An asset inventory result acquisition unit, used to perform data inventory verification on the intangible assets based on the future asset value trend information of the intangible assets and the asset financial rating index of the intangible assets, and obtain an asset inventory verification result;

[0192] An asset processing unit, configured to perform asset processing on the intangible assets based on the asset inventory verification result;

[0193] An asset card generating unit, configured to generate an asset card of the intangible asset based on the future asset value trend information of the intangible asset and the asset financial rating index of the intangible asset;

[0194] The asset information storage unit is used to associate and store the asset card, the asset inventory verification result and the asset number information of the intangible asset in an asset database.

[0195] The intangible asset management device provided in the embodiment of the present application performs vector processing on the asset data information of the intangible assets in the enterprise obtained based on the word segmentation vectorization algorithm, and constructs an asset data model of the intangible assets. Based on the technical factor method, the asset usage status parameters of the intangible assets are evaluated by financial index to obtain the asset financial rating index of the intangible assets. The asset data model is analyzed according to the asset financial rating index to predict the future asset value trend information of the intangible assets. The intangible assets are systematically managed based on the future asset value trend information. The embodiment of the present application constructs an asset data model of the intangible assets, evaluates the financial index of the intangible assets based on the asset usage status, and predicts the future value trend of the intangible assets, so as to effectively establish the intangible asset delisting evaluation standard, split and dispose of the intangible assets according to their functions, improve the tracking rate of the intangible assets, and can reduce the accounting cost and quickly release the value of fixed assets compared to the manual inventory method.

[0196] An embodiment of the present application also provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program implements the above-mentioned intangible asset management method when executed by the processor.

[0197] Figure 8 FIG. 8 is a schematic diagram showing the structure of an electronic device 800 according to an embodiment of the present invention. Figure 8 As shown, the electronic device 800 includes a central processing unit (CPU) 801, which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) 802 or computer program instructions loaded from a storage unit 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the electronic device 800 can also be stored. The CPU 801, the ROM 802, and the RAM 803 are connected to each other via a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0198] Multiple components in the electronic device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, a microphone, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a disk, an optical disk, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the electronic device 800 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0199] The various processes and processing described above may be performed by the processing unit 801. For example, the method of any of the above embodiments may be implemented as a computer software program, which is tangibly contained in a computer-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the CPU 801, one or more actions in the method described above may be performed.

[0200] In addition, an embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the above-mentioned intangible asset management method is implemented.

[0201] The various embodiments in this specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the various embodiments can be referenced to each other.

[0202] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, devices, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0203] The embodiments of the present application are described with reference to the flowcharts and / or block diagrams of the methods, terminals (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0204] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing terminal to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0205] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal so that a series of operating steps are executed on the computer or other programmable terminal to produce a computer-implemented process, thereby providing instructions for implementing the process in the computer or other programmable terminal. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0206] Although the preferred embodiments of the present application have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the embodiments of the present application.

[0207] Finally, it should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, the elements defined by the statement "comprise a ..." do not exclude the presence of other identical elements in the process, method, article or terminal including the elements.

[0208] The above is a detailed introduction to an intangible asset management method, an intangible asset management device, an electronic device and a computer-readable storage medium provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. An intangible asset management method, characterized in that: The method comprises: Vectorizing the acquired asset data information of the intangible assets within the enterprise based on a word segmentation vectorization algorithm to construct an asset data model of the intangible assets; Based on the technical factor method, a financial index evaluation is performed on the asset usage status parameters of the intangible asset to obtain the asset financial rating index of the intangible asset; Performing model analysis on the asset data model according to the asset financial rating index to predict and obtain future asset value trend information of the intangible asset; The intangible assets are systematically managed based on the future asset value trend information.

2. The method according to claim 1, characterized in that The method of performing vectorization processing on the acquired asset data information of the intangible assets in the enterprise based on the word segmentation vectorization algorithm to construct an asset data model of the intangible assets includes: Obtaining asset data information of intangible assets within the enterprise; Splitting the asset data information based on a plurality of preset step sizes to obtain split asset phrases of the intangible assets; Using the word segmentation vectorization algorithm to search for the phrase vector corresponding to the split asset phrase from a preset word library; Performing recognition processing on the phrase vector to obtain asset keywords of the intangible asset; The asset keywords and the asset data information are stored according to a preset mapping relationship to construct an asset data model of the intangible asset.

