An industrial chain data analysis method and system for enterprise positioning

Abstract

The present application discloses a method and system for analyzing industrial chain data for enterprise positioning. By extracting industry characteristics according to industry field information, industry characteristic information is obtained; according to enterprise basic information, enterprise characteristic information is determined; based on the industry characteristic information and enterprise characteristic information, enterprise positioning analysis is carried out to determine the enterprise industrial chain positioning segment; according to the industry characteristic information and enterprise chain positioning segment, a customer group portrait is obtained; according to the enterprise basic information, enterprise transformation projects are determined and targeted digital block matching is carried out for the enterprise transformation projects and the customer group portrait to obtain a block matching result; based on the block matching result, enterprise transformation information is determined. It realizes digital transformation on the basis of meeting the requirements of the customer group for industrial chain positioning, ensures the reliability of the transformation, and solves the technical problems in the prior art that there is a lack of positioning analysis of the customer group in digital transformation, resulting in blind transformation and poor transformation effects.

Description

Technical Field

[0001] This application relates to the technical field of digital transformation, and particularly to a method and system for analyzing industrial chain data for enterprise positioning. Background Art

[0002] With the development of the Internet, digitization has penetrated into all walks of life. In order to meet the development of the market and keep up with the times, digital transformation of enterprises is a corresponding choice made by many enterprises. How to carry out digital transformation is a common concern at present. The forms of digitization are diverse, and it is necessary to fit the development characteristics of one's own enterprise. Blindly carrying out digital transformation not only increases investment, but also does not bring the expected effect to the development of the enterprise.

[0003] It is found that the above technology has at least the following technical problems:

[0004] In the prior art, there is a lack of positioning analysis of customer groups in digital transformation, resulting in blind transformation and poor transformation effects. Summary of the Invention

[0005] The purpose of this application is to provide a method and system for analyzing industrial chain data for enterprise positioning, so as to solve the technical problems in the prior art that there is a lack of positioning analysis of customer groups in digital transformation, resulting in blind transformation and poor transformation effects. It achieves the technical effect of analyzing the industry field characteristics of an enterprise, determining the positioning segment of its industrial chain, analyzing according to the positioning of the industrial chain and the customer portrait group, and performing targeted digital block matching on the enterprise information according to the analyzed data, so that the enterprise can achieve digital transformation on the basis of meeting the industrial chain positioning.

[0006] In view of the above problems, the embodiments of this application provide a method and system for analyzing industrial chain data for enterprise positioning.

[0007] In a first aspect, this application provides a method for analyzing industrial chain data for enterprise positioning. The method includes: obtaining enterprise basic information, where the enterprise basic information includes industry field information; extracting industry characteristics according to the industry field information to obtain industry characteristic information; determining enterprise characteristic information according to the enterprise basic information; performing enterprise positioning analysis based on the industry characteristic information and the enterprise characteristic information to determine the enterprise industrial chain positioning segment; obtaining a customer group portrait according to the industry characteristic information and the enterprise chain positioning segment; determining an enterprise transformation project according to the enterprise basic information, and performing targeted digital block matching on the enterprise transformation project and the customer group portrait to obtain a block matching result; and determining enterprise transformation information based on the block matching result.

[0008] On the other hand, the present application also provides an industrial chain data analysis system for enterprise positioning, which is used to execute an industrial chain data analysis method for enterprise positioning as described in the first aspect. The system includes:

[0009] A first acquisition unit, which is used to acquire enterprise basic information, and the enterprise basic information includes industry field information;

[0010] A second acquisition unit, which is used to extract industry characteristics according to the industry field information to obtain industry characteristic information;

[0011] A first determination unit, which is used to determine enterprise characteristic information according to the enterprise basic information;

[0012] A second determination unit, which is used to perform enterprise positioning analysis based on the industry characteristic information and the enterprise characteristic information to determine the enterprise industrial chain positioning segment;

[0013] A third acquisition unit, which is used to obtain a customer group portrait according to the industry characteristic information and the enterprise chain positioning segment;

[0014] A fourth acquisition unit, which is used to determine an enterprise transformation project according to the enterprise basic information, and perform targeted digital block matching on the enterprise transformation project and the customer group portrait to obtain a block matching result;

[0015] A third determination unit, which is used to determine enterprise transformation information based on the block matching result.

[0016] In a third aspect, the present application also provides an industrial chain data analysis system for enterprise positioning, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the method described in the first aspect are implemented.

[0017] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the method described in any item of the first aspect is implemented.

[0018] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0019] 1. By analyzing the industry field characteristics of an enterprise, the positioning segment of its industrial chain is determined. Based on the positioning of the industrial chain and the analysis of the customer portrait group, and according to the analyzed data, targeted digital block matching of the enterprise's information is carried out. For the matching results, corresponding digital transformation decisions are made based on the evaluation results in terms of technology and customer needs, achieving the technical effect that the enterprise can achieve digital transformation on the basis of meeting the requirements of the customer group positioned by the industrial chain, ensuring the acceptance degree on the customer side and guaranteeing the benefits after transformation.

