Enterprise management system for enterprise experience asset management based on artificial intelligence

Abstract

The invention provides an enterprise management system for enterprise experience asset management based on artificial intelligence, and relates to the field of data processing, and the system comprises an experience asset obtaining module which is used for receiving to-be-managed enterprise experience assets uploaded by a user side; the empirical asset analysis module is used for analyzing the enterprise empirical assets to be managed and determining asset feature information of the enterprise empirical assets to be managed; the empirical asset management module is used for determining an optimal management scheme of the to-be-managed enterprise empirical assets according to the asset feature information of the to-be-managed enterprise empirical assets and managing the to-be-managed enterprise empirical assets; and the experience asset calling module is used for receiving an enterprise experience asset calling request initiated by the user side, determining an experience asset type matched with the enterprise experience asset calling request according to the enterprise experience asset calling request, and calling target enterprise experience assets to the user side, and has the advantage of improving the intelligent level of education enterprise experience asset management.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to an enterprise management system for enterprise experience asset management based on artificial intelligence. Background Art

[0002] Enterprise experience asset management refers to the management activities of enterprises to effectively allocate, utilize, dispose of and supervise the experience assets accumulated in the operation process. These experience assets include the knowledge, skills, methods and strategies accumulated by the enterprise in market operation, product development, customer service, production process optimization and other aspects. Education enterprise experience asset management refers to the management activities of education enterprises to effectively allocate, utilize, protect and supervise the intangible assets such as teaching experience, management experience, market operation experience, etc. accumulated in the long-term operation process. These experience assets are an important part of the core competitiveness of education enterprises, and they play an irreplaceable role in improving teaching quality, optimizing management processes, and enhancing market competitiveness.

[0003] In educational enterprises, experience assets often exist in a fragmented form, lacking unified management and integration. Teachers, employees, and managers may each have some experience assets, but these assets lack connection and sharing, resulting in the inability to form an effective experience asset system. This limits the accumulation and inheritance of experience assets and also affects the overall competitiveness of the enterprise.

[0004] Therefore, it is necessary to provide an enterprise management system based on artificial intelligence for enterprise experience asset management, so as to improve the intelligence level of experience asset management of educational enterprises. Summary of the invention

[0005] The present invention provides an enterprise management system for managing enterprise experience assets based on artificial intelligence, including: an experience asset acquisition module, used to receive enterprise experience assets to be managed uploaded by a user terminal; an experience asset analysis module, used to analyze the enterprise experience assets to be managed and determine asset feature information of the enterprise experience assets to be managed; an experience asset management module, used to determine the optimal management plan for the enterprise experience assets to be managed based on the asset feature information of the enterprise experience assets to be managed, and manage the enterprise experience assets to be managed based on the optimal management plan for the enterprise experience assets to be managed; an experience asset retrieval module, used to receive an enterprise experience asset retrieval request initiated by a user terminal, determine target asset feature information based on the enterprise experience asset retrieval request, and retrieve the target enterprise experience asset to the user terminal based on the target asset feature information.

[0006] Furthermore, the experience asset analysis module analyzes the enterprise experience assets to be managed to determine the asset characteristic information of the enterprise experience assets to be managed, including: acquiring multiple managed enterprise experience assets; determining multiple asset type keywords corresponding to each experience asset type according to the multiple managed enterprise experience assets and the experience asset type to which each of the managed enterprise experience assets belongs; determining asset retrieval characteristic keywords corresponding to each experience asset type according to enterprise experience asset retrieval requests of the multiple managed enterprise experience assets; determining the asset characteristic information of the enterprise experience assets to be managed according to the multiple asset type keywords corresponding to each experience asset type and the asset retrieval characteristic keywords corresponding to each experience asset type.

[0007] Furthermore, the experience asset analysis module determines a plurality of asset type keywords corresponding to each experience asset type according to the plurality of managed enterprise experience assets and the experience asset type to which each of the managed enterprise experience assets belongs, including: establishing a first keyword library, wherein the first keyword library includes a plurality of initial asset type keywords; for each experience asset type, determining the initial asset type keyword corresponding to the experience asset type based on the managed enterprise experience assets corresponding to the experience asset type, and determining a first correlation coefficient between any two initial asset type keywords corresponding to the experience asset type according to the managed enterprise experience assets corresponding to the experience asset type; for any two experience asset types, determining a first correlation coefficient between the initial asset type keyword corresponding to each experience asset type and any two initial asset type keywords corresponding to each experience asset type according to the initial asset type keyword corresponding to the experience asset type number, calculate the first keyword similarity of the two experience asset types; determine a first similar experience asset type group according to the first keyword similarity of any two experience asset types, wherein the first similar experience asset type group includes at least two experience asset types; for each of the first similar experience asset type groups, determine the central asset type keyword corresponding to the first similar experience asset type group and the marginal asset type keyword corresponding to each experience asset type included in the first similar experience asset type group according to the first correlation coefficient between the initial asset type keyword corresponding to each experience asset type and any two initial asset type keywords corresponding to each experience asset type, wherein the multiple asset type keywords corresponding to the experience asset type include the central asset type keyword corresponding to the first similar experience asset type group to which the experience asset type belongs and the marginal asset type keyword corresponding to the experience asset type.

