Configuration data analysis method and device, computer equipment and storage medium

Abstract

The invention relates to the field of data processing and financial science and technology, and discloses a configuration data analysis method and device, computer equipment and a medium, and the method comprises the steps: carrying out the business component analysis of a business configuration text, and obtaining a business component set; performing component dependency analysis on the service configuration text by using the service component set to obtain a service component structure; extracting business keywords from the data analysis scheme, and performing database retrieval on the business keywords to obtain a business data set; performing performance function matching on the data analysis scheme to obtain a service performance function; performing data analysis on the service data set according to the service performance function and the service component structure to obtain analysis service data; and performing data format conversion on the analysis service data to obtain a data analysis result. And the flexibility and efficiency of data analysis are improved.

Description

Technical Field

[0001] The present invention relates to the fields of data processing and financial technology, and in particular to a configurable data analysis method, device, computer equipment and storage medium. Background Art

[0002] Data analysis plays a very important role in practical work. In the field of financial services, data analysis can help formulate investment strategies and risk management models. By conducting customer risk assessment and anti-fraud analysis, it can improve the efficiency and security of financial services. In marketing, through data analysis, companies can better understand customer needs, market trends and competitor situations, thereby specifying effective marketing strategies, optimizing advertising push, and conducting customer segmentation and personalized marketing.

[0003] Data analysis methods are complex and diverse. In actual use, different data analysis solutions often need to be designed for different system structures and business needs. In addition, the data analysis solutions for each project are not universal, which often leads to a large amount of resources being spent on solution configuration when performing data analysis, making data analysis less flexible and, in turn, less efficient. Summary of the invention

[0004] The present invention provides an artificial intelligence configurable data analysis method, device, computer equipment and storage medium to solve the technical problem that a large amount of resources are needed to configure solutions during data analysis, resulting in poor flexibility of data analysis and subsequently low efficiency of data analysis.

[0005] In a first aspect, a configuration data analysis method is provided, comprising:

[0006] Performing business component analysis on the pre-acquired business configuration text to obtain a business component set;

[0007] Using the business component set to perform component dependency analysis on the business configuration text to obtain a business component structure;

[0008] Extracting business keywords from the pre-acquired data analysis solution, and performing a database search on the business keywords to obtain a business data set;

[0009] Performing function matching on the data analysis scheme to obtain a business function;

[0010] Performing data analysis on the business data set according to the business function and the business component structure to obtain analyzed business data;

[0011] The analysis business data is converted into a data format to obtain a data analysis result.

[0012] In a second aspect, a configurable data analysis device is provided, comprising:

[0013] A business analysis module is used to perform business component analysis on the pre-acquired business configuration text to obtain a business component set;

[0014] A dependency analysis module, used to perform component dependency analysis on the business configuration text using the business component set to obtain a business component structure;

[0015] A database search module is used to extract business keywords from the pre-acquired data analysis solution and perform a database search on the business keywords to obtain a business data set;

[0016] A function matching module, used to match the function of the data analysis scheme to obtain a business function;

[0017] A data analysis module, used to perform data analysis on the business data set according to the business function and the business component structure to obtain analyzed business data;

[0018] The format conversion module is used to convert the data format of the analysis business data to obtain data analysis results.

[0019] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned configurable data analysis method when executing the computer program.

[0020] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned configurable data analysis method is implemented.

[0021] In the scheme implemented by the above-mentioned configurable data analysis method, device, computer equipment and storage medium, communication can be carried out with the server through the client's network. The server can receive the business configuration text and the data analysis scheme through the client, and perform business structure analysis on the business configuration text to obtain the business component structure; extract business keywords from the data analysis scheme, and perform function function matching on the data analysis scheme to obtain the business function function; perform database retrieval on the business keywords to obtain the business data set; use the analysis function function to map the business component structure to obtain the business function model; use the business function model to perform data analysis on the business data set to obtain the analyzed business data; perform data format conversion on the analyzed business data to obtain the data analysis result, and feed the data analysis result back to the client. In the present invention, for data analysis in different business scenarios, for complex insurance entities such as insurance business, the business component analysis method can be used to first extract word features from the configuration text word set to obtain the configuration text word feature set; then perform business component matching and text mapping on the configuration text word feature set to obtain the business component set, and automatically match the corresponding function function and the required data set, thereby improving the flexibility of analysis and then improving the efficiency of data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0023] Figure 1 is a schematic diagram of an application environment of a configurable data analysis method in one embodiment of the present invention;

