Data visualization configuration method and device, equipment and medium

Abstract

The invention relates to a data processing technology, can be applied to business system platforms of financial science and technology, medical health and the like, and discloses a data visualization configuration method, device and equipment and a storage medium, the method comprises the following steps: carrying out word segmentation on a preset target text to obtain a word segmentation text; performing keyword extraction on the word segmentation text according to a preset part-of-speech rule to obtain a target keyword; performing fuzzy query in a preset database according to the target keyword to obtain a query field; performing data query in the database according to the query field to obtain target data; and displaying the target data returned by the database on a visual interface. According to the method, the data visualization efficiency and the data query accuracy can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and in particular to a data visualization configuration method, device, equipment and medium. Background Art

[0002] Configuring a visualization interface is often a very important issue in the data processing process. Visualization configuration usually involves adding cards to the interface, pulling down the cards to select the information to be displayed, generating visualization graphic cards, and repeating the operation until a complete visualization interface is generated. However, this method is highly complex, labor-intensive, and prone to errors.

[0003] Existing technologies for configuring visualization interfaces mostly involve adding function cards, pulling down the cards to select the information the user wants to display, and repeating this process until a complete visualization interface is generated. However, this manual approach is prone to errors in environments with large data volumes or high concurrency, increasing both labor and time costs. Traditional visualization interface configuration relies on the cooperation of both querying users, reviewing the database based on the querying party's needs and providing feedback on the results. This lacks interactivity and makes it difficult to achieve efficient visualization of data between different partners.

[0004] For example, in the fintech business field, during periods of stock market fluctuations, the risk preferences and investment strategies that investors need to query may change significantly. If data query visualization cannot be queried in a timely manner, financial service providers may not be able to provide investment data or financial products that meet user needs in a timely manner, and cannot provide targeted customer advice, which will affect financial and economic development and investors' investment decisions.

[0005] For example, in the field of healthcare, although data query visualization display technology can improve decision-making efficiency, it also has obvious shortcomings. On the one hand, the sources of medical data are diverse and the standards are not unified, which makes data integration difficult and key information may be missed during visualization. On the other hand, medical data involves sensitive patient information. If protection measures are insufficient during the visualization process, it is easy to cause the risk of privacy leakage.

[0006] Therefore, how to improve the efficiency of data visualization and the accuracy of data query has become an urgent problem to be solved. Summary of the Invention

[0007] The present invention provides a data visualization configuration method, device, equipment and medium, the main purpose of which is to solve the problems of low data visualization efficiency and low data query accuracy.

[0008] In a first aspect, to achieve the above-mentioned objectives, the present invention provides a data visualization configuration method, comprising:

[0009] Segment the preset target text to obtain segmented text;

[0010] Extract keywords from the segmented text according to preset part-of-speech rules to obtain target keywords;

[0011] Perform a fuzzy query in a preset database based on the target keyword to obtain a query field;

[0012] Performing data query in the database according to the query field to obtain target data;

[0013] The target data returned by the database is displayed on a visual interface.

[0014] In a second aspect, the present invention further provides a data visualization configuration device, the device comprising:

[0015] The word segmentation module is used to segment the preset target text to obtain the segmented text;

[0016] A keyword extraction module is used to extract keywords from the segmented text according to preset part-of-speech rules to obtain target keywords;

[0017] A fuzzy query module, configured to perform a fuzzy query in a preset database based on the target keyword to obtain a query field;

[0018] A data query module, configured to perform data query in the database according to the query field to obtain target data;

[0019] A visualization display module is used to display the target data returned by the database on a visualization interface.

[0020] In a third aspect, the present invention further provides an electronic device, comprising:

[0021] at least one processor; and,

[0022] a memory communicatively connected to the at least one processor; wherein,

[0023] The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor to enable the at least one processor to perform the data visualization configuration method described above.

[0024] In a fourth aspect, the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores at least one computer program, and the at least one computer program is executed by a processor in an electronic device to implement the above-mentioned data visualization configuration method.