[0020] 2. By obtaining the customer characteristics of the positioning segment according to the positioning segment of the enterprise chain; obtaining the industry customer group according to the industry characteristic information; inputting the customer characteristics of the positioning segment and the industry customer group into the customer portrait matching model, and obtaining the output result of the customer portrait matching model, where the output result includes the customer group portrait; achieving the technical effect of joining the neural network model to quickly and reliably analyze the customer group portrait of the industrial chain positioning segment, laying a foundation for subsequent digital transformation based on the customer characteristics of the corresponding positioning segment of the enterprise.

[0021] 3. By performing weight analysis based on the feature matching results to determine the positioning segment of the enterprise's industrial chain, using the principal component analysis weight algorithm to reduce the dimension of the matching feature set, and using the main features to position the industrial chain stage of the enterprise, achieving the technical effect of using the principal component features to position the enterprise, ensuring the reliability of the features and the accuracy of the positioning result, and avoiding the situation where the result of the enterprise's industrial chain positioning segment is inaccurate due to the interference of non-positioning main features.

[0022] The above description is only an overview of the technical solution of this application. In order to be able to more clearly understand the technical means of this application, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of this application more obvious and understandable, the following specifically gives the specific implementation manners of this application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the drawings required to be used in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only exemplary, and for those of ordinary skill in the art, other drawings can be obtained according to the provided drawings without creative efforts.

[0024] Figure 1 It is a schematic flowchart of a method for analyzing industrial chain data for enterprise positioning according to an embodiment of this application;

[0025] Figure 2 It is a schematic structural diagram of a system for analyzing industrial chain data for enterprise positioning according to an embodiment of this application;

[0026] Figure 3 This is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.

[0027] Explanation of reference numerals: First acquisition unit 11, second acquisition unit 12, first determination unit 13, second determination unit 14, third acquisition unit 15, fourth acquisition unit 16, third determination unit 17, bus 300, receiver 301, processor 302, transmitter 303, memory 304, bus interface 305. Detailed implementation manners

[0028] By providing an industrial chain data analysis method and system for enterprise positioning in an embodiment of the present application, the technical problem in the prior art of lacking positioning analysis of customer groups in digital transformation, resulting in blind transformation and poor transformation effects, is solved.

[0029] Next, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the example embodiments described herein. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the scope of protection of the present application. Additionally, it should be noted that for the sake of description, only parts related to the present application are shown in the accompanying drawings rather than all.

[0030] The general idea of the technical solution provided by the present application is as follows:

[0031] Based on the industry characteristic information and the enterprise characteristic information, perform enterprise positioning analysis to determine the enterprise industrial chain positioning segment; according to the industry characteristic information and the enterprise chain positioning segment, obtain the customer group portrait; according to the enterprise basic information, determine the enterprise transformation project, and perform targeted digital block matching for the enterprise transformation project and the customer group portrait to obtain the block matching result; based on the block matching result, determine the enterprise transformation information. It achieves the technical effect of analyzing the industry field characteristics of an enterprise to determine its industrial chain positioning segment, analyzing based on the industrial chain positioning and the customer portrait group, and performing targeted digital block matching on the enterprise information according to the analyzed data, enabling the enterprise to achieve digital transformation on the basis of meeting the industrial chain positioning.

[0032] After introducing the basic principle of the present application, the various non-limiting implementation manners of the present application will be specifically introduced below with reference to the accompanying drawings of the specification.

[0033] Embodiment 1

[0034] Please refer to the attached Figure 1, an embodiment of the present application provides a method for analyzing industrial chain data for enterprise positioning, and the method includes:

[0035] Step S100: Obtain enterprise basic information, where the enterprise basic information includes industry field information;

[0036] Specifically, the enterprise basic information is the content of the enterprise's basic data, including enterprise name, enterprise qualification, asset status, scale, business scope, address, industry field, etc. Among them, the industry field information determines the content introduction of the corresponding field of the industry where the enterprise is located, and can segment and determine the specific business scope and customer group of the enterprise, thus laying a foundation for subsequent analysis.

[0037] Step S200: Extract industry characteristics according to the industry field information to obtain industry characteristic information;

[0038] Further, the extracting industry characteristics according to the industry field information to obtain industry characteristic information includes: determining domain attribute characteristics according to the industry field information; obtaining industry industrial chain division criteria based on the domain attribute characteristics, and extracting division criterion characteristics based on the industry industrial chain division criteria; integrating industry characteristics according to the domain attribute characteristics and the division criterion characteristics to obtain the industry characteristic information.