[0024] Figure 2 is a flow chart of a configuration data analysis method in one embodiment of the present invention;

[0025] Figure 3 yes Figure 1 A schematic flow chart of a specific implementation of step S10;

[0026] Figure 4 yes Figure 1 A schematic flow chart of a specific implementation of step S20;

[0027] Figure 5 yes Figure 4 A schematic flow chart of a specific implementation of step S30;

[0028] Figure 6is a structural diagram of a configurable data analysis device in one embodiment of the present invention;

[0029] Figure 7 is a schematic diagram of a structure of a computer device in one embodiment of the present invention;

[0030] Figure 8 It is another structural schematic diagram of a computer device in one embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] The configuration data analysis method provided by the embodiment of the present invention can be applied in the following aspects: Figure 1 In the application environment, the client communicates with the server through the network. The server can receive the business configuration text and the data analysis scheme through the client, and perform business structure analysis on the business configuration text to obtain the business component structure; extract business keywords from the data analysis scheme, and perform function matching on the data analysis scheme to obtain the business function function; perform database retrieval on the business keywords to obtain the business data set; use the analysis function function to perform function mapping on the business component structure to obtain the business function model; use the business function model to perform data analysis on the business data set to obtain the analysis business data; perform data format conversion on the analysis business data to obtain the data analysis result, and feed the data analysis result back to the client. In the present invention, for data analysis under different business scenarios, for complex insurance entities such as insurance business, the business component analysis method can be used to first extract word features from the configuration text word set to obtain the configuration text word feature set; then perform business component matching and text mapping on the configuration text word feature set to obtain the business component set, and automatically match the corresponding function function and the required data set, thereby improving the flexibility of analysis and then improving the efficiency of data analysis. Among them, the client can be, but is not limited to, various personal computers, laptops, smart phones, tablet computers and portable wearable devices. The server side can be implemented by an independent server or a server cluster composed of multiple servers. The present invention is described in detail below through specific embodiments.

[0033] See also Figure 2 As shown, Figure 2 A flow chart of a configuration data analysis method provided by an embodiment of the present invention includes the following steps:

[0034] S10: Perform business component analysis on the pre-acquired business configuration text to obtain a business component set.

[0035] In detail, the business configuration text is a text of relevant organizational structure requirements obtained by structural analysis and brainstorming by a corresponding group of business personnel for a preset business scenario, and each business component in the business component set is a hierarchical component that realizes independent functions in the business scenario.

[0036] In the embodiment of the present invention, refer to Figure 3 As shown, the business component analysis is performed on the pre-acquired business configuration text to obtain a business component set, including:

[0037] S11, filtering out irrelevant words from the pre-acquired business configuration text to obtain a cleaned configuration text;

[0038] S12, performing text segmentation on the cleaning configuration text to obtain a configuration text word set;

[0039] S13, extracting word features from the configuration text word set to obtain a configuration text word feature set;

[0040] S14, performing business component matching on the configuration text word feature set to obtain a business component word feature set;

[0041] S15. Perform text mapping on the business component word feature set to obtain a business component set.

[0042] Specifically, the irrelevant word screening refers to screening out special symbols and irrelevant words such as stop words in the business configuration text. The irrelevant word screening operation can be performed by a regular expression matching method, and the text segmentation operation can be performed using a two-way maximum matching or byte pair encoding (Byte Pair Encoding, abbreviated as BPE) method. The text segmentation operation refers to splitting the text into a set of words, wherein the Sohu Byte Pair Encoding is based on the characters or sub-word pairs with the highest merging frequency, and gradually combines them into larger units, thereby reducing different word forms, and finally creating a vocabulary containing commonly used sub-words or character fragments.

[0043] In detail, the word feature extraction refers to extracting the semantic features of each configuration text word in the configuration text word set. The word feature extraction can be performed using the Word2Vec method, wherein Word2Vec is a model that converts words into vector representations to capture the semantic relationship between words. The Word2Vec maps words to a continuous vector space so that words with similar semantics are closer in the vector space.

[0044] Specifically, the business component matching refers to using a pre-similarity algorithm or an algorithm such as a Euclidean distance to match word features similar to each configuration text word feature in the configuration text word feature set from a preset business component word feature library as business component word features and compile them into a business component word feature set. The text mapping refers to mapping each business component word feature in the business component word feature set into a corresponding word text.