[0025] The present invention segments the target text based on predefined dictionaries and rules, improves the accuracy of word segmentation recognition and the efficiency of word segmentation, eliminates ambiguous phenomena encountered in word processing, and provides strong support for subsequent text processing; the segmented text is tagged with parts of speech according to preset part-of-speech rules, and is screened according to the part-of-speech rules, which can exclude words that are irrelevant or have low relevance to the text topic, thereby improving the accuracy of keyword extraction and enhancing the robustness of text analysis; fuzzy queries are performed in a preset database using target keywords, allowing searches to be performed using partial keywords or keyword variants, thereby improving the flexibility of queries and enhancing the fault tolerance of queries; through configurable query files, query logic can be easily modified or extended without modifying the code, which greatly reduces maintenance costs, makes the query process more flexible and scalable, and enhances the accuracy of queries; by parsing the target data and binding it to preset chart configuration items, a visual chart can be quickly generated, avoiding the tedious process of manually drawing charts and configuring chart parameters, improving the efficiency of data visualization, and enhancing the readability of data. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0027] Figure 1 This is a schematic diagram of an application environment of a data visualization configuration method according to an embodiment of the present invention;

[0028] Figure 2 A flowchart of a data visualization configuration method provided by one embodiment of the present invention;

[0029] Figure 3 A schematic diagram of a module of a data visualization configuration device provided by one embodiment of the present invention;

[0030] Figure 4 A schematic structural diagram of an electronic device for implementing a data visualization configuration method provided by an embodiment of the present invention;

[0031] Figure 5 This is another structural diagram of an electronic device for implementing a data visualization configuration method provided by an embodiment of the present invention.

[0032] The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, and to fully understand and implement how the present disclosure applies technical means to solve technical problems and achieve the corresponding technical effects, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. The embodiments of the present disclosure and the various features in the embodiments can be combined with each other without conflict, and the technical solutions formed are all within the scope of protection of the present disclosure. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without making creative work should fall within the scope of protection of the present disclosure.

[0034] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, apparatus, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0035] An embodiment of the present application provides a data visualization configuration method, and the execution subject of the data visualization configuration method includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the device provided by the embodiment of the present application. In other words, the data visualization configuration method can be executed by software or hardware installed on a terminal device or a server device. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDNs), and big data and artificial intelligence platforms.

[0036] The embodiment of the present invention provides a data visualization configuration method, which can be applied to Figure 1In the application environment, the client communicates with the server through the network. The server can obtain the target text from the client and segment the target text using predefined dictionaries and rules, improving the accuracy and efficiency of word segmentation, eliminating ambiguity encountered in word processing, and providing strong support for subsequent text processing. The segmented text is tagged with parts of speech according to preset part-of-speech rules and filtered according to the part-of-speech rules to exclude words that are irrelevant or less relevant to the text topic, thereby improving the accuracy of keyword extraction and enhancing the robustness of text analysis. Fuzzy queries are performed within a preset database using target keywords, allowing searches using partial keywords or keyword variants, thereby increasing query flexibility and enhancing query tolerance. Configurable query files allow easy modification or extension of query logic without code modifications, significantly reducing maintenance costs, making the query process more flexible and scalable, and enhancing query accuracy. By parsing the target data and binding it to preset chart configuration items, visual charts can be quickly generated, avoiding the tedious process of manually drawing charts and configuring chart parameters, improving data visualization efficiency, and feeding the final data query results back to the client. The client can be, but is not limited to, various personal computers, laptops, smartphones, tablet computers, and portable wearable devices. The server can be implemented as an independent server or a server cluster consisting of multiple servers. The present invention is described in detail below through specific embodiments.

[0037] Reference Figure 2 FIG. 1 is a flow chart of a data visualization configuration method provided by an embodiment of the present invention. In this embodiment, the data visualization configuration method includes:

[0038] S1. Segment the preset target text to obtain segmented text.

[0039] In an embodiment of the present invention, the target text refers to the query content that the inquirer wants to query. For example, the inquirer can enter "22 years of financial channel electronic technology product sales" in the visual interface to conduct a query; the word segmentation can be a rule-based word segmentation algorithm that relies on pre-defined dictionaries and rules to divide the target text into several meaningful words.

[0040] In the embodiment of the present invention, segmenting the preset target text to obtain the segmented text includes:

[0041] Segmenting the target text into multiple short texts;

[0042] According to the maximum matching length of the short text, forward matching is performed with the short text one character at a time to obtain a segmented text.

[0043] In detail, the target text is preliminarily segmented according to preset segmentation rules. The segmentation rules can be based on factors such as grammar, vocabulary boundaries, punctuation marks, etc. Through the segmentation rules, the target text is segmented into multiple shorter text fragments, namely short texts, which include words, phrases or punctuation marks, etc.

[0044] Furthermore, the maximum matching length of the short text is usually set according to the characteristics of the target text and the word segmentation requirements, which determines the maximum length of the short text considered when attempting to match. The forward reduction of one word at a time refers to the forward maximum matching algorithm, which attempts to match the longest short text that matches the preset dictionary from the starting position of the short text. If the match is successful, the short text is segmented as a word. If the match fails, the length of the short text is reduced word by word until the match is successful or the short text length is 1.