[0008] Furthermore, the experience asset analysis module determines the asset retrieval feature keywords corresponding to each of the experience asset types based on the enterprise experience asset retrieval requests of the multiple managed enterprise experience assets, including: establishing a second keyword library, wherein the second keyword library includes multiple initial asset retrieval feature keywords; for each of the experience asset types, determining the initial asset retrieval feature keywords corresponding to the experience asset type based on the enterprise experience asset retrieval requests of the managed enterprise experience assets corresponding to the experience asset type, and determining the second correlation coefficient between any two initial asset retrieval feature keywords corresponding to the experience asset type based on the enterprise experience asset retrieval requests of the managed enterprise experience assets corresponding to the experience asset type; for any two experience asset types, determining the second correlation coefficient between the initial asset retrieval feature keywords corresponding to each of the experience asset types and the second correlation coefficient between any two initial asset retrieval feature keywords corresponding to each of the experience asset types relationship number, calculate the second keyword similarity of the two experience asset types; determine the second similar experience asset type group according to the second keyword similarity of any two experience asset types, wherein the second similar experience asset type group includes at least two experience asset types; for each of the second similar experience asset type groups, determine the central asset retrieval feature keyword corresponding to the second similar experience asset type group and the marginal asset retrieval feature keyword corresponding to each experience asset type included in the second similar experience asset type group according to the second correlation coefficient between the initial asset retrieval feature keyword corresponding to each experience asset type and any two initial asset retrieval feature keywords corresponding to each experience asset type, wherein the asset retrieval feature keyword corresponding to the experience asset type includes the central asset retrieval feature keyword corresponding to the second similar experience asset type group to which the experience asset type belongs and the marginal asset retrieval feature keyword corresponding to the experience asset type.

[0009] Furthermore, the experience asset analysis module determines the asset feature information of the enterprise experience assets to be managed based on multiple asset type keywords corresponding to each of the experience asset types and asset retrieval feature keywords corresponding to each of the experience asset types, including: determining the first attribution parameter between the enterprise experience assets to be managed and each of the first similar experience asset type groups based on the central asset type keywords corresponding to each of the first similar experience asset type groups; determining the first similar experience asset type group that matches the enterprise experience assets to be managed based on the first attribution parameter between the enterprise experience assets to be managed and each of the first similar experience asset type groups; determining the relationship between the enterprise experience assets to be managed and the enterprise experience assets to be managed based on the edge asset type keywords corresponding to each experience asset type included in the first similar experience asset type group that matches the enterprise experience assets to be managed. The second attribution parameter between each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed; determining the experience asset type that the enterprise experience asset to be managed matches based on the second attribution parameter between the enterprise experience asset to be managed and each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed; extracting the asset portrait of the enterprise experience asset to be managed based on the central asset type keywords and marginal asset type keywords corresponding to the experience asset type that the enterprise experience asset to be managed matches; extracting the retrieval feature of the enterprise experience asset to be managed based on the central asset retrieval feature keywords and marginal asset retrieval feature keywords corresponding to the experience asset type that the enterprise experience asset to be managed matches, wherein the asset feature information of the enterprise experience asset to be managed includes the asset portrait and retrieval feature of the enterprise experience asset to be managed.

[0010] Furthermore, the asset portrait of the enterprise experience assets to be managed includes at least the experience asset type matching the enterprise experience assets to be managed, the word frequency of each of the central asset type keywords, the word frequency of each of the marginal asset type keywords, the association parameters between any two central asset type keywords, the association parameters between any two marginal asset type keywords, and the association parameters between any central asset type keyword and any marginal asset type keyword.

[0011] Furthermore, the experience asset management module determines the optimal management plan for the enterprise experience assets to be managed based on the asset feature information of the enterprise experience assets to be managed, including: determining similar managed enterprise experience assets based on the asset portrait of the enterprise experience assets to be managed and the asset portrait of each managed enterprise experience asset included in the experience asset type that matches the enterprise experience assets to be managed; determining the optimal management plan for the enterprise experience assets to be managed based on the optimal management plans of the similar managed enterprise experience assets and the enterprise experience asset retrieval request, wherein the optimal management plan at least includes an optimal asset segmentation plan and an optimal distributed storage plan.

[0012] Furthermore, the experience asset management module manages the enterprise experience assets to be managed according to the optimal management plan for the enterprise experience assets to be managed, including: dividing the enterprise experience assets to be managed into multiple asset fragments according to the optimal asset segmentation plan; storing multiple asset fragments corresponding to the enterprise experience assets to be managed according to the optimal distributed storage plan.

[0013] Further, the experience asset retrieval module receives an enterprise experience asset retrieval request initiated by a user terminal, and determines the experience asset type that matches the enterprise experience asset retrieval request based on the enterprise experience asset retrieval request, including: calculating the first matching parameter between the enterprise experience asset retrieval request and each of the second similar experience asset type groups based on the central asset retrieval feature keywords corresponding to each second similar experience asset type group; determining the second similar experience asset type group that matches the enterprise experience asset retrieval request based on the first matching parameter between the enterprise experience asset retrieval request and each of the second similar experience asset type groups; determining the second matching parameter between the enterprise experience asset retrieval request and each experience asset type included in the second similar experience asset type group that matches the enterprise experience asset retrieval request based on the edge asset retrieval feature keywords corresponding to each experience asset type included in the second similar experience asset type group that matches the enterprise experience asset retrieval request; determining the experience asset type that matches the enterprise experience asset retrieval request based on the second matching parameter between the enterprise experience asset retrieval request and each experience asset type included in the second similar experience asset type group that matches the enterprise experience asset retrieval request.

[0014] Furthermore, the experience asset retrieval module retrieves the target enterprise experience assets to the user end, including: determining the target enterprise experience assets from the managed enterprise experience assets included in the experience asset type that matches the enterprise experience assets to be managed; and retrieving the target enterprise experience assets to the user end based on the optimal management plan for the target enterprise experience assets.