[0045] In the embodiment of the present invention, by performing business component analysis on the pre-acquired business configuration text, the information of each business component in the business scenario can be directly extracted, which enhances the flexibility of data analysis of the business scenario, reduces the steps of personnel entering business components, and improves the efficiency of data analysis.

[0046] S20: Use the business component set to perform component dependency analysis on the business configuration text to obtain a business component structure.

[0047] In detail, the business component structure includes a set of business components required by the business scenario and dependencies between the business components.

[0048] In the embodiment of the present invention, refer to Figure 4 As shown, the business component set is used to perform component dependency analysis on the business configuration text to obtain a business component structure, including:

[0049] S21, extracting a configuration text word feature set from the business configuration text;

[0050] S22, performing self-attention encoding on the configuration text word feature set to obtain an attention text feature;

[0051] S23, using the business component set to perform component annotation on the attention text feature to obtain annotated text features;

[0052] S24, performing feedforward activation and residual connection on the annotated text features to obtain component dependency relationships;

[0053] S25. Generate a business component structure according to the component dependency and the business component set.

[0054] Specifically, the method of extracting a configuration text word feature set from the business configuration text is consistent with the method described in the above step S10, which includes screening out irrelevant words from the pre-acquired business configuration text to obtain a cleaned configuration text; performing text segmentation on the cleaned configuration text to obtain a configuration text word set; and performing word feature extraction on the configuration text word set to obtain a configuration text word feature set, and will not be repeated here.

[0055] In detail, self-attention encoding can be performed using a self-attention mechanism or a multi-head attention method. The feedforward activation refers to activation using the ReLU activation function of the feedforward layer of a neural network with an attention mechanism such as Transformer. The residual connection refers to residual connection using the residual layer of Transformer, and feature activation operation is performed using a normalization layer. The self-attention mechanism is a technology that enables a model to focus on different positions in a sequence and calculate the dependencies between them when processing sequence data. The self-attention mechanism is widely used in natural language processing models, especially Transformer models, which solves the challenge that traditional sequence models are difficult to capture long-distance dependencies.

[0056] Specifically, the component labeling refers to labeling each token in the attention text feature with a component through named entity recognition or other specific task mechanisms, so as to facilitate the subsequent inference of which tokens or text fragments in the attention text feature belong to specific components or modules, and generate component dependencies based on context dependencies.

[0057] In detail, the business component structure is generated according to the component dependency and the business component set. For example, when the business component set is (subsystem, development group, development team, technology center), the dependency is that the development team depends on the technology center, the development group depends on the development team, and the subsystem depends on the development group. The corresponding business component structure is subsystem - development group - development team - technology center.

[0058] In an embodiment of the present invention, by utilizing the business component set to perform component dependency analysis on the business configuration text, the dependency relationship between the various business components in the business configuration text can be captured through the self-attention mechanism combined with contextual information, thereby forming a systematic understanding of the component composition of the business scenario, facilitating the implementation of modular and configurable data analysis.

[0059] S30: extracting business keywords from the pre-acquired data analysis solution, and performing a database search on the business keywords to obtain a business data set.

[0060] In detail, the data analysis plan refers to the type and plan of data analysis required for the business scenario corresponding to the business configuration text. The data analysis plan may be "conducting summary statistics of demand quantity".

[0061] Specifically, the business keyword refers to a keyword related to the business data in the data analysis plan for performing data analysis on the business configuration text. For example, when the data analysis plan is "conducting summary statistics of demand quantity", the business keyword is "demand quantity".

[0062] In the embodiment of the present invention, refer to Figure 5 As shown, the database search is performed on the business keywords to obtain a business data set, including:

[0063] S31, extracting database keywords from a preset business database;

[0064] S32, generating a business query statement according to the database keyword and the business keyword;

[0065] S33, performing a database search on the business database according to the business query statement to obtain a matching data set;

[0066] S34, performing outlier and duplicate value screening operations on the matching data set to obtain a cleaned business data set;

[0067] S35: performing a data standardization operation on the cleaned business data set to obtain a business data set.

[0068] In detail, the business database refers to a database that records all relevant data corresponding to the business scenario, and the database keyword refers to keywords such as the database name or table name of the business database. The business database can be a network database, a relational database, and a tree database.