[0039] Specifically, feature extraction is performed according to the specific description information of industry characteristics and domain-related content in the industry field information. The industry characteristic information is the label information that can express the specific content of the industry field determined after keyword and semantic analysis of the description content in the industry field information. Among them, it includes determining the domain attribute of the industry field information, analyzing the attribute characteristics using the industry field attribute, so as to determine the domain attribute characteristics. Different fields face different industrial structures. For the determination of the domain attribute, the industrial chain characteristics in this attribute are determined. For example, for the chemical industry, mechanical processing, textile industry, etc., different attributes correspond to different industry industrial chains. The self-characteristics of the industry industrial chain will be used for corresponding stage divisions, upstream, midstream, and downstream. Each stage corresponds to its own division criterion characteristics, and the industrial chain division situation of the industry field is described by characteristics. The domain attribute characteristics and the industrial chain division criterion characteristics are used for feature fusion, that is, the specific characteristics of the industry attribute are used for the concrete description of the industrial chain division criterion characteristics, and the industry characteristics are used for the standard description of each industrial chain partition. Through the industry characteristic information, the industry characteristics, performance content, and data characteristics of each stage in this industry can be correspondingly described.

[0040] Step S300: Determine enterprise characteristic information according to the enterprise basic information;

[0041] Specifically, the description content in the enterprise basic information is used for feature extraction to obtain the feature tags of the enterprise. The enterprise feature information can be used to describe and locate the features of the enterprise such as scale, status, scope, equipment, and funds, and to portrait the enterprise.

[0042] Step S400: Based on the industry feature information and the enterprise feature information, conduct enterprise positioning analysis to determine the enterprise industrial chain positioning segment;

[0043] Further, the conducting enterprise positioning analysis based on the industry feature information and the enterprise feature information to determine the enterprise industrial chain positioning segment includes: dividing the industry feature information according to the industry industrial chain division standard; constructing an industrial chain feature list based on the industry feature information divided according to the industrial chain; performing feature matching according to the enterprise feature information in the industrial chain feature list to obtain a feature matching result; and determining the enterprise industrial chain positioning segment based on the feature matching result.

[0044] Specifically, the industry features are divided according to the industrial chain division standard based on the industry feature information to construct an industrial chain feature list. The industrial chain feature list divides the features of each stage of the industrial chain for the industry feature information according to the industrial chain division standard, and for each industrial stage, it corresponds to what kind of industry features, and a mapping relationship is constructed between the industry features and the industrial chain stage division. Through the mapping relationship between the industry features and the stage division in the industrial chain feature list, the enterprise industrial chain positioning analysis is realized. The enterprise feature information is used for matching in the industrial chain feature list to match the industry features that fit it, and using the mapping relationship between the industry feature and the industrial chain division stage, the enterprise industrial chain positioning segment corresponding to the enterprise is determined. The enterprise industrial chain positioning segment is the stage segment information where the currently analyzed enterprise is located in the industrial chain structure, that is, which stage of the industrial chain it is in.

[0045] Step S500: Obtain the customer group portrait according to the industry feature information and the enterprise chain positioning segment;

[0046] Further, the obtaining the customer group portrait according to the industry feature information and the enterprise chain positioning segment includes: obtaining the positioning segment customer features according to the enterprise chain positioning segment; obtaining the industry customer group according to the industry feature information; inputting the positioning segment customer features and the industry customer group into the customer portrait matching model to obtain the output result of the customer portrait matching model, and the output result includes the customer group portrait.

[0047] Specifically, industry characteristic information is used to determine the customer groups in the industry. Based on the characteristics of the industry's customer groups, the characteristics of customer groups at different stages are analyzed according to the characteristics of different segments of the industrial chain, so as to analyze the characteristics of different customer groups of enterprises at different stages, describe the customer characteristics at different stages of the industrial chain, and achieve the effect of accurately positioning the customer groups. To further improve the accuracy of creating customer group portraits at different stages, the embodiments of the present application use a neural network model for machine learning and output, which improves the operation speed and ensures the accuracy of the analysis results. The historical data processed through the customer group portraits at different stages is used as training data, and the customer group portrait results are used as identification information. Each set of training data includes the customer characteristics of the positioning segment, the industry customer groups, and the identification information indicating the customer group portraits. Through the learning and convergence of the training data, the neural network model learns the logical data relationship between the customer characteristics of the positioning segment, the industry customer groups, and the customer group portraits at different stages, and is verified through the results of the identification information. When the input customer characteristics of the positioning segment and the industry customer groups are input, the customer group portrait information corresponding to the positioning segment is output. The identified stage customer group portrait is compared with the customer group portrait information corresponding to the positioning segment output. If the similarity between the two is close to the same or until the same position, the training ends. Otherwise, the loss function operation is performed on the output result and the identification data, and the operation result is returned to the neural network model for continued training to continuously optimize the model until the output result is the same as the identification information of the training data or reaches the preset training convergence result, and then the training ends to obtain a customer portrait matching model. The customer portrait matching model can realize that when the customer characteristics of the positioning segment and the industry customer groups are input, the customer group portrait of the industry matching the input positioning segment of the industrial chain is output. Thus, the technical effect of quickly and reliably analyzing the customer group portrait of the positioning segment of the industrial chain is achieved, laying a foundation for the subsequent digital transformation based on the customer characteristics of the corresponding positioning segment of the enterprise.