[0015] Compared with the prior art, the enterprise management system for enterprise experience asset management based on artificial intelligence provided by the present invention has at least the following beneficial effects:

[0016] 1. Through the experience asset acquisition module, enterprises can easily receive the enterprise experience assets to be managed uploaded by the user without manual input or sorting, which greatly improves work efficiency. The experience asset analysis module can conduct in-depth analysis of the enterprise experience assets to be managed, accurately extract asset feature information, and provide strong support for subsequent management and retrieval. Based on the asset feature information, the experience asset management module can intelligently determine the optimal management plan for the enterprise experience assets to be managed, including asset segmentation, distributed storage, etc., so as to optimize resource allocation and improve asset utilization efficiency. With the increase and change of enterprise experience assets, the management system can dynamically adjust the management plan to ensure that the assets are always in the optimal management state. The experience asset retrieval module can quickly respond to the enterprise experience asset retrieval request from the user, quickly locate and retrieve the target enterprise experience assets according to the target asset feature information, and improve user satisfaction. By deeply analyzing the user's usage habits and needs, the management system can provide personalized asset recommendations and services to further enhance the user experience. The experience asset management system can uniformly manage and integrate the experience assets within the enterprise to form a knowledge base for employees to consult and learn.

[0017] 2. Based on the managed enterprise experience assets, it is possible to determine multiple asset type keywords for each experience asset type, which not only helps to classify the experience assets more accurately, but also provides a basis for subsequent management and retrieval. By calculating the keyword similarity between experience asset types, the system can identify similar experience asset type groups, thereby further refining the classification system. Asset retrieval feature keywords are determined for each experience asset type, which greatly improves the retrieval efficiency of experience assets. By analyzing the similarity of retrieval feature keywords, the system can identify experience asset types similar to the enterprise experience assets to be managed, thereby quickly locating relevant experience assets. It is possible to extract asset portraits of the enterprise experience assets to be managed, including experience asset types, keyword frequency, correlation parameters between keywords, etc., providing rich information for in-depth understanding of experience assets. The generation of asset portraits helps enterprises better understand and utilize their own experience assets, thereby making more informed decisions. Designed and implemented based on artificial intelligence technology, it can automatically complete tasks such as analysis, classification, retrieval and portrait extraction of experience assets, greatly reducing the cost and error rate of manual intervention. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] This specification will be further described in the form of exemplary embodiments, which will be described in detail by the accompanying drawings. These embodiments are not restrictive, and in these embodiments, the same number represents the same structure, wherein:

[0019] Figure 1 It is a module diagram of an enterprise management system for enterprise experience asset management based on artificial intelligence according to some embodiments of this specification;

[0020] Figure 2 It is a flowchart of determining asset characteristic information of enterprise experience assets to be managed according to some embodiments of this specification. DETAILED DESCRIPTION

[0021] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0022] Figure 1 is a module diagram of an enterprise management system for enterprise experience asset management based on artificial intelligence according to some embodiments of this specification, such as Figure 1 As shown, the enterprise management system for enterprise experience asset management based on artificial intelligence may include an experience asset acquisition module, an experience asset analysis module, an experience asset management module and an experience asset retrieval module.

[0023] The experience asset acquisition module can be used to receive the enterprise experience assets to be managed uploaded by the user.

[0024] The user end may be a terminal used by teachers, employees, managers and other users. Enterprise experience assets may include intangible assets such as teaching experience, management experience, and market operation experience. The enterprise experience assets to be managed uploaded by the user end may be in the form of text, image, audio, etc. For enterprise experience assets to be managed in non-text form, the experience asset acquisition module may first convert them into text form.

[0025] The experience asset analysis module can be used to analyze the enterprise experience assets to be managed and determine the asset characteristic information of the enterprise experience assets to be managed.

[0026] Specifically include:

[0027] Access to multiple managed corporate experience assets;

[0028] According to a plurality of managed enterprise experience assets and the experience asset type to which each managed enterprise experience asset belongs, determining a plurality of asset type keywords corresponding to each experience asset type;

[0029] Determine asset search feature keywords corresponding to each experience asset type according to enterprise experience asset retrieval requests of multiple managed enterprise experience assets;

[0030] The asset characteristic information of the enterprise experience assets to be managed is determined based on a plurality of asset type keywords corresponding to each experience asset type and an asset search characteristic keyword corresponding to each experience asset type.

[0031] Preferably, the experience asset analysis module determines a plurality of asset type keywords corresponding to each experience asset type according to a plurality of managed enterprise experience assets and the experience asset type to which each managed enterprise experience asset belongs, including:

[0032] Establishing a first keyword library, wherein the first keyword library includes a plurality of initial asset type keywords, for example, the first keyword library may include teaching experience keywords (for example, teaching method keywords, educational concept keywords, curriculum design keywords, teaching interaction keywords, etc.), management experience keywords (for example, team building keywords, employee motivation keywords, strategic planning keywords, etc.), market operation keywords (for example, market research keywords, marketing strategy keywords, brand promotion keywords, etc.), etc.;

[0033] For each experience asset type, based on the managed enterprise experience assets corresponding to the experience asset type, determine the initial asset type keyword corresponding to the experience asset type, and based on the managed enterprise experience assets corresponding to the experience asset type, determine the first correlation coefficient between any two initial asset type keywords corresponding to the experience asset type;

[0034] For any two experience asset types, the similarity of the first keywords of the two experience asset types is calculated according to the first correlation coefficient between the initial asset type keyword corresponding to each experience asset type and any two initial asset type keywords corresponding to each experience asset type;

[0035] Determining a first similar experience asset type group according to the first keyword similarity between any two experience asset types, wherein the first similar experience asset type group includes at least two experience asset types;

[0036] For each first similar experience asset type group, the central asset type keyword corresponding to the first similar experience asset type group and the marginal asset type keyword corresponding to each experience asset type included in the first similar experience asset type group are determined based on the first correlation coefficient between the initial asset type keyword corresponding to each experience asset type and any two initial asset type keywords corresponding to each experience asset type, wherein the multiple asset type keywords corresponding to the experience asset type include the central asset type keyword corresponding to the first similar experience asset type group to which the experience asset type belongs and the marginal asset type keyword corresponding to the experience asset type.