[0045] For example, assuming that the target text is "22 years of sales of electronic technology products through financial channels", the preset segmentation rules may perform preliminary segmentation based on punctuation marks, spaces, etc. The target text has no punctuation marks, spaces, etc., so preliminary segmentation may not be performed or the target text may only be regarded as a whole; assuming that the preset maximum matching length of the short text is 3, and the preset dictionary includes words such as "22 years", "finance", "electronic products", and "sales", start from the beginning of the short text in a forward direction by reducing one word at a time, and try to match the longest string that matches the words in the dictionary. First try "22 years", but this is not in the dictionary, and then try "22 years" again, which is in the dictionary, so "22 years" is segmented as a word, and then continue to try to match from "sales of electronic technology products through financial channels", and finally get the segmented text.

[0046] For example, in a healthcare scenario, assume the target text is "Patient Zhang San, male, 52 years old, has had a persistent fever and cough for a week." The present invention can also use professional medical field word segmentation tools, such as a word segmentation tool trained on medical text based on a deep learning model, to segment the target text. The resulting segmented text is: "Patient / Zhang San / , / male / , / 52 years old / , / has had a persistent fever / and / cough / for / a week / ."

[0047] Specifically, we select specialized word segmentation tools that have been trained with a large amount of medical text data. These tools have better recognition and classification capabilities for medical terms such as "upper respiratory tract infection," "white blood cell count," and "amoxicillin capsules." The tools automatically segment the text based on their internal algorithms and models, and output the word segmentation results, namely the segmented text.

[0048] In the embodiment of the present invention, the rule-based word segmentation algorithm relies on predefined dictionaries and rules to segment the preset target text, improves the accuracy of word segmentation recognition and the efficiency of word segmentation, eliminates the ambiguity encountered in word processing, and provides strong support for subsequent text processing.

[0049] S2. Extract keywords from the segmented text according to preset part-of-speech rules to obtain target keywords.

[0050] In the embodiment of the present invention, the preset part-of-speech rule refers to extracting nouns as keywords, screening out words starting with the part of speech n, i.e. nouns, through a list derivation method, and outputting them as target keywords.

[0051] In the embodiment of the present invention, extracting keywords from the segmented text according to preset part-of-speech rules to obtain target keywords includes:

[0052] Performing part-of-speech tagging on each segmentation word in the segmentation text to obtain a segmentation text containing the part-of-speech tag;

[0053] The segmented text of the noun part of speech is screened out from the segmented text containing the part-of-speech tag and used as the target keyword.

[0054] In detail, part-of-speech tagging is performed on each participle, and part-of-speech tagging is the process of determining the part of speech to which each participle belongs, such as noun, verb, adjective, etc. After obtaining the part-of-speech text containing the part-of-speech tag, the participles with the noun part of speech are screened out. This is because nouns usually represent entities, concepts or things. The screening process can be achieved by traversing each participle and checking its part-of-speech tag. If the part-of-speech tag of the participle is a noun (such as "n", "NN", etc., the specific tag depends on the tag set used), it is retained as a candidate keyword.

[0055] In the embodiment of the present invention, the step of performing part-of-speech tagging on each segmented word in the segmented text to obtain a segmented text containing the part-of-speech tag includes:

[0056] Performing vector conversion on each word in the word segmentation text to obtain a word vector set;

[0057] Obtaining the feature vector corresponding to each word segmentation according to the word vector set;

[0058] Mapping the feature vector to the corresponding part-of-speech tag of each word according to a preset part-of-speech tag model;

[0059] Part-of-speech tagging is performed on the word vector set according to the part-of-speech tag to obtain a word segmentation text containing the part-of-speech tag.

[0060] In detail, the present invention utilizes existing word vector technology such as Word2Vec to convert each word in the word segmentation text into a corresponding word vector, thereby forming a word vector set. After obtaining the word vector set, the convolution layer and pooling layer in deep learning are used to extract the feature vectors of each word segmentation, so as to more finely represent the characteristics of each word segmentation and extract information useful for subsequent part-of-speech tagging. A pre-trained part-of-speech tag model is used to predict the part-of-speech tag for each word segmentation. The part-of-speech tag model can be a model based on machine learning (such as support vector machine, decision tree, etc.) or deep learning (such as neural network), which can accurately map the feature vector to the corresponding part-of-speech tag, combine the predicted part-of-speech tag with the original word vector set, and perform part-of-speech tagging, that is, pair each word with its corresponding part-of-speech tag and mark it in the word segmentation text, thereby generating a word segmentation text containing part-of-speech tags, in which each word segmentation is marked with the corresponding part of speech (such as noun, verb, adjective, etc.).