[0069] Specifically, the business query statement is a query statement used to query the data corresponding to the business keyword in the business database. The business query statement can be generated by combining database query statements such as select from, group by or order by with conditional statements such as where. For example, the business query statement can be "select business keyword from database keyword".

[0070] In detail, the standard score method, interquartile range method, box plot method, score method or median absolute deviation method can be used to screen out abnormal data, and the primary key-based deduplication, fuzzy matching deduplication and hash deduplication method can be used to screen out duplicate values. Among them, the standard score method determines whether it is an outlier by calculating the difference between the data point and the data average. The interquartile range method uses the distribution of the data to determine the outlier by calculating the gap between the upper quartile and the lower quartile of the data. The box plot method is a visualization tool based on the five-number summary of the data, which is used to identify outliers. The box plot displays the median, upper and lower quartiles, and the range represented by the "whiskers". Data points outside the "whiskers" are usually considered to be outliers.

[0071] Specifically, the hash deduplication method is a duplicate data screening method based on hash functions, which is used to quickly detect and delete duplicate records in a data set. That is, each data in the matching data set can be hashed using hash functions such as MD5 and SHA-256 to obtain a hash value set, and then compare whether the hash value set is repeated.

[0072] In detail, data standardization operations can be performed using standardization methods such as Min-Max normalization, Z-Score standardization, maximum absolute value scaling, and Robust standardization. Among them, Min-Max normalization is used to scale the data to a specific range, and the range is usually [0,1]; Z-Score standardization is used to convert the data into a standard normal distribution with a mean of 0 and a standard deviation of 1; Maximum absolute value scaling is used to scale the data to the range of [-1,1], and the positivity of the data needs to be kept unchanged; Robust standardization is used to scale based on the median and interquartile range of the data to reduce the impact of outliers on standardization.

[0073] In the embodiment of the present invention, by extracting business keywords and performing database retrieval on the business keywords to obtain a business data set, the business data that needs to be analyzed corresponding to the business configuration text can be automatically retrieved, thereby improving the efficiency of data analysis.

[0074] S40: Perform function matching on the data analysis scheme to obtain a business function.

[0075] In detail, the business function function refers to a logical calculation function used to perform data analysis on each business data corresponding to the business data set. The business function function can be a weighted sum, a statistical maximum, a variance calculation, and a standard deviation calculation function.

[0076] In an embodiment of the present invention, the function function matching of the data analysis scheme to obtain the business function function includes: extracting operation keywords from the data analysis scheme to obtain business function keywords; performing context analysis on the data analysis scheme according to the business function keywords to obtain a business analysis object; performing function mapping on the business function keywords to obtain a mapping function function; and labeling the mapping function function using the business analysis object to obtain a business function function.

[0077] In detail, the regular expression matching method can be used to match operation keywords, where the operation keywords are keywords related to function operations of data analysis, such as "sum", "modulus" and "average value", etc. The business function keywords can be "linear regression analysis", "calculate average value" or "calculate variance".

[0078] Specifically, the context analysis refers to extracting data analysis objects corresponding to the business function keywords from the data analysis plan. The context analysis can be performed using a bag of words model (BOW), dependency syntax analysis, and other pre-trained language models. The business analysis object refers to an object in the business data set that needs to be analyzed. For example, when the business data set is a business demand data set, the business analysis object may be an internal demand.

[0079] In detail, the bag-of-words model is a text representation method. The bag-of-words model converts text into a vector of fixed length to represent the frequency of occurrence or whether each word in the text appears. The bag-of-words model does not consider the order or grammatical structure of the words, but only counts the number of occurrences of each word in the document; the dependency syntactic analysis is a sentence structure analysis method. The dependency syntactic analysis is used to represent the dependency relationship between words in a sentence, that is, the relationship between words in the syntactic structure. The dependency syntactic analysis regards each word as a node and connects these nodes through dependency relationships to form a dependency tree. The pre-trained language model can be a BERT model, wherein the BERT model is a pre-trained language model based on the Transformer architecture and is a bidirectional contextual learning model. BERT has made significant progress in natural language processing, especially in tasks such as question answering and text classification.

[0080] In detail, the function mapping refers to using a mapping table or mapping relationship between preset keywords and operation functions to map out a mapping function function corresponding to the business function keyword. The mapping function function is, for example: when the business function keyword is "calculate average", the mapping function function can be the NumPy or Pandas function in Python; when the business function keyword is "regression analysis", the mapping function function can be the LinearRegression function in the Scikit-learn library; when the business function keyword is "data filtering", the mapping function function can be the filter function or query function of the Pandas data frame.