[0048] Step S600: According to the enterprise basic information, determine the enterprise transformation project, and perform targeted digital block matching on the enterprise transformation project and the customer group portrait to obtain a block matching result;

[0049] Further, based on the enterprise basic information, determine an enterprise transformation project, and perform targeted digital block matching for the enterprise transformation project and the customer group portrait to obtain a block matching result, including: obtaining group demand characteristics according to the customer group portrait; obtaining transformation matching technology information according to the enterprise transformation project; performing matching feature analysis based on the enterprise transformation project and the transformation matching technology information to determine project transformation technology characteristics; performing matching based on the group demand characteristics and the project transformation technology characteristics to obtain a matching degree; determining whether the matching degree meets a predetermined requirement; when it is satisfied, determining the transformation matching technology information and the project transformation technology characteristics.

[0050] Further, after determining whether the matching degree meets the predetermined requirement, it includes: when the matching degree does not meet the predetermined requirement, obtaining a feature deviation value according to the group demand characteristics and the project transformation technology characteristics; obtaining a deviation support technology according to the feature deviation value; obtaining a technology fusion evaluation result according to the deviation support technology and the transformation matching technology information; when the technology fusion evaluation result meets the fusion requirement, obtaining a fusion reminder information.

[0051] Specifically, based on the enterprise's basic information, determine the enterprise transformation project. The enterprise transformation project can be a pre-defined project entered, that is, which project the enterprise currently needs to carry out targeted digital transformation for, or corresponding project recommendations can be made according to the enterprise scale, business scope, and current business characteristics given in the enterprise's basic information for the current digital transformation characteristics. Conduct targeted digital block matching for the enterprise transformation project and the customer group portrait. Specifically, first analyze the demand characteristics of the customer group in the customer group portrait to obtain the demand characteristics of the current corresponding customer group. Conduct feature analysis on the needs of the customer group and the current transformation project to evaluate whether the current transformation project matches the customer group's needs. The digital block mainly determines the digital transformation direction corresponding to the transformation project and the corresponding technical support. Determine the corresponding transformation direction for the current enterprise transformation project, such as building a marketing platform, etc. Determine the transformation matching technology information corresponding to the direction that needs to be transformed. The digital transformation direction realized by the current transformation matching technology information and the determined digital block correspond to the customer group's needs, that is, the customer's needs can be realized through the determined digital block, then the block matching result is a successful match. The block matching result includes the matching result, the matching project direction, the matching technology information, etc. Based on the information in the block matching result, the digital transformation direction and feasibility can be determined. If the matching degree between the current transformation direction and the result of technology implementation and the customer group's needs does not meet the requirements, that is, the result realized by the current technology transformation block does not meet the customer group's demand characteristics, then the block matching result is an unsuccessful match. At the same time, according to the differences between the matching results, indicate which aspect of the customer's needs cannot meet the requirements, and then conduct a technical analysis according to the feature deviation value. If the current feature deviation value is to be realized, what technical support is needed, such as the existing technology in the current market or the technology that needs to be developed. Use the determined deviation support technology and the current determined transformation matching technology information to conduct a technical feature analysis to determine whether there is compatibility. If the two can be integrated, then give the corresponding reminder. The user can receive the current analysis result according to the integration reminder information and make corresponding processing according to the suggestions given by the analysis result to ensure the harmony between the technical aspect and the customer demand aspect of the digital transformation. On the basis of ensuring the demand characteristics of the customer group, carry out digital transformation to meet the requirements of the market and ensure the acceptance of the customer group, avoiding the low response degree of the customer group and affecting the post-transformation revenue effect.

[0052] Step S700: Based on the block matching result, determine the enterprise transformation information.

[0053] Specifically, for the content given in the block matching result, determine the direction of enterprise transformation to give guidance results for digital transformation. The block matching result includes the matching results of the technical aspect and the customer demand aspect, and whether the two-way requirements are met. For the technical aspect matching result and the demand aspect matching result in the block matching result, determine whether to carry out digital transformation, or how to carry out digital transformation, and whether technical R & D and improvement are required, etc., which are guiding decision-making information for enterprise transformation. By analyzing the industry field characteristics of the enterprise, the positioning segment of its industrial chain is determined. According to the positioning of the industrial chain and the analysis of the customer portrait group, and based on the analyzed data, targeted digital block matching of the enterprise information is carried out, enabling the enterprise to achieve digital transformation on the basis of meeting the requirements of the customer group for the industrial chain positioning, ensuring the acceptance degree of the customer side, and guaranteeing the technical effect of the post-transformation revenue. Thus, it solves the technical problem in the prior art that there is a lack of positioning analysis of the customer group in digital transformation, resulting in blind transformation and poor post-transformation effects.