[0061] Furthermore, the present invention can also add a part-of-speech tag to each participle using a marking tool (such as jieba) with its part-of-speech tagging function. The marking tool provides a rich part-of-speech tagging set, in which each part-of-speech is represented by a specific character or character combination, for example, "n" represents a noun, "v" represents a verb, etc., and the noun participles are filtered out according to the preset filtering conditions (i.e., the part-of-speech is "n" or other relevant tags of noun phrases) and used as target keywords.

[0062] Furthermore, assuming that the part-of-speech tags of nouns include "n" (common noun), "vn" (noun-verb), etc., depending on the part-of-speech tagging system of the word segmentation tool used, the preset part-of-speech tagging function is used to traverse the tuple of each word and its part-of-speech tag. For each tuple, it checks whether the part-of-speech tag exists in the preset word segmentation list. If so, the word is used as the target keyword.

[0063] The present invention filters out the segmentation text of the noun part of speech from the segmentation text containing the part-of-speech tags through a list derivation method, thereby improving the indirectness and readability of the query statement, improving the screening efficiency, and facilitating subsequent processing and analysis.

[0064] In an embodiment of the present invention, keywords are extracted from the segmented text according to preset part-of-speech rules. The preset part-of-speech rules are usually based on the language characteristics and grammatical structure of the text, and can screen out words that are more in line with the text theme as keywords. By tagging the segmented text with parts of speech and screening it according to the part-of-speech rules, words that are irrelevant or have low relevance to the text theme can be excluded, thereby improving the accuracy of keyword extraction and enhancing the robustness of text analysis.

[0065] S3. Perform a fuzzy query in the preset database based on the target keyword to obtain query fields.

[0066] In an embodiment of the present invention, the fuzzy query refers to a method for querying data that conforms to a certain specified format. It uses a combination of the target keyword and wildcards such as "%" for querying. Here, "%" represents any number of characters.

[0067] In an embodiment of the present invention, performing the fuzzy query in the preset database based on the target keyword to obtain query fields includes:

[0068] Construct a fuzzy query statement based on the target keyword and the preset wildcards;

[0069] Query the query field set saved in the preset database according to the fuzzy query statement to obtain the query fields containing the target keyword, so as to obtain the target query fields.

[0070] Specifically, the wildcards refer to tools for performing fuzzy queries in database queries. They allow the querying party to match data records through partial string patterns. Wildcards are particularly useful in SQL queries, especially when dealing with large datasets. By using wildcards such as "%", the querying party can greatly simplify the process of writing complex queries and improve the flexibility of queries; the query field set is the query result returned by the database according to the query request after sending a query request to the preset database according to predefined query conditions. The predefined query conditions are determined according to the content that the querying party may query in the corresponding text box in a specific application scenario. For example, if the target text is "Sales of electronic technology products in the financial channel in 2022", the field content of the query field set corresponding to this text may include: product time, product type, product channel, and sales amount, etc., fields related to the target text.

[0071] Further, in an embodiment of the present invention, constructing a fuzzy query statement based on the target keyword and wildcards is the Structured Query Language (SQL) statement. Exemplarily, in the field of fintech business, if the querying party queries the target text "Sales of electronic technology products in the financial channel in 2022", the predefined query condition is to query the sales amount of this product in 2022. The fuzzy query statement is search_pattern = f'%{2022 year}%'. Query the query field set saved in the preset database according to the fuzzy query statement to obtain the query fields containing the target keyword, thereby obtaining the target query fields.

[0072] For example, in the medical and health field, such as in a hospital's medical information management system, a preset database stores a large amount of patient medical records, including fields such as patient name, diagnosis results, medication records, etc. The doctor wants to find all medical records whose diagnosis results contain "pneumonia" related information to understand the recent incidence of pneumonia.

[0073] The target keyword is set to "pneumonia", and a fuzzy query statement is constructed based on the target keyword and the preset wildcard "%". In the SQL language environment, the query statement is SELECT*FROM medical record information table WHERE diagnosis result LIKE'%pneumonia%'; the constructed fuzzy query statement is submitted to the preset database for execution, and the database management system will query the saved medical record information table (query field set) according to the query statement for records whose diagnosis result field contains "pneumonia".

[0074] After querying, the present invention obtains the target query field, that is, all medical records containing "pneumonia" in the diagnosis results. The records contain relevant field information such as the patient's name, age, diagnosis time, specific diagnosis results, medication status, etc. Doctors can further analyze the disease characteristics and treatment effects of pneumonia patients through the target query field.