[0081] Specifically, the business analysis object is used to mark the mapping function to obtain the business function, which can indicate the object for subsequent data analysis and ensure the accuracy of the data analysis.

[0082] In the embodiment of the present invention, by matching the functional functions of the data analysis scheme to obtain the business functional functions, the functional functions for performing data analysis operations can be automatically matched in a configurable manner, eliminating the step of manually screening the functional functions, thereby improving the efficiency of data analysis.

[0083] S50: Analyze the business data set according to the business function and the business component structure to obtain analyzed business data.

[0084] In detail, the analyzed business data refers to the data results obtained by performing business data analysis on the business data set, and the analyzed business data may be the demand numbers corresponding to each component in the system development architecture.

[0085] In an embodiment of the present invention, the data analysis of the business data set is performed according to the business function function and the business component structure to obtain analyzed business data, including: extracting a business analysis object from the business function function; matching a business component object corresponding to the business analysis object from the business component structure; performing data matching on the business data set using the business component object to obtain a component data set; and performing data analysis on the component data set using the business function to obtain analyzed business data.

[0086] In detail, the business analysis object is consistent with the business analysis object in the above step S40, and the matched business component object is the object of each component structure in the business component structure corresponding to the business analysis object. For example, when the business component structure is subsystem - development group - development team - technology center, the business component object can be "development team requirement number".

[0087] Specifically, using the business component object to perform data matching on the business data set to obtain the component data set means matching the data corresponding to the business component objects one by one from the business data set, and aggregating the matched data into a component data set in the order and structure of the business component objects.

[0088] In detail, the use of the business function function to perform data analysis on the component data set to obtain analyzed business data refers to calling the business function function to perform specific calculations on the component data set. For example, when the business function function is a mean function that calculates the mean and the component data set is "the number of development team requirements", the code for data analysis can be "mean_value = dataset['number of development team requirements'].mean()", wherein mean_value is the analyzed business data, dataset is a data set object containing data, dataset can be structured data in various forms, and mean() is the mean function that calculates the mean.

[0089] In an embodiment of the present invention, by performing data analysis on the business data set according to the business function and the business component structure, analyzed business data is obtained, and the function functions and corresponding data corresponding to the business scenario can be automatically screened according to needs for data analysis, thereby realizing configurable data analysis and improving the efficiency of data analysis on business data.

[0090] S60: Convert the data format of the analyzed business data to obtain data analysis results.

[0091] In detail, the analytical business data currently obtained is relatively primitive and lacks intuitiveness. In order to improve the intuitiveness of the results of data analysis, it is necessary to convert the data format of the analytical business data into data formats such as lists, pie charts, bar charts, and scatter plots to facilitate data understanding.

[0092] Specifically, before converting the data format of the analyzed business data to obtain the data analysis results, the present solution also includes data storage of the analyzed business data, and the data storage may include general storage and personalized storage, wherein the general storage refers to providing a unified and standardized data storage method for all users or systems, and the personalized storage refers to storing data according to the user's personalized needs or specific usage scenarios.

[0093] In detail, the general storage method usually does not take into account the user's personal characteristics or personalized needs, but stores data in a general format or structure, which is suitable for a wide range of application scenarios. The personalized storage takes into account the user's behavior, preferences or specific usage requirements, and provides a personalized data storage method to meet the differentiated needs of different users.

[0094] In an embodiment of the present invention, the data format conversion of the analyzed business data to obtain the data analysis result includes: extracting the data format of the analyzed business data to obtain the analyzed data format; format splitting the analyzed business data according to the analyzed data format to obtain analyzed data values ​​and analyzed data structure; and using the analyzed data structure to convert the data format of the analyzed data values ​​to obtain the data analysis result.

[0095] In detail, the data format extraction refers to extracting the data structure format corresponding to the analysis business data. The data can be loaded using Pandas DataFrame or other data structure forms to achieve data format extraction. The analysis data format includes a list format and a graphical format.

[0096] Specifically, the format splitting refers to splitting the analysis business data into values ​​and data structures corresponding to the analysis data format. For example, when the analysis data format is a list format, the corresponding analysis data values ​​refer to the values ​​of each data in the analysis business data, and the analysis data structure is in a list format. When the analysis data format is a graphical format, the corresponding analysis data values ​​refer to the values ​​of each data in the analysis business data, and the corresponding analysis data structure is a classification label structure.