[0054] Further, based on the feature matching result, perform weight analysis to determine the positioning segment of the enterprise industrial chain, including: obtaining a matching feature set according to the feature matching result; performing a decentralization process on the matching feature set to obtain a decentralized feature set; obtaining a covariance matrix based on the decentralized feature set; performing an operation on the covariance matrix to obtain the first eigenvector of the covariance matrix; projecting the matching feature set onto the first eigenvector to obtain a dimensionality-reduced feature set; obtaining the variance contribution rate of the dimensionality-reduced feature set based on the dimensionality-reduced feature set; performing normalization processing of the index weights according to the variance contribution rate to obtain feature weight values, performing an operation on the matching feature set based on the feature weight values to determine screening feature information; comparing the screening feature information in the industrial chain feature list to determine the positioning segment of the enterprise industrial chain.

[0055] Specifically, in the process of determining the enterprise industrial chain positioning segment based on the feature matching result, the embodiment of the present application adopts the principal component weight algorithm to process the feature matching result. Since there will be an overlap in the enterprise features with the features of other stages in the industrial chain feature list in this industry field, after all, the industry fields are the same, there will be multiple matching features or cross-stage features in the feature matching. If an accurate positioning of the enterprise is to be carried out, the weight calculation of each matching feature is performed, the factors with small influence are filtered, and the features that play an important role are extracted, so as to avoid the interference of multiple features, and the principal component is used to realize the positioning analysis of the enterprise industrial chain. By performing a de-centralization process on the matching feature set, that is, all the feature sets after successful matching, a confidence interval for finding the data feature within the average value range is determined, that is, the de-centered feature set. The variance operation is performed on the de-centered feature set, and the data is dimensionally reduced by using the variance operation result. The eigenvalues and eigenvectors of the covariance matrix are calculated, the eigenvalues are sorted, and the first few largest eigenvalues and the corresponding eigenvectors are retained. The matching feature set is transformed into the determined eigenvector to construct a new space, realizing the dimensionality reduction processing of the feature data. After the dimensionality reduction processing, factor analysis is performed using the variance calculation result of the obtained features. Factor analysis mainly calculates the cumulative variance contribution of the principal components to the variance values of the main features. When the variance contribution reaches the preset range, that is, the determined principal component can describe the matching features of the enterprise and can reflect the information content of all indicators, then the principal component is used for the industrial chain positioning analysis of the enterprise. The index weight is the normalization of the weighted average of the coefficients of the feature index in each principal component with the variance contribution rate of the principal component as the weight, so as to determine the weight value of the principal component. Based on the feature weight value, the screening feature information is determined, and the screening feature information is the principal component feature determined according to the weight value; based on the screening feature information, a comparison is made in the industrial chain feature list to determine the enterprise industrial chain positioning segment, avoiding the interference of other features and affecting the reliability of the enterprise industrial chain positioning segment result.

[0056] In summary, the embodiment of the present application has the following technical effects:

[0057] 1. By analyzing the industry field features of the enterprise, the positioning segment of its industrial chain is determined. According to the positioning of the industrial chain and the analysis of the customer portrait group, and based on the analyzed data, targeted digital block matching of the enterprise information is carried out. For the evaluation results on the technical aspect and the customer demand aspect of the matching result, corresponding digital transformation decisions are made, achieving the technical effect that the enterprise can realize digital transformation on the basis of meeting the requirements of the customer group for the industrial chain positioning, ensuring the acceptance degree of the customer side, and guaranteeing the benefits after the transformation.

[0058] 2. By obtaining the customer characteristics of the positioning segment according to the enterprise chain positioning segment, obtaining the industry customer group according to the industry characteristic information, and inputting the customer characteristics of the positioning segment and the industry customer group into the customer portrait matching model to obtain the output result of the customer portrait matching model, where the output result includes the customer group portrait, the technical effect of realizing fast and reliable analysis of the customer group portrait of the industrial chain positioning segment by adding a neural network model is achieved, laying a foundation for subsequent digital transformation based on the customer characteristics of the corresponding positioning segment of the enterprise.

[0059] 3. By performing weight analysis based on the feature matching result to determine the enterprise industrial chain positioning segment, using the principal component analysis weight algorithm to perform feature dimensionality reduction on the matching feature set, and using the main features to perform the positioning of the enterprise's industrial chain stage, the technical effect of using the principal component features for enterprise positioning, ensuring the reliability of the features and the accuracy of the positioning result, and avoiding the inaccurate situation of the enterprise industrial chain positioning segment result caused by the interference of non-positioning main features is achieved.