[0075] In an embodiment of the present invention, a fuzzy query is performed in a preset database using target keywords, allowing the use of partial keywords or keyword variants for searching, thereby improving the flexibility of the query. In the fuzzy query, relevant query results are provided by matching similar keywords, thereby enhancing the fault tolerance of the query.

[0076] S4. Perform data query in the database according to the query field to obtain target data.

[0077] In an embodiment of the present invention, the data query refers to the operation of requesting and retrieving data stored in a database. The data query is mainly used for behavioral queries of data retrieval and data update. The basic process of data query includes using SQL statements to specify the data tables and fields to be queried, and using conditional expressions to filter data records that meet specific conditions. The query results can be the values ​​of one or more fields, which are usually arranged in a certain order and displayed to the querying party.

[0078] In an embodiment of the present invention, performing a data query in the database according to the query field to obtain target data includes:

[0079] Obtaining a configured query file corresponding to the query field;

[0080] Parsing the configured query file to obtain a corresponding preset database query statement;

[0081] Perform data query in the database according to the database query statement and the query field to obtain target data.

[0082] In detail, the present invention retrieves configured query files related to the query fields from a preset database. These files usually contain database query logic and parameters preset for specific query fields. The obtained configured query files are parsed and converted into executable database query statements according to certain grammar or format rules. The parsing process includes parsing the file structure, identifying query parameters, building query logic, etc. The present invention performs data query in the preset database based on the database query statements obtained by parsing and in combination with the query fields. The query results are the required target data, which may be presented in the form of tables, record sets or other forms.

[0083] The present invention will also filter the data according to the authority of the querying party and return the data information to which the querying party has authority. For example, if the querying party has authority for Guangdong, only the data for Guangdong will be displayed.

[0084] For example, in the financial technology business field, the target text is "22-year financial channel electronic technology product sales", and the query fields corresponding to the text may include: product time, product type, product channel, sales and other fields related to the target text. According to the database query statement and query field, data query is performed in the database to obtain the query results, that is, the target data is "Year = 2022", "Product = Electronic Technology", "Channel = Finance", and "Sales".

[0085] For example, in the field of healthcare, if the electronic health record (EHR) system of a large medical institution needs to frequently execute multiple complex data queries to support clinical research, patient management and medical quality assessment, in order to improve query efficiency and flexibility, the system uses configurable query files to manage different query requirements.

[0086] Suppose a research team needs to query the information of all patients who have been diagnosed with "type 2 diabetes" and have received "insulin treatment" in the past year. Through the previous fuzzy query, it has been determined that the query fields include "patient ID", "diagnosis results", "medication records" and "consultation date"; according to the query requirements, the corresponding file is obtained from the system's configured query file library. The file defines how to query the data of patients with type 2 diabetes and insulin treatment. The system parses the configuration file and extracts the preset database query statement.

[0087] Based on the parsed database query statement, the system executes a query operation in the EHR system database. The query conditions include the diagnosis result containing "type 2 diabetes", the medication record containing "insulin", and the consultation date within the past year. After the query is completed, the system returns the target data, that is, all patient records that meet the conditions.

[0088] In an embodiment of the present invention, through the configuration query file, the query logic can be easily modified or extended without modifying the code, which greatly reduces maintenance costs and makes the query process more flexible and scalable; the configuration query file is usually carefully designed and tested to ensure that the query statement it generates can accurately reflect the query requirements, thereby enhancing the accuracy of the query.

[0089] S5. Display the target data returned by the database on a visual interface.

[0090] In an embodiment of the present invention, the visual interface refers to a graphical user interface, abbreviated as GUI. The visual interface is an interface display format for communication between people and computers, allowing users to use input devices such as a mouse to manipulate icons or menu options on the screen to select commands, call files, start programs or perform other daily tasks.

[0091] In detail, data visualization is the scientific and technological study of the visual representation of data. It is a kind of information extracted in a certain summary form, including various attributes and variables of the corresponding information units. Data visualization uses graphics, image processing, computer vision and user interface to visually interpret data through expression, modeling and display of three-dimensional, surface, attribute and animation.

[0092] The visualization interface of the present invention displays information in a graphical manner, using graphics, charts, maps and other visual elements to convey information, helping the inquirer to quickly understand data, discover trends and make decisions.

[0093] In an embodiment of the present invention, displaying the target data returned by the database on a visual interface includes:

[0094] performing data preprocessing on the target data to obtain processed target data;

[0095] The processed target data is bound to a preset chart configuration item to generate a visual chart.