[0037] Specifically, the keyword frequency distribution characteristics of each managed enterprise experience asset can be extracted based on the first keyword library, wherein the keyword frequency distribution characteristics of the managed enterprise experience assets can include the frequency of each initial asset type keyword in the managed enterprise experience assets.

[0038] For each experience asset type, based on the keyword frequency distribution characteristics of the managed enterprise experience assets corresponding to the experience asset type, calculate the frequency mean and frequency standard deviation corresponding to each initial asset type keyword; based on the frequency mean and frequency standard deviation corresponding to each initial asset type keyword, calculate the correlation parameters between each initial asset type keyword and this experience asset type; take the initial asset type keyword whose correlation parameters are greater than the correlation parameter threshold as the initial asset type keyword corresponding to this experience asset type.

[0039] For example, the correlation parameters between the initial asset type keyword and the experience asset type can be calculated according to the following formula:

[0040]

[0041] Among them, C (keyword,type) are the parameters related to the initial asset type keyword and the empirical asset type, μ keyword is the mean frequency of the keywords corresponding to the initial asset type, μ 0 is the preset word frequency mean, β 1 and β 2 is the preset parameter, β 1 and β 2 greater than 0, σ 0 is the preset word frequency standard deviation, σ keyword is the standard deviation of the word frequency corresponding to the initial asset type keyword, f (keyword,n) is the frequency of the initial asset type keyword in the keyword frequency distribution characteristics of the nth managed enterprise experience asset corresponding to the experience asset type, and N is the total number of managed enterprise experience assets corresponding to the experience asset type.

[0042] The first correlation coefficient between any two initial asset type keywords corresponding to the empirical asset type can be calculated according to the following formula:

[0043]

[0044] Among them, C (keyword,(i,j)) is the first correlation coefficient between the i-th initial asset type keyword and the j-th initial asset type keyword corresponding to the empirical asset type, f (i,n) is the keyword frequency of the ith initial asset type keyword in the keyword frequency distribution characteristics of the nth managed enterprise experience asset corresponding to the experience asset type, f (j,n) The frequency of the jth initial asset type keyword in the keyword frequency distribution characteristics of the nth managed enterprise experience asset corresponding to the experience asset type.

[0045] For any two empirical asset types, the overlap of the initial asset type keywords of the two empirical asset types is calculated based on the initial asset type keywords corresponding to each empirical asset type. When the overlap of the initial asset type keywords of the two empirical asset types is greater than the overlap threshold, the union of the initial asset type keywords corresponding to the two empirical asset types is determined, and the difference in the first correlation coefficients of any two initial asset type keywords in the union in the two empirical asset types is calculated. Then, based on the overlap of the initial asset type keywords and the difference in the first correlation coefficients of any two initial asset type keywords in the union in the two empirical asset types, the similarity of the first keywords of the two empirical asset types is calculated.

[0046] For example, the first keyword similarity of two experience asset types can be calculated according to the following formula:

[0047]

[0048] Among them, S (type,(e,f)) is the similarity between the first keyword of the e-th experience asset type and the f-th experience asset type, P (type,(e,f)) is the overlap of the initial asset type keywords of the e-th experience asset type and the f-th experience asset type, a 11 and a 12 is the preset weight, a 11 and a 12 are greater than 0, and a 11 +a 12 =1, The mth corresponding to the eth type of experience asset 1 The initial asset type keyword and the mth 2 The first correlation coefficient between the initial asset type keywords, The mth corresponding to the fth type of experience asset 1The initial asset type keyword and the mth 2 The first correlation coefficient between the initial asset type keywords, M is the total number of initial asset type keywords contained in the union of the initial asset type keywords corresponding to the e-th experience asset type and the f-th experience asset type.

[0049] The first keyword similarity of any two experience asset types in the first similar experience asset type group is greater than the first keyword similarity threshold.

[0050] The central asset type keyword corresponding to the first similar experience asset type group may be the union of the initial asset type keywords corresponding to each experience asset type included in the first similar experience asset type group, and the marginal asset type keyword corresponding to the experience asset type may be an initial asset type keyword that is a non-central asset type keyword among the initial asset type keywords corresponding to the experience asset type and has a first correlation coefficient with at least one central asset type keyword greater than a first correlation coefficient threshold.

[0051] Preferably, the experience asset analysis module determines the asset search feature keywords corresponding to each experience asset type according to the enterprise experience asset retrieval request of multiple managed enterprise experience assets, including:

[0052] Establishing a second keyword library, wherein the second keyword library includes a plurality of initial asset search feature keywords, such as regional keywords, time keywords, target audience keywords, business field keywords, project stage keywords, asset level keywords, etc.;

[0053] For each experience asset type, based on the enterprise experience asset retrieval request of the managed enterprise experience assets corresponding to the experience asset type, determine the initial asset retrieval feature keyword corresponding to the experience asset type, and based on the enterprise experience asset retrieval request of the managed enterprise experience assets corresponding to the experience asset type, determine the second correlation coefficient between any two initial asset retrieval feature keywords corresponding to the experience asset type;

[0054] For any two types of experience assets, the second keyword similarity of the two types of experience assets is calculated according to the second correlation coefficient between the initial asset search feature keyword corresponding to each type of experience asset and any two initial asset search feature keywords corresponding to each type of experience asset;

[0055] Determining a second similar experience asset type group according to the second keyword similarity between any two experience asset types, wherein the second similar experience asset type group includes at least two experience asset types;

[0056] For each second similar experience asset type group, the central asset retrieval feature keywords corresponding to the second similar experience asset type group and the marginal asset retrieval feature keywords corresponding to each experience asset type included in the second similar experience asset type group are determined based on the second correlation coefficient between the initial asset retrieval feature keywords corresponding to each experience asset type and any two initial asset retrieval feature keywords corresponding to each experience asset type, wherein the asset retrieval feature keywords corresponding to the experience asset type include the central asset retrieval feature keywords corresponding to the second similar experience asset type group to which the experience asset type belongs and the marginal asset retrieval feature keywords corresponding to the experience asset type.