[0060] Embodiment 2

[0061] Based on a method for analyzing industrial chain data for enterprise positioning in the foregoing embodiment with the same inventive concept, the present invention also provides a system for analyzing industrial chain data for enterprise positioning. Please refer to the appendix Figure 2 , the system includes:

[0062] The first obtaining unit 11 is used to obtain enterprise basic information, where the enterprise basic information includes industry field information;

[0063] The second obtaining unit 12 is used to extract industry characteristics according to the industry field information to obtain industry characteristic information;

[0064] The first determining unit 13 is used to determine enterprise characteristic information according to the enterprise basic information;

[0065] The second determining unit 14 is used to perform enterprise positioning analysis based on the industry characteristic information and the enterprise characteristic information to determine the enterprise industrial chain positioning segment;

[0066] The third obtaining unit 15 is used to obtain the customer group portrait according to the industry characteristic information and the enterprise chain positioning segment;

[0067] The fourth obtaining unit 16 is used to determine the enterprise transformation project according to the enterprise basic information, and perform targeted digital block matching on the enterprise transformation project and the customer group portrait to obtain the block matching result;

[0068] A third determination unit 17, configured to determine enterprise transformation information based on the block matching result.

[0069] Further, the system further includes:

[0070] A fourth determination unit, configured to determine domain attribute features according to the industry domain information;

[0071] A first execution unit, configured to obtain an industry industrial chain division standard based on the domain attribute features, and extract division standard features based on the industry industrial chain division standard;

[0072] A fifth obtaining unit, configured to perform industry feature integration according to the domain attribute features and the division standard features to obtain the industry feature information.

[0073] Further, the system further includes:

[0074] A second execution unit, configured to perform industrial chain feature division on the industry feature information according to the industry industrial chain division standard;

[0075] A first construction unit, configured to construct an industrial chain feature list based on the industry feature information divided according to the industrial chain;

[0076] A sixth obtaining unit, configured to perform feature matching in the industrial chain feature list according to the enterprise feature information to obtain a feature matching result;

[0077] A fifth determination unit, configured to perform weight analysis based on the feature matching result to determine the enterprise industrial chain positioning segment.

[0078] Further, the system further includes:

[0079] A seventh obtaining unit, configured to obtain a matching feature set according to the feature matching result;

[0080] An eighth obtaining unit, configured to perform a decentralization process on the matching feature set to obtain a decentralized feature set;

[0081] A ninth obtaining unit, configured to obtain a covariance matrix based on the decentralized feature set;

[0082] A tenth obtaining unit, configured to perform an operation on the covariance matrix to obtain a first eigenvector of the covariance matrix;

[0083] An eleventh acquisition unit, configured to project the matching feature set onto the first feature vector to obtain a dimensionality-reduced feature set;

[0084] A twelfth acquisition unit, configured to obtain the variance contribution rate of the dimensionality-reduced feature set based on the dimensionality-reduced feature set;

[0085] A third execution unit, configured to perform normalization processing on the index weights according to the variance contribution rate to obtain feature weight values, and perform operations on the matching feature set based on the feature weight values to determine the screened feature information;

[0086] A sixth determination unit, configured to perform comparison in the industrial chain feature list based on the screened feature information to determine the enterprise industrial chain positioning segment.

[0087] Further, the system further includes:

[0088] A thirteenth acquisition unit, configured to obtain the positioning segment customer features according to the enterprise chain positioning segment;

[0089] A fourteenth acquisition unit, configured to obtain the industry customer groups according to the industry feature information;

[0090] A fourth execution unit, configured to input the positioning segment customer features and the industry customer groups into a customer portrait matching model to obtain the output result of the customer portrait matching model, where the output result includes the customer group portrait.

[0091] Further, the system further includes:

[0092] A fifteenth acquisition unit, configured to obtain the group demand features according to the customer group portrait;

[0093] A sixteenth acquisition unit, configured to obtain the transformation matching technology information according to the enterprise transformation project;

[0094] A seventh determination unit, configured to perform matching feature analysis according to the enterprise transformation project and the transformation matching technology information to determine the project transformation technology features;

[0095] A seventeenth acquisition unit, configured to perform matching based on the group demand features and the project transformation technology features to obtain a matching degree;

[0096] A first judgment unit, configured to judge whether the matching degree meets a predetermined requirement;

[0097] An eighth determination unit, configured to determine the transformation matching technical information and the project transformation technical features when conditions are met.