[0097] In detail, the numerical value may be sales volume, percentage, etc., the classification label structure may be a label such as a country or product, the data format of a list may be converted using a print algorithm, and the data format of a graph may be converted using components such as Matplotlib or Seaborn.

[0098] In the embodiment of the present invention, by converting the data format of the analyzed business data to obtain data analysis results, the data can be efficiently converted into different types of charts and formats, thereby better performing data analysis and presentation.

[0099] It can be seen that in the above scheme, by performing business component analysis on the pre-acquired business configuration text, the information of each business component in the business scenario can be directly extracted, which enhances the flexibility of data analysis of the business scenario, reduces the steps for personnel to enter business components, and improves the efficiency of data analysis; by using the business component set to perform component dependency analysis on the business configuration text, the dependency relationship between each business component in the business configuration text can be captured through the self-attention mechanism combined with context information, thereby forming a systematic understanding of the component structure of the business scenario, and facilitating the realization of modular and configurable data analysis; by extracting business keywords and performing database retrieval on the business keywords to obtain a business data set, the business data that needs to be analyzed corresponding to the business configuration text can be automatically retrieved, thereby improving the efficiency of data analysis.

[0100] By matching the functional functions of the data analysis scheme to obtain the business functional functions, the functional functions for data analysis operations can be automatically matched in a configurable manner, eliminating the step of manually screening the functional functions, thereby improving the efficiency of data analysis; by performing data analysis on the business data set according to the business functional functions and the business component structure to obtain analyzed business data, the functional functions and corresponding data corresponding to the business scenarios can be automatically screened according to needs for data analysis, thus realizing configurable data analysis and improving the efficiency of data analysis on business data.

[0101] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0102] In one embodiment, a configuration data analysis device is provided, which corresponds one-to-one to the configuration data analysis method in the above embodiment. Figure 6 As shown, the configurable data analysis device includes a business analysis module 101, a dependency analysis module 102, a database search module 103, a function matching module 104, a data analysis module 105 and a format conversion module 106. The functional modules are described in detail as follows:

[0103] The business analysis module 101 is used to perform business component analysis on the pre-acquired business configuration text to obtain a business component set;

[0104] A dependency analysis module 102, configured to perform component dependency analysis on the business configuration text using the business component set to obtain a business component structure;

[0105] A database search module 103 is used to extract business keywords from the pre-acquired data analysis solution and perform a database search on the business keywords to obtain a business data set;

[0106] A function matching module 104 is used to match the data analysis scheme with a function to obtain a business function;

[0107] A data analysis module 105, configured to perform data analysis on the business data set according to the business function and the business component structure to obtain analyzed business data;

[0108] The format conversion module 106 is used to convert the data format of the analyzed business data to obtain data analysis results.

[0109] In one embodiment, when the business analysis module 101 performs business component analysis on the pre-acquired business configuration text to obtain a business component set, it is used to:

[0110] Remove irrelevant words from the pre-acquired business configuration text to obtain a cleaned configuration text;

[0111] Performing text segmentation on the cleaning configuration text to obtain a configuration text word set;

[0112] Performing word feature extraction on the configuration text word set to obtain a configuration text word feature set;

[0113] Performing business component matching on the configuration text word feature set to obtain a business component word feature set;

[0114] Text mapping is performed on the business component word feature set to obtain a business component set.

[0115] In one embodiment, when the dependency analysis module 102 performs component dependency analysis on the business configuration text using the business component set to obtain the business component structure, it is used to:

[0116] Extracting a configuration text word feature set from the business configuration text;

[0117] Performing self-attention encoding on the configuration text word feature set to obtain an attention text feature;

[0118] Using the business component set to perform component annotation on the attention text feature to obtain annotated text features;

[0119] Performing feed-forward activation and residual connection on the annotated text features to obtain component dependency;

[0120] A business component structure is generated according to the component dependency relationship and the business component set.

[0121] In one embodiment, when performing a database search on the business keyword to obtain a business data set, the database search module 103 is used to:

[0122] Extract database keywords from a preset business database;

[0123] Generate a business query statement according to the database keywords and the business keywords;

[0124] Performing a database search on the business database according to the business query statement to obtain a matching data set;

[0125] Performing outlier and duplicate value screening operations on the matching data set to obtain a cleaned business data set;

[0126] A data standardization operation is performed on the cleaned business data set to obtain a business data set.