[0096] In detail, the present invention performs data preprocessing on the target data, including data cleaning, data conversion, etc., such as removing duplicate values, handling missing data, adjusting data formats, etc., and converts the target data into a format and type suitable for visual display through data preprocessing. In the visual interface, there are usually multiple chart types preset, such as bar charts, line charts, pie charts, etc. and corresponding chart configuration items, such as axis labels, legends, titles, data formats, etc. The preprocessed target data is bound to the chart configuration items, that is, the binding is achieved by modifying the properties in the configuration item object, and then the preprocessed target data is mapped to the coordinate axis of the chart, the chart title, coordinate axis labels are set, and the color, font size, etc. are adjusted to display the target data in the visual chart in an intuitive and easy-to-understand manner.

[0097] Furthermore, for example, the target data after data preprocessing is "Year = 2022", "Product = Electronic Technology", "Channel = Finance", and "Sales". Time is used as the horizontal axis of the preset bar chart, and sales is used as the vertical axis of the bar chart. The bar chart is drawn and displayed using the drawing system in the preset database, such as the Matplotlib drawing tool.

[0098] In an embodiment of the present invention, by parsing the target data and binding it to preset chart configuration items, a visual chart can be quickly generated, avoiding the tedious process of manually drawing charts and configuring chart parameters, improving the efficiency of data visualization, and enhancing the readability of data. At the same time, it can also flexibly handle complex data structures and types, so that various types of data can be visually displayed.

[0099] For example, in the field of medical health, a tertiary hospital has developed a medical health data management system to better monitor and manage the blood sugar levels of hospitalized patients in order to optimize treatment plans and prevent complications. The system obtains relevant target data such as patients' blood sugar tests from the hospital's database and displays it in a visual interface.

[0100] The present invention extracts the blood glucose test data of all inpatients in the past month from a hospital database, including information such as patient ID, name, test time, and blood glucose value as target data; the data preprocessing includes data cleaning, i.e., checking whether there are missing values ​​or anomalies in the target data, and removing the abnormal data; converting the test time from the storage format of the database to a more intuitive date format to facilitate subsequent display, and at the same time classifying the blood glucose values ​​as normal, high, and extremely high, aggregating the blood glucose values ​​by patient ID and date, and calculating the average blood glucose value of each patient per day to obtain the processed target data.

[0101] In the visualization interface development tool, the configuration items of the line chart are preset, including the chart title, X-axis label, Y-axis label, legend, etc., and the processed target data (patient ID, date, average blood glucose value) are bound to the preset line chart configuration items; the visualization interface generates a line chart based on the bound data and configuration items. The blood glucose change trend of each patient is represented by a broken line, and different patients are distinguished by different colors. Doctors can use this chart to quickly understand the blood glucose fluctuations of each patient in the past month, identify patients with poor blood glucose control or abnormal blood glucose trends in a specific time period, and adjust the treatment plan in time.

[0102] For example, in the field of financial technology business, data visualization is also widely used in financial business. The financial industry is essentially a service industry with data information as its core support. Businesses such as credit issuance and risk control, and insurance product design are all formed on the basis of sufficient data information collection and analysis; in the digital economy era, financial institutions can more accurately profile borrowers by aggregating data information from other industries and fields, thereby minimizing information asymmetry and market failure and improving credit risk control capabilities.

[0103] The application of big data technology in data visualization has provided the Internet financial industry with valuable data resources and efficient analysis tools, promoting the innovation and development of the industry. Through big data analysis in data visualization, financial institutions can gain a deeper understanding of customer needs, formulate more accurate product and service strategies, and improve customer satisfaction and loyalty. At the same time, when using data queries for financial business, data security and privacy protection are important issues. It is necessary to establish a sound data classification and grading system to prevent the abuse of sensitive information such as data manipulation and ensure the security and compliance of data use.

[0104] The present invention segments the target text based on predefined dictionaries and rules, improves the accuracy of word segmentation recognition and the efficiency of word segmentation, eliminates ambiguous phenomena encountered in word processing, and provides strong support for subsequent text processing; the segmented text is tagged with parts of speech according to preset part-of-speech rules, and is screened according to the part-of-speech rules, which can exclude words that are irrelevant or have low relevance to the text topic, thereby improving the accuracy of keyword extraction and enhancing the robustness of text analysis; fuzzy queries are performed in a preset database using target keywords, allowing searches to be performed using partial keywords or keyword variants, thereby improving the flexibility of queries and enhancing the fault tolerance of queries; through configurable query files, query logic can be easily modified or extended without modifying the code, which greatly reduces maintenance costs, makes the query process more flexible and scalable, and enhances the accuracy of queries; by parsing the target data and binding it to preset chart configuration items, a visual chart can be quickly generated, avoiding the tedious process of manually drawing charts and configuring chart parameters, improving the efficiency of data visualization, and enhancing the readability of data.