3. The method according to claim 1, characterized in that The method based on the technical factor method performs a financial index evaluation on the asset usage status parameters of the intangible asset to obtain the asset financial rating index of the intangible asset, including: A multi-process concurrent collection method is adopted to collect asset usage information of intangible assets in the enterprise in multiple dimensions; Evaluate the usage status of the intangible asset based on asset usage information in multiple dimensions to obtain asset usage status parameters of the intangible asset; The technical factor method is used to perform a financial index evaluation on the asset usage status parameters to obtain the asset financial rating index of the intangible asset.

4. The method according to claim 3, characterized in that The method of using the technical factor method to evaluate the asset usage status parameters by a financial index to obtain the asset financial rating index of the intangible asset includes: Initializing the asset usage status parameter to obtain an initialization status parameter; The initialization state parameters are stored in a one-dimensional array according to a set order to generate an asset state parameter array; Processing the historical output value of the intangible asset and the asset status parameter array according to a first preset algorithm to obtain a net output technical factor of the intangible asset; Processing the asset status parameter array according to a second preset algorithm to obtain a variance distribution technical factor of the cumulative asset investment of the intangible asset; The financial index of the intangible asset is evaluated based on the net output technical factor and the variance distribution technical factor to obtain the asset financial rating index.

5. The method according to claim 1, characterized in that The performing of model analysis on the asset data model according to the asset financial rating index to predict the future asset value trend information of the intangible asset includes: Performing model analysis on the asset data model based on the asset financial rating index of the intangible asset to obtain an asset life cycle index of the intangible asset; Based on the asset life cycle index, a future asset value trend graph of the intangible asset is drawn, and the future asset value trend graph is used as future asset value trend information of the intangible asset.

6. The method according to claim 1, characterized in that The systematic management of the intangible assets based on the future asset value trend information includes: Performing data inventory verification on the intangible assets based on the future asset value trend information of the intangible assets and the asset financial rating index of the intangible assets to obtain asset inventory verification results; Performing asset processing on the intangible assets based on the asset inventory verification results; Generating an asset card of the intangible asset based on the future asset value trend information of the intangible asset and the asset financial rating index of the intangible asset; The asset card, the asset inventory verification result and the asset number information of the intangible asset are associated and stored in an asset database.

7. An intangible asset management device, characterized in that: The device comprises: An asset data model building module is used to vectorize the asset data information of the intangible assets of the enterprise obtained based on a word segmentation vectorization algorithm to build an asset data model of the intangible assets; An asset rating index acquisition module is used to perform a financial index evaluation on the asset usage status parameters of the intangible asset based on a technical factor method to obtain an asset financial rating index of the intangible asset; An asset value trend acquisition module is used to perform model analysis on the asset data model according to the asset financial rating index, and predict the future asset value trend information of the intangible asset; The intangible asset management module is used to systematically manage the intangible assets based on the future asset value trend information.

8. The device according to claim 7, characterized in that The asset data model building module includes: An asset data information acquisition unit, used to acquire asset data information of intangible assets within the enterprise; A split asset phrase acquisition unit, configured to split the asset data information based on a plurality of preset step sizes to obtain split asset phrases of the intangible assets; A phrase vector acquisition unit, used to use the word segmentation vectorization algorithm to search for the phrase vector corresponding to the split asset phrase from a preset word library; A keyword vector acquisition unit, used to perform recognition processing on the phrase vector to obtain asset keywords of the intangible asset; The asset data model construction unit is used to store the asset keywords and the asset data information according to a preset mapping relationship to construct an asset data model of the intangible asset.

9. An electronic device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the intangible asset management method according to any one of claims 1 to 6 when executing the program.

10. A computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the intangible asset management method described in any one of claims 1 to 6.

Images