[0127] In one embodiment, when the function matching module 104 performs function function matching on the data analysis scheme to obtain the business function function, it is used to:

[0128] Extracting operation keywords from the data analysis scheme to obtain business function keywords;

[0129] Performing context analysis on the data analysis scheme according to the business function keywords to obtain a business analysis object;

[0130] Performing function mapping on the business function keywords to obtain a mapping function;

[0131] The mapping function is annotated using the business analysis object to obtain a business function.

[0132] In one embodiment, when the data analysis module 105 performs data analysis on the business data set according to the business function and the business component structure to obtain analyzed business data, it is used to:

[0133] Extracting a business analysis object from the business function;

[0134] Matching a business component object corresponding to the business analysis object from the business component structure;

[0135] Using the business component object to perform data matching on the business data set to obtain a component data set;

[0136] The business function is used to perform data analysis on the component data set to obtain analyzed business data.

[0137] In one embodiment, when the format conversion module 106 performs data format conversion on the analysis business data to obtain the data analysis result, it is used to:

[0138] Extracting the data format of the analysis business data to obtain an analysis data format;

[0139] Decomposing the analysis business data in a format according to the analysis data format to obtain analysis data values ​​and analysis data structure;

[0140] The analysis data structure is used to perform data format conversion on the analysis data value to obtain a data analysis result.

[0141] The present invention provides a configurable data analysis device, which first performs business component analysis on a pre-acquired business configuration text, and can directly extract information of each business component in a business scenario, thereby enhancing the flexibility of data analysis of the business scenario, reducing the steps of personnel entering business components, and improving the efficiency of data analysis; by using the business component set to perform component dependency analysis on the business configuration text, it is possible to capture the dependency relationship between each business component in the business configuration text through a self-attention mechanism combined with context information, thereby forming a systematic cognition of the component structure of the business scenario, and facilitating modular and configurable data analysis; by extracting business keywords and performing database retrieval on the business keywords to obtain a business data set, it is possible to automatically retrieve the business data that needs to be analyzed corresponding to the business configuration text, thereby improving the efficiency of data analysis.

[0142] By matching the functional functions of the data analysis scheme to obtain the business functional functions, the functional functions for data analysis operations can be automatically matched in a configurable manner, eliminating the step of manually screening the functional functions, thereby improving the efficiency of data analysis; by performing data analysis on the business data set according to the business functional functions and the business component structure to obtain analyzed business data, the functional functions and corresponding data corresponding to the business scenarios can be automatically screened according to needs for data analysis, thus realizing configurable data analysis and improving the efficiency of data analysis on business data.

[0143] For the specific limitations of the configurable data analysis device, please refer to the limitations of the intelligent question and answer method above, which will not be repeated here. Each module in the above-mentioned configurable data analysis device can be implemented in whole or in part through software, hardware and a combination thereof. The above-mentioned modules can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above modules.

[0144] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory, a network interface and a database connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client via a network connection. When the computer program is executed by the processor, it implements a function or step on the server side of a configurable data analysis method.

[0145] In one embodiment, a computer device is provided. The computer device may be a client, and its internal structure diagram may be as follows: Figure 8 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server through a network connection. When the computer program is executed by the processor, it implements the functions or steps of the client side of a configurable data analysis method

[0146] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0147] Performing business component analysis on the pre-acquired business configuration text to obtain a business component set;

[0148] Using the business component set to perform component dependency analysis on the business configuration text to obtain a business component structure;

[0149] Extracting business keywords from the pre-acquired data analysis solution, and performing a database search on the business keywords to obtain a business data set;

[0150] Performing function matching on the data analysis scheme to obtain a business function;

[0151] Performing data analysis on the business data set according to the business function and the business component structure to obtain analyzed business data;

[0152] The analysis business data is converted into a data format to obtain a data analysis result.

[0153] In one embodiment, a computer readable storage medium is provided, on which a computer program is stored, and when the computer program is executed by a processor, the following steps are implemented:

[0154] Performing business component analysis on the pre-acquired business configuration text to obtain a business component set;

[0155] Using the business component set to perform component dependency analysis on the business configuration text to obtain a business component structure;

[0156] Extracting business keywords from the pre-acquired data analysis solution, and performing a database search on the business keywords to obtain a business data set;

[0157] Performing function matching on the data analysis scheme to obtain a business function;

[0158] Performing data analysis on the business data set according to the business function and the business component structure to obtain analyzed business data;

[0159] The analysis business data is converted into a data format to obtain a data analysis result.