[0057] Specifically, the keyword frequency distribution characteristics of the enterprise experience asset retrieval request of the managed enterprise experience assets corresponding to the experience asset type can be extracted based on the second keyword library, wherein the keyword frequency distribution characteristics of the enterprise experience asset retrieval request of the managed enterprise experience assets can include the frequency of each initial asset retrieval feature keyword in the enterprise experience asset retrieval request of the managed enterprise experience assets.

[0058] For each experience asset type, based on the keyword frequency distribution characteristics of the enterprise experience asset retrieval request of the managed enterprise experience assets, the word frequency mean and word frequency standard deviation corresponding to each initial asset retrieval feature keyword are calculated; based on the word frequency mean and word frequency standard deviation corresponding to each initial asset retrieval feature keyword, the relevant parameters of each initial asset retrieval feature keyword and the experience asset type are calculated; the initial asset type keyword whose relevant parameters are greater than the relevant parameter threshold is used as the initial asset retrieval feature keyword corresponding to the experience asset type.

[0059] The method of calculating the relevant parameters of each initial asset search feature keyword and the empirical asset type is similar to the method of calculating the relevant parameters of the initial asset type keyword and the empirical asset type, which will not be repeated here.

[0060] For any two types of empirical assets, the overlap of the initial asset retrieval feature keywords of the two empirical asset types is calculated based on the initial asset retrieval feature keywords corresponding to each empirical asset type. When the overlap of the initial asset retrieval feature keywords of the two empirical asset types is greater than the overlap threshold, the union of the initial asset retrieval feature keywords corresponding to the two empirical asset types is determined, and the difference in the second correlation coefficients of any two initial asset retrieval feature keywords in the union in the two empirical asset types is calculated. Then, based on the overlap of the initial asset retrieval feature keywords and the difference in the second correlation coefficients of any two initial asset type keywords in the union in the two empirical asset types, the second keyword similarity of the two empirical asset types is calculated.

[0061] The method of calculating the second keyword similarity of two types of experience assets is similar to the method of calculating the first keyword similarity of two types of experience assets, and will not be repeated here.

[0062] The second keyword similarity of any two experience asset types in the second similar experience asset type group is greater than the second keyword similarity threshold.

[0063] The central asset retrieval feature keyword corresponding to the second similar experience asset type group can be the union of the initial asset retrieval feature keywords corresponding to each experience asset type included in the first similar experience asset type group, and the marginal asset type keyword corresponding to the experience asset type can be an initial asset retrieval feature keyword that is a non-central asset retrieval feature keyword among the initial asset retrieval feature keywords corresponding to the experience asset type and has a second correlation coefficient with at least one central asset retrieval feature keyword greater than a second correlation coefficient threshold.

[0064] Figure 2 is a flow chart of determining asset feature information of enterprise experience assets to be managed according to some embodiments of this specification, such as Figure 2 As shown, as a preferred embodiment, the experience asset analysis module determines the asset feature information of the enterprise experience assets to be managed according to multiple asset type keywords corresponding to each experience asset type and asset search feature keywords corresponding to each experience asset type, including:

[0065] Determine a first attribution parameter between the enterprise experience asset to be managed and each first similar experience asset type group according to the central asset type keyword corresponding to each first similar experience asset type group;

[0066] Determine the first similar experience asset type group that matches the enterprise experience asset to be managed according to the first attribution parameter between the enterprise experience asset to be managed and each first similar experience asset type group;

[0067] Determine a second attribution parameter between the enterprise experience asset to be managed and each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed, based on the marginal asset type keyword corresponding to each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed;

[0068] Determine the experience asset type that matches the enterprise experience asset to be managed according to a second attribution parameter between the enterprise experience asset to be managed and each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed;

[0069] Extracting asset portraits of the enterprise experience assets to be managed according to the central asset type keywords and the marginal asset type keywords corresponding to the experience asset types matched by the enterprise experience assets to be managed;

[0070] According to the central asset retrieval feature keywords and the edge asset retrieval feature keywords corresponding to the experience asset type matching the enterprise experience assets to be managed, the retrieval features of the enterprise experience assets to be managed are extracted, wherein the asset feature information of the enterprise experience assets to be managed includes the asset portrait and retrieval features of the enterprise experience assets to be managed.

[0071] Specifically, based on the first keyword library, the keyword frequency distribution characteristics of the enterprise experience assets to be managed are extracted, and the initial asset type keywords with a frequency greater than a frequency threshold are used as the initial asset type keywords of the enterprise experience assets to be managed.

[0072] Calculate the degree of overlap between the initial asset type keyword of the enterprise experience asset to be managed and the central asset type keyword corresponding to each first similar experience asset type group as the first attribution parameter between the enterprise experience asset to be managed and the first similar experience asset type group, and take the first similar experience asset type group whose first attribution parameter is greater than the first attribution parameter threshold as the first similar experience asset type group that matches the enterprise experience asset to be managed.

[0073] Calculate the degree of overlap between the initial asset type keyword of the enterprise experience asset to be managed and the marginal asset type keyword corresponding to each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed as the second attribution parameter between the enterprise experience asset to be managed and each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed, and take the experience asset type whose second attribution parameter is greater than the second attribution parameter threshold as the experience asset type that matches the enterprise experience asset to be managed.