[0105] It should be understood that the order of execution of the steps in the above embodiments does not necessarily mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0106] like Figure 3 , which is a functional module diagram of a data visualization configuration device provided by one embodiment of the present invention.

[0107] In an embodiment of the present disclosure, a data visualization configuration device is provided, which corresponds one-to-one to a data visualization configuration method in the above embodiment. Figure 3 As shown, the data visualization configuration device 100 can be installed in an electronic device. According to the functions to be implemented, the data real-time labeling device 100 includes a word segmentation module 101, a keyword extraction module 102, a fuzzy query module 103, a data query module 104 and a visualization display module 105. The functional modules are described in detail as follows:

[0108] The word segmentation module 101 is used to segment the preset target text to obtain a segmented text;

[0109] The keyword extraction module 102 is used to extract keywords from the segmented text according to preset part-of-speech rules to obtain target keywords;

[0110] A fuzzy query module 103 is configured to perform a fuzzy query in a preset database based on the target keyword to obtain a query field;

[0111] A data query module 104 is configured to perform a data query in the database according to the query field to obtain target data;

[0112] The visualization display module 105 is used to display the target data returned by the database on a visualization interface.

[0113] In one embodiment, when the word segmentation module 101 performs word segmentation on a preset target text to obtain a segmented text, it is used to:

[0114] Segmenting the target text into multiple short texts;

[0115] According to the maximum matching length of the short text, forward matching is performed with the short text one character at a time to obtain a segmented text.

[0116] In one embodiment, when the keyword extraction module 101 extracts keywords from the segmented text according to the preset part-of-speech rules to obtain target keywords, it is used to:

[0117] Performing part-of-speech tagging on each segmentation word in the segmentation text to obtain a segmentation text containing the part-of-speech tag;

[0118] The segmented text of the noun part of speech is screened out from the segmented text containing the part-of-speech tag and used as the target keyword.

[0119] In one embodiment, when performing part-of-speech tagging on each word in the segmented text to obtain the segmented text containing the part-of-speech tag, the keyword extraction module 102 is configured to:

[0120] Performing vector conversion on each word in the word segmentation text to obtain a word vector set;

[0121] Obtaining the feature vector corresponding to each word segmentation according to the word vector set;

[0122] Mapping the feature vector to the corresponding part-of-speech tag of each word according to a preset part-of-speech tag model;

[0123] Part-of-speech tagging is performed on the word vector set according to the part-of-speech tag to obtain a word segmentation text containing the part-of-speech tag.

[0124] In one embodiment, when the fuzzy query module 103 performs a fuzzy query based on the target keyword in a preset database to obtain a query field, it is configured to:

[0125] Constructing a fuzzy query statement based on the target keyword and preset wildcards;

[0126] According to the fuzzy query statement, a query field containing the target keyword is searched in a query field set stored in a preset database to obtain a target query field.

[0127] In one embodiment, when performing a data query in the database based on the query field to obtain target data, the data query module 104 is configured to:

[0128] Obtaining a configured query file corresponding to the query field;

[0129] Parsing the configured query file to obtain a corresponding preset database query statement;

[0130] Perform data query in the database according to the database query statement and the query field to obtain target data.

[0131] In one embodiment, when displaying the target data returned by the database on a visual interface, the visualization display module 105 is configured to:

[0132] performing data preprocessing on the target data to obtain processed target data;

[0133] The processed target data is bound to a preset chart configuration item to generate a visual chart.

[0134] In the present invention, for a data visualization configuration, first, the present invention segments the target text based on a predefined dictionary and rules, improves the accuracy of segmentation recognition and the efficiency of segmentation, eliminates the ambiguity encountered in word processing, and provides strong support for subsequent text processing; the segmented text is tagged with parts of speech according to preset part-of-speech rules, and is screened according to the part-of-speech rules, which can exclude those words that are irrelevant or have low relevance to the text topic, thereby improving the accuracy of keyword extraction and enhancing the robustness of text analysis; fuzzy queries are performed in a preset database using target keywords, allowing searches to be performed using partial keywords or keyword variants, thereby improving the flexibility of queries and enhancing the fault tolerance of queries; through the configuration of query files, the query logic can be easily modified or extended without modifying the code, which greatly reduces maintenance costs, makes the query process more flexible and scalable, and enhances the accuracy of queries; by parsing the target data and binding it to preset chart configuration items, a visual chart can be quickly generated, avoiding the tedious process of manually drawing charts and configuring chart parameters, improving the efficiency of data visualization, and enhancing the readability of data. The specific definition of a data visualization configuration device can be found in the definition of a data visualization configuration method above and will not be repeated here. Each module in the aforementioned data visualization configuration device can be implemented in whole or in part through software, hardware, or a combination thereof. Each of the aforementioned modules can be embedded in or independent of a processor in a computer device in hardware form, or can be stored in a memory in a computer device in software form, so that the processor can call and execute the corresponding operations of each of the aforementioned modules.