[0098] Furthermore, the system further includes:

[0099] An eighteenth acquisition unit, configured to obtain a feature deviation value according to the group demand characteristics and the project transformation technical features when the matching degree does not meet the predetermined requirements;

[0100] A nineteenth acquisition unit, configured to obtain deviation support technologies according to the feature deviation value;

[0101] A twentieth acquisition unit, configured to obtain a technology integration evaluation result according to the deviation support technologies and the transformation matching technical information;

[0102] A twenty-first acquisition unit, configured to obtain a fusion reminder message when the technology integration evaluation result meets the fusion requirements.

[0103] The various embodiments in this specification are described in a progressive manner. Each embodiment focuses on the differences from other embodiments. The Figure 1 A method and specific example for analyzing the industrial chain data of enterprise positioning in the first embodiment are equally applicable to a system for analyzing the industrial chain data of enterprise positioning in this embodiment. Through the detailed description of the method for analyzing the industrial chain data of enterprise positioning above, those skilled in the art can clearly know the system for analyzing the industrial chain data of enterprise positioning in this embodiment. Therefore, for the sake of simplicity of the specification, it will not be elaborated here. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple. For the relevant parts, reference can be made to the description in the method section.

[0104] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to these embodiments will be obvious to those skilled in the art. The general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to these embodiments shown herein, but will be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0105] Exemplary electronic device

[0106] Next, reference is made to Figure 3 to describe the electronic device according to an embodiment of the present application.

[0107] Figure 3The figure shows a schematic structural diagram of an electronic device according to an embodiment of the present application.

[0108] Based on the inventive concept of a method for analyzing the industrial chain data of an enterprise positioning in the foregoing embodiment, the present invention further provides a system for analyzing the industrial chain data of an enterprise positioning, on which a computer program is stored, and when the program is executed by a processor, it implements the steps of any one of the methods for analyzing the industrial chain data of an enterprise positioning described above.

[0109] Among them, in Figure 3 In the figure, the bus architecture (represented by bus 300), bus 300 may include any number of interconnected buses and bridges, and bus 300 links various circuits including one or more processors represented by processor 302 and a memory represented by memory 304 together. Bus 300 may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art, and therefore, will not be further described herein. Bus interface 305 provides an interface between bus 300 and receiver 301 and transmitter 303. Receiver 301 and transmitter 303 may be the same element, that is, a transceiver, which provides a unit for communicating with various other devices on the transmission medium.

[0110] Processor 302 is responsible for managing bus 300 and general processing, while memory 304 may be used to store data used by processor 302 when executing operations.

[0111] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0112] The present application provides a method and system for analyzing industrial chain data for enterprise positioning. By obtaining enterprise basic information, the enterprise basic information includes industry field information; extracting industry characteristics according to the industry field information to obtain industry characteristic information; determining enterprise characteristic information according to the enterprise basic information; performing enterprise positioning analysis based on the industry characteristic information and the enterprise characteristic information to determine the enterprise industrial chain positioning segment; obtaining a customer group portrait according to the industry characteristic information and the enterprise chain positioning segment; determining an enterprise transformation project according to the enterprise basic information, and performing targeted digital block matching on the enterprise transformation project and the customer group portrait to obtain a block matching result; determining enterprise transformation information based on the block matching result. It achieves the technical effect of determining the positioning segment of its industrial chain by analyzing the industry field characteristics of the enterprise, analyzing based on the positioning of the industrial chain and the customer portrait group, and performing targeted digital block matching on the enterprise information according to the analyzed data, so that the enterprise can achieve digital transformation on the basis of meeting the requirements of the customer group for the industrial chain positioning. Thus, it solves the technical problem in the prior art that there is a lack of positioning analysis of the customer group in digital transformation, resulting in blind transformation and poor transformation effects.

[0113] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a device, or a computer program product. Therefore, the present application can adopt the form of a completely software embodiment, a completely hardware embodiment, or an embodiment combining software and hardware aspects. In addition, the present application is in the form of a computer program product that can be implemented on one or more computer-usable storage media containing computer-usable program code. The computer-usable storage media includes, but is not limited to: USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disk memories, compact disc read-only memories (CD-ROMs), optical memories, and other media that can store program code.

[0114] The present invention is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products of the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for implementing in the process Figure 1 one process or multiple processes and / or blocks Figure 1A system for the functions specified in one or more boxes.

[0115] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory produce a manufacture including an instruction system that implements the functions specified in one Figure 1 one process or more processes and / or boxes Figure 1 one box or more boxes.

[0116] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are performed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one Figure 1 one process or more processes and / or boxes Figure 1 one box or more boxes. Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications to these embodiments once they learn the basic creative concepts.

[0117] Obviously, those skilled in the art can make various changes and variations to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the same technology of the present invention, the present invention also intends to include these modifications and variations.