[0074] The search features of the enterprise experience assets to be managed may include parameters corresponding to each central asset search feature keyword and parameters corresponding to the edge asset search feature keyword corresponding to the experience asset type matched by the enterprise experience assets to be managed. For example, time: 2023, region: City B.

[0075] Preferably, the asset portrait of the enterprise experience assets to be managed includes at least the experience asset type matching the enterprise experience assets to be managed, the word frequency of each central asset type keyword, the word frequency of each marginal asset type keyword, the association parameters between any two central asset type keywords, the association parameters between any two marginal asset type keywords, and the association parameters between any central asset type keyword and any marginal asset type keyword.

[0076] Specifically, the enterprise experience assets to be managed are divided into multiple sentences, and the number of times each central asset type keyword and peripheral asset type keyword appears in each sentence is counted. According to the number of times each central asset type keyword and peripheral asset type keyword appears in each sentence, the association parameter between any two central asset type keywords, the association parameter between any two peripheral asset type keywords, and the association parameter between any one central asset type keyword and any one peripheral asset type keyword are determined.

[0077] For example, the correlation parameter between two central asset type keywords can be calculated according to the following formula:

[0078]

[0079] Among them, C (Central keywords,(g,h)) is the association parameter between the g-th central asset type keyword and the h-th central asset type keyword, R is the total number of sentences into which the enterprise experience assets to be managed are divided, and f (g,r) is the number of times the g-th central asset type keyword appears in the r-th sentence, f (h,r) is the number of times the h-th central asset type keyword appears in the r-th sentence.

[0080] The method of calculating the association parameters between any two edge asset type keywords and the association parameters between any central asset type keyword and any edge asset type keyword is similar to the method of calculating the association parameters between any two central asset type keywords, which will not be repeated here.

[0081] The experience asset management module can be used to determine the optimal management plan for the enterprise experience assets to be managed based on the asset feature information of the enterprise experience assets to be managed, and manage the enterprise experience assets to be managed based on the optimal management plan for the enterprise experience assets to be managed.

[0082] Preferably, the experience asset management module determines the optimal management scheme for the enterprise experience assets to be managed according to the asset feature information of the enterprise experience assets to be managed, including:

[0083] Determine similar managed enterprise experience assets based on the asset profile of the enterprise experience asset to be managed and the asset profile of each managed enterprise experience asset included in the experience asset type that matches the enterprise experience asset to be managed;

[0084] Based on the optimal management plans of similar managed enterprise experience assets and enterprise experience asset retrieval requests, the optimal management plan for the enterprise experience assets to be managed is determined, wherein the optimal management plan at least includes the optimal asset segmentation plan (for example, the number of asset fragments, the size of each asset fragment, etc.) and the optimal distributed storage plan (for example, the storage location of each asset fragment, etc.).

[0085] Specifically, the portrait similarity of the asset portrait of the enterprise experience asset to be managed and the asset portrait of each managed enterprise experience asset included in the experience asset type that matches the enterprise experience asset to be managed can be calculated, and the managed enterprise experience assets whose portrait similarity is greater than the portrait similarity threshold are regarded as similar managed enterprise experience assets.

[0086] The optimal management solution for the enterprise experience assets to be managed can be determined through a solution generation model based on the optimal management solutions of similar managed enterprise experience assets and enterprise experience asset retrieval requests, wherein the solution generation model can be a convolutional neural network (CNN) model.

[0087] Preferably, the experience asset management module manages the enterprise experience assets to be managed according to the optimal management scheme of the enterprise experience assets to be managed, including:

[0088] According to the optimal asset segmentation plan, the enterprise experience assets to be managed are divided into multiple asset segments;

[0089] According to the optimal distributed storage solution, multiple asset fragments corresponding to the enterprise experience assets to be managed are stored.

[0090] The experience asset retrieval module can be used to receive an enterprise experience asset retrieval request initiated by a user end, determine target asset feature information based on the enterprise experience asset retrieval request, and retrieve the target enterprise experience asset to the user end based on the target asset feature information.

[0091] Preferably, the experience asset retrieval module receives an enterprise experience asset retrieval request initiated by a user terminal, and determines the experience asset type that matches the enterprise experience asset retrieval request according to the enterprise experience asset retrieval request, including:

[0092] Calculate the first matching parameter between the enterprise experience asset retrieval request and each second similar experience asset type group according to the central asset retrieval feature keyword corresponding to each second similar experience asset type group;

[0093] Determine a second similar experience asset type group that matches the enterprise experience asset retrieval request according to a first matching parameter between the enterprise experience asset retrieval request and each second similar experience asset type group;

[0094] Determine a second matching parameter between the enterprise experience asset retrieval request and each experience asset type included in the second similar experience asset type group that matches the enterprise experience asset retrieval request according to the edge asset retrieval feature keyword corresponding to each experience asset type included in the second similar experience asset type group that matches the enterprise experience asset retrieval request;

[0095] The experience asset type that matches the enterprise experience asset retrieval request is determined based on the enterprise experience asset retrieval request and a second matching parameter between each experience asset type included in a second similar experience asset type group that matches the enterprise experience asset retrieval request.

[0096] Specifically, based on the second keyword library, the keyword frequency distribution characteristics of the enterprise experience assets to be managed are extracted, and the initial asset retrieval feature keywords with a frequency greater than a frequency threshold are used as the initial asset retrieval feature keywords of the enterprise experience assets to be managed.

[0097] Calculate the degree of overlap between the initial asset retrieval feature keywords of the enterprise experience assets to be managed and the central asset retrieval feature keywords corresponding to each first similar experience asset type group as the first matching parameter between the enterprise experience assets to be managed and the second similar experience asset type group, and take the second similar experience asset type group whose first matching parameter is greater than the first matching parameter threshold as the second similar experience asset type group that matches the enterprise experience asset retrieval request.