[0160] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can refer to the relevant descriptions on the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0161] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0162] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0163] The above-described embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some of the technical features therein by equivalents; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention, and should be included in the protection scope of the present invention. It should be noted that if software tools or components other than those of the company appear in the embodiments of this application, they are only used for example introduction and do not represent actual use.

Claims

1. A configuration data analysis method, characterized in that: include: Performing business component analysis on the pre-acquired business configuration text to obtain a business component set; Using the business component set to perform component dependency analysis on the business configuration text to obtain a business component structure; Extracting business keywords from the pre-acquired data analysis solution, and performing a database search on the business keywords to obtain a business data set; Performing function matching on the data analysis scheme to obtain a business function; Performing data analysis on the business data set according to the business function and the business component structure to obtain analyzed business data; The analysis business data is converted into a data format to obtain a data analysis result.

2. The configuration data analysis method according to claim 1, characterized in that: The business component analysis is performed on the pre-acquired business configuration text to obtain a business component set, including: Remove irrelevant words from the pre-acquired business configuration text to obtain a cleaned configuration text; Performing text segmentation on the cleaning configuration text to obtain a configuration text word set; Performing word feature extraction on the configuration text word set to obtain a configuration text word feature set; Performing business component matching on the configuration text word feature set to obtain a business component word feature set; Text mapping is performed on the business component word feature set to obtain a business component set.

3. The configuration data analysis method according to claim 1, characterized in that: The using the business component set to perform component dependency analysis on the business configuration text to obtain a business component structure includes: Extracting a configuration text word feature set from the business configuration text; Performing self-attention encoding on the configuration text word feature set to obtain an attention text feature; Using the business component set to perform component annotation on the attention text feature to obtain annotated text features; Performing feed-forward activation and residual connection on the annotated text features to obtain component dependency; A business component structure is generated according to the component dependency relationship and the business component set.

4. The configuration data analysis method according to claim 1, characterized in that: The database search is performed on the business keywords to obtain a business data set, including: Extract database keywords from a preset business database; Generate a business query statement according to the database keywords and the business keywords; Performing a database search on the business database according to the business query statement to obtain a matching data set; Performing outlier and duplicate value screening operations on the matching data set to obtain a cleaned business data set; A data standardization operation is performed on the cleaned business data set to obtain a business data set.

5. The configuration data analysis method according to claim 1, characterized in that: The performing function matching on the data analysis scheme to obtain a business function includes: Extracting operation keywords from the data analysis scheme to obtain business function keywords; Performing context analysis on the data analysis scheme according to the business function keywords to obtain a business analysis object; Performing function mapping on the business function keywords to obtain a mapping function; The mapping function is annotated using the business analysis object to obtain a business function.

6. The configuration data analysis method according to claim 1, characterized in that: The performing data analysis on the business data set according to the business function and the business component structure to obtain analyzed business data includes: Extracting a business analysis object from the business function; Matching a business component object corresponding to the business analysis object from the business component structure; Using the business component object to perform data matching on the business data set to obtain a component data set; The business function is used to perform data analysis on the component data set to obtain analyzed business data.

7. The configuration data analysis method according to claim 1, characterized in that: The data format conversion of the analyzed business data to obtain the data analysis results includes: Extracting the data format of the analysis business data to obtain an analysis data format; Decomposing the analysis business data in a format according to the analysis data format to obtain analysis data values ​​and analysis data structure; The analysis data structure is used to perform data format conversion on the analysis data value to obtain a data analysis result.

8. A configurable data analysis device, characterized in that: include: A business analysis module is used to perform business component analysis on the pre-acquired business configuration text to obtain a business component set; A dependency analysis module, used to perform component dependency analysis on the business configuration text using the business component set to obtain a business component structure; A database search module is used to extract business keywords from the pre-acquired data analysis solution and perform a database search on the business keywords to obtain a business data set; A function matching module, used to match the function of the data analysis scheme to obtain a business function; A data analysis module, used to perform data analysis on the business data set according to the business function and the business component structure to obtain analyzed business data; The format conversion module is used to convert the data format of the analysis business data to obtain data analysis results.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the configurable data analysis method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the configurable data analysis method according to any one of claims 1 to 7 is implemented.

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