Claims

1. A method for analyzing industrial chain data of enterprise positioning, characterized in that, The method includes: Obtaining enterprise basic information, where the enterprise basic information includes industry field information; Performing industry feature extraction according to the industry field information to obtain industry feature information; Determining enterprise feature information according to the enterprise basic information; Performing enterprise positioning analysis based on the industry feature information and the enterprise feature information to determine the enterprise industrial chain positioning segment; Obtaining a customer group portrait according to the industry feature information and the enterprise industrial chain positioning segment; Determining an enterprise transformation project according to the enterprise basic information, and performing targeted digital block matching for the enterprise transformation project and the customer group portrait to obtain a block matching result; Determining enterprise transformation information based on the block matching result; Among them, the obtaining of the customer group portrait according to the industry feature information and the enterprise industrial chain positioning segment includes: Obtaining positioning segment customer features according to the enterprise industrial chain positioning segment; Obtaining an industry customer group according to the industry feature information; Inputting the positioning segment customer features and the industry customer group into a customer portrait matching model to obtain the output result of the customer portrait matching model, where the output result includes a customer group portrait; Among them, the determining of the enterprise transformation project according to the enterprise basic information, and performing targeted digital block matching for the enterprise transformation project and the customer group portrait to obtain a block matching result includes: Obtaining group demand features according to the customer group portrait; Obtaining transformation matching technology information according to the enterprise transformation project; Performing matching feature analysis according to the enterprise transformation project and the transformation matching technology information to determine project transformation technology features; Performing matching based on the group demand features and the project transformation technology features to obtain a matching degree; Judging whether the matching degree meets a predetermined requirement; When it is satisfied, determining the transformation matching technology information and the project transformation technology features; Among them, after judging whether the matching degree meets the predetermined requirement, it includes: When the matching degree does not meet the predetermined requirement, obtaining a feature deviation value according to the group demand features and the project transformation technology features; Obtaining deviation support technology according to the feature deviation value; Obtaining a technology fusion evaluation result according to the deviation support technology and the transformation matching technology information; When the technology fusion evaluation result meets the fusion requirement, obtaining a fusion reminder information.

2. The method according to claim 1, characterized in that The performing of industry feature extraction according to the industry field information to obtain industry feature information includes: Determining domain attribute features according to the industry field information; Obtaining an industry industrial chain division standard based on the domain attribute features, and extracting division standard features based on the industry industrial chain division standard; Performing industry feature integration according to the domain attribute features and the division standard features to obtain the industry feature information.

3. The method according to claim 2, wherein The performing of enterprise positioning analysis based on the industry feature information and the enterprise feature information to determine the enterprise industrial chain positioning segment includes: Performing industrial chain feature division on the industry feature information according to the industry industrial chain division standard; Constructing an industrial chain feature list based on the industry feature information divided according to the industrial chain; Perform feature matching in the industrial chain feature list according to the enterprise feature information to obtain a feature matching result; Based on the feature matching result, perform weight analysis to determine the enterprise's industrial chain positioning segment.

4. The method according to claim 3, wherein Based on the feature matching result, perform weight analysis to determine the enterprise's industrial chain positioning segment, including: According to the feature matching result, obtain a matching feature set; Perform a decentralization process on the matching feature set to obtain a de-centered feature set; Based on the de-centered feature set, obtain a covariance matrix; Perform operations on the covariance matrix to obtain the first eigenvector of the covariance matrix; Project the matching feature set onto the first eigenvector to obtain a dimensionality-reduced feature set; Based on the dimensionality-reduced feature set, obtain the variance contribution rate of the dimensionality-reduced feature set; According to the variance contribution rate, perform normalization processing on the index weights to obtain feature weight values, and based on the feature weight values, perform operations on the matching feature set to determine the screened feature information; Based on the screened feature information, perform a comparison in the industrial chain feature list to determine the enterprise's industrial chain positioning segment.

5. An industrial chain data analysis system for enterprise positioning, characterized in that, For executing the method according to any one of claims 1 to 4, the system includes: A first obtaining unit, which is used to obtain enterprise basic information, and the enterprise basic information includes industry field information; A second obtaining unit, which is used to extract industry features according to the industry field information to obtain industry feature information; A first determining unit, which is used to determine enterprise feature information according to the enterprise basic information; A second determining unit, which is used to perform enterprise positioning analysis based on the industry feature information and the enterprise feature information to determine the enterprise's industrial chain positioning segment; A third obtaining unit, which is used to obtain a customer group portrait according to the industry feature information and the enterprise's industrial chain positioning segment; A fourth obtaining unit, which is used to determine an enterprise transformation project according to the enterprise basic information, and perform targeted digital block matching on the enterprise transformation project and the customer group portrait to obtain a block matching result; A third determining unit, which is used to determine enterprise transformation information based on the block matching result.

6. An industrial chain data analysis system for enterprise positioning, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, the steps of the method according to any one of claims 1-4 are implemented.

7. A computer-readable storage medium, characterized in that, A computer program is stored on the storage medium, and when the computer program is executed by the processor, the method according to any one of claims 1-4 is implemented.

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