[0098] Calculate the degree of overlap between the initial asset retrieval feature keywords of the enterprise experience asset to be managed and the marginal asset retrieval feature keywords corresponding to each experience asset type included in the second similar experience asset type group that matches the enterprise experience asset retrieval request as the second matching parameter between the enterprise experience asset to be managed and each experience asset type included in the second similar experience asset type group that matches the enterprise experience asset to be managed, and take the experience asset type whose second matching parameter is greater than the second matching parameter threshold as the experience asset type that matches the enterprise experience asset to be managed.

[0099] Preferably, the experience asset retrieval module retrieves the target enterprise experience assets to the user end, including:

[0100] Determine the target enterprise experience asset from the managed enterprise experience assets included in the experience asset type matching the enterprise experience asset to be managed;

[0101] According to the optimal management plan of the target enterprise's experience assets, the target enterprise's experience assets are retrieved to the user end.

[0102] Specifically, the managed enterprise experience assets included in the experience asset types that match the enterprise experience asset retrieval request are sorted. For example, the managed enterprise experience assets included in the experience asset types that match the enterprise experience asset retrieval request can be sorted based on the number of times the managed enterprise experience assets are retrieved, the emotional characteristics of the feedback information of the user who retrieves the managed enterprise experience assets, the reliability of the user who uploads the managed enterprise experience assets, etc., and the managed enterprise experience assets with higher rankings are used as target enterprise experience assets.

[0103] According to the optimal management plan of the target enterprise's experience assets, multiple asset fragments of the target enterprise's experience assets are retrieved, spliced ​​and restored into the target enterprise's experience assets, and the restored target enterprise's experience assets are retrieved to the user end.

[0104] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. An enterprise management system for enterprise experience asset management based on artificial intelligence, characterized in that: include: The experience asset acquisition module is used to receive the enterprise experience assets to be managed uploaded by the user; An experience asset analysis module, used to analyze the enterprise experience assets to be managed and determine asset feature information of the enterprise experience assets to be managed; An experience asset management module, used to determine the optimal management scheme of the enterprise experience assets to be managed according to the asset feature information of the enterprise experience assets to be managed, and manage the enterprise experience assets to be managed according to the optimal management scheme of the enterprise experience assets to be managed; The experience asset retrieval module is used to receive an enterprise experience asset retrieval request initiated by a user terminal, determine the experience asset type that matches the enterprise experience asset retrieval request based on the enterprise experience asset retrieval request, and retrieve the target enterprise experience asset to the user terminal.

2. The enterprise management system for enterprise experience asset management based on artificial intelligence according to claim 1 is characterized in that: The experience asset analysis module analyzes the enterprise experience assets to be managed to determine asset feature information of the enterprise experience assets to be managed, including: Access to multiple managed corporate experience assets; According to the plurality of managed enterprise experience assets and the experience asset type to which each of the managed enterprise experience assets belongs, determining a plurality of asset type keywords corresponding to each of the experience asset types; Determining asset search feature keywords corresponding to each type of experience asset according to the enterprise experience asset retrieval request of the plurality of managed enterprise experience assets; The asset characteristic information of the enterprise experience assets to be managed is determined according to a plurality of asset type keywords corresponding to each of the experience asset types and an asset search characteristic keyword corresponding to each of the experience asset types.

3. The enterprise management system for enterprise experience asset management based on artificial intelligence according to claim 2 is characterized in that: The experience asset analysis module determines a plurality of asset type keywords corresponding to each experience asset type according to the plurality of managed enterprise experience assets and the experience asset type to which each of the managed enterprise experience assets belongs, including: Establishing a first keyword library, wherein the first keyword library includes a plurality of initial asset type keywords; For each of the experience asset types, based on the managed enterprise experience assets corresponding to the experience asset type, determine the initial asset type keyword corresponding to the experience asset type, and determine the first correlation coefficient between any two initial asset type keywords corresponding to the experience asset type according to the managed enterprise experience assets corresponding to the experience asset type; For any two experience asset types, calculating the first keyword similarity of the two experience asset types according to the initial asset type keyword corresponding to each of the experience asset types and the first correlation coefficient between any two initial asset type keywords corresponding to each of the experience asset types; Determining a first similar experience asset type group according to the first keyword similarity of any two experience asset types, wherein the first similar experience asset type group includes at least two experience asset types; For each of the first similar experience asset type groups, the central asset type keyword corresponding to the first similar experience asset type group and the marginal asset type keyword corresponding to each of the experience asset types included in the first similar experience asset type group are determined based on the first correlation coefficient between the initial asset type keyword corresponding to each of the experience asset types and any two initial asset type keywords corresponding to each of the experience asset types, wherein the multiple asset type keywords corresponding to the experience asset type include the central asset type keyword corresponding to the first similar experience asset type group to which the experience asset type belongs and the marginal asset type keyword corresponding to the experience asset type.

4. The enterprise management system for enterprise experience asset management based on artificial intelligence according to claim 3 is characterized in that: The experience asset analysis module determines, according to the enterprise experience asset retrieval request of the plurality of managed enterprise experience assets, asset search feature keywords corresponding to each experience asset type, including: Establishing a second keyword library, wherein the second keyword library includes a plurality of initial asset search feature keywords; For each of the experience asset types, based on the enterprise experience asset retrieval request of the managed enterprise experience assets corresponding to the experience asset type, determine the initial asset retrieval feature keyword corresponding to the experience asset type, and determine the second correlation coefficient between any two initial asset retrieval feature keywords corresponding to the experience asset type according to the enterprise experience asset retrieval request of the managed enterprise experience assets corresponding to the experience asset type; For any two types of experience assets, the second keyword similarity of the two types of experience assets is calculated according to the second correlation coefficient between the initial asset search feature keyword corresponding to each type of experience asset and any two initial asset search feature keywords corresponding to each type of experience asset; Determining a second similar experience asset type group according to the second keyword similarity of any two experience asset types, wherein the second similar experience asset type group includes at least two experience asset types; For each of the second similar experience asset type groups, the central asset retrieval feature keywords corresponding to the second similar experience asset type group and the marginal asset retrieval feature keywords corresponding to each of the experience asset types included in the second similar experience asset type group are determined based on the second correlation coefficient between the initial asset retrieval feature keywords corresponding to each of the experience asset types and any two initial asset retrieval feature keywords corresponding to each of the experience asset types, wherein the asset retrieval feature keywords corresponding to the experience asset type include the central asset retrieval feature keywords corresponding to the second similar experience asset type group to which the experience asset type belongs and the marginal asset retrieval feature keywords corresponding to the experience asset type.

5. The enterprise management system for enterprise experience asset management based on artificial intelligence according to claim 4 is characterized in that: The experience asset analysis module determines the asset feature information of the enterprise experience assets to be managed according to a plurality of asset type keywords corresponding to each experience asset type and an asset search feature keyword corresponding to each experience asset type, including: Determining a first attribution parameter between the enterprise experience asset to be managed and each of the first similar experience asset type groups according to the central asset type keyword corresponding to each of the first similar experience asset type groups; Determine a first similar experience asset type group that matches the enterprise experience asset to be managed according to a first attribution parameter between the enterprise experience asset to be managed and each of the first similar experience asset type groups; Determine a second attribution parameter between the enterprise experience asset to be managed and each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed, according to the marginal asset type keyword corresponding to each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed; Determine the experience asset type that matches the enterprise experience asset to be managed according to a second attribution parameter between the enterprise experience asset to be managed and each experience asset type included in the first similar experience asset type group that matches the enterprise experience asset to be managed; Extracting an asset profile of the enterprise experience asset to be managed according to the central asset type keyword and the edge asset type keyword corresponding to the experience asset type matched by the enterprise experience asset to be managed; According to the central asset retrieval feature keywords and the edge asset retrieval feature keywords corresponding to the experience asset type matching the enterprise experience assets to be managed, the retrieval features of the enterprise experience assets to be managed are extracted, wherein the asset feature information of the enterprise experience assets to be managed includes the asset portrait and retrieval features of the enterprise experience assets to be managed.

6. The enterprise management system for enterprise experience asset management based on artificial intelligence according to claim 5 is characterized in that: The asset portrait of the enterprise experience assets to be managed includes at least the experience asset type matching the enterprise experience assets to be managed, the word frequency of each of the central asset type keywords, the word frequency of each of the marginal asset type keywords, the association parameters between any two central asset type keywords, the association parameters between any two marginal asset type keywords, and the association parameters between any central asset type keyword and any marginal asset type keyword.

7. The enterprise management system for enterprise experience asset management based on artificial intelligence according to claim 5 or 6, characterized in that: The experience asset management module determines the optimal management scheme of the enterprise experience assets to be managed according to the asset feature information of the enterprise experience assets to be managed, including: Determine similar managed enterprise experience assets according to the asset portrait of the enterprise experience asset to be managed and the asset portrait of each managed enterprise experience asset included in the experience asset type matching the enterprise experience asset to be managed; Based on the optimal management scheme of similar managed enterprise experience assets and the enterprise experience asset retrieval request, the optimal management scheme of the enterprise experience assets to be managed is determined, wherein the optimal management scheme at least includes an optimal asset segmentation scheme and an optimal distributed storage scheme.

8. The enterprise management system for enterprise experience asset management based on artificial intelligence according to claim 7 is characterized in that: The experience asset management module manages the enterprise experience assets to be managed according to the optimal management solution of the enterprise experience assets to be managed, including: According to the optimal asset segmentation scheme, the enterprise experience assets to be managed are segmented into a plurality of asset segments; According to the optimal distributed storage solution, multiple asset fragments corresponding to the enterprise experience assets to be managed are stored.

9. The enterprise management system for enterprise experience asset management based on artificial intelligence according to any one of claims 4 to 6, characterized in that: The experience asset retrieval module receives an enterprise experience asset retrieval request initiated by a user terminal, and determines the experience asset type matching the enterprise experience asset retrieval request according to the enterprise experience asset retrieval request, including: Calculate the first matching parameter between the enterprise experience asset retrieval request and each of the second similar experience asset type groups according to the central asset retrieval feature keywords corresponding to each of the second similar experience asset type groups; Determine a second similar experience asset type group that matches the enterprise experience asset retrieval request according to a first matching parameter between the enterprise experience asset retrieval request and each of the second similar experience asset type groups; Determine a second matching parameter between the enterprise experience asset retrieval request and each experience asset type included in the second similar experience asset type group that matches the enterprise experience asset retrieval request according to the edge asset retrieval feature keyword corresponding to each experience asset type included in the second similar experience asset type group that matches the enterprise experience asset retrieval request; The experience asset type that matches the enterprise experience asset retrieval request is determined based on the enterprise experience asset retrieval request and a second matching parameter between each experience asset type included in a second similar experience asset type group that matches the enterprise experience asset retrieval request.

10. The enterprise management system for enterprise experience asset management based on artificial intelligence according to claim 9, characterized in that: The experience asset retrieval module retrieves the target enterprise experience assets to the user end, including: Determine the target enterprise experience asset from the managed enterprise experience assets included in the experience asset type matching the enterprise experience asset to be managed; According to the optimal management plan of the target enterprise's experience assets, the target enterprise's experience assets are retrieved to the user end.

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