[0135] 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 4 As shown. The computer device includes a processor, memory, network interface and database connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes non-volatile and / or volatile storage media and 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 the functions or steps on the server side of a data visualization configuration method.

[0136] 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 5 As shown. The computer device includes a processor, memory, network interface, display screen, and input device connected via a system bus. 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 computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external server via a network connection. When executed by the processor, the computer program implements the functions or steps on the client side of a data visualization configuration method.

[0137] 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. When the processor executes the computer program, the following steps are performed:

[0138] Segment the preset target text to obtain segmented text;

[0139] Extract keywords from the segmented text according to preset part-of-speech rules to obtain target keywords;

[0140] Perform a fuzzy query in a preset database based on the target keyword to obtain a query field;

[0141] Performing data query in the database according to the query field to obtain target data;

[0142] The target data returned by the database is displayed on a visual interface.

[0143] In the several embodiments provided by the present invention, it should be understood that the disclosed devices and apparatuses can be implemented in other ways. For example, the system embodiments described above are merely illustrative. For example, the module division is merely a logical function division, and actual implementation may employ other division methods.

[0144] In addition, the functional modules in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or hardware plus software functional modules.

[0145] Therefore, the embodiments should be considered in all respects as illustrative and non-restrictive, and the scope of the invention is defined by the appended claims rather than the foregoing description, and all changes that come within the meaning and range of equivalents of the claims are intended to be embraced therein. Any reference to a figure in a claim should not be construed as limiting the claim to which it relates.

[0146] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0147] In some implementations of this embodiment, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that when the computer program is executed by a processor, the steps of the method described in the above embodiment are implemented.

[0148] The readable storage medium of the present invention stores a computer program, which, when executed by a processor of an electronic device, can implement:

[0149] Segment the preset target text to obtain segmented text;

[0150] Extract keywords from the segmented text according to preset part-of-speech rules to obtain target keywords;

[0151] Perform a fuzzy query in a preset database based on the target keyword to obtain a query field;

[0152] Performing data query in the database according to the query field to obtain target data;

[0153] The target data returned by the database is displayed on a visual interface.

[0154] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or computer device can be found in the relevant descriptions of the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0155] The computer-readable storage medium may also store at least one computer-executable program / instruction, such as a computer-readable instruction. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), a hard disk, a flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above may be performed.

[0156] In addition, the computer device may also include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (eg, keyboard, mouse, speaker, etc.).

[0157] The processor can communicate with external devices via an I / O bus via a wired or wireless network.

[0158] In one embodiment, the at least one computer executable instruction may also be compiled into or constitute a software product / computer program product, wherein one or more computer executable instructions are executed by a processor to perform the various functions and / or method steps in the embodiments described in the present technology.

[0159] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. 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. By way of illustration and not limitation, RAM is available in various 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).

[0160] Those skilled in the art will clearly understand that for the sake of convenience and brevity 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.

[0161] In the embodiments provided in the present disclosure, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely illustrative. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architectures, functions and operations of the devices, methods and computer program products according to multiple embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a portion of code, and the above-mentioned module, program segment or a portion of code contains one or more executable instructions for implementing the specified logical functions. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0162] It should be noted that, in this disclosure, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element limited by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0163] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. 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 make equivalent replacements for some of the technical features therein. 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 all be included in the scope of protection of the present invention.

[0164] It should be noted that if software tools or components other than those of our company appear in the embodiments of this application, they are only used for illustration and do not represent actual use.

Claims

1. A data visualization configuration method, characterized in that: The method comprises: Segment the preset target text to obtain segmented text; Extract keywords from the segmented text according to preset part-of-speech rules to obtain target keywords; Perform a fuzzy query in a preset database based on the target keyword to obtain a query field; Performing data query in the database according to the query field to obtain target data; The target data returned by the database is displayed on a visual interface.

2. The data visualization configuration method according to claim 1, characterized in that: The step of segmenting the preset target text to obtain a segmented text includes: Segmenting the target text into multiple short texts; According to the maximum matching length of the short text, forward matching is performed with the short text one character at a time to obtain a segmented text.

3. The data visualization configuration method according to claim 1, wherein: The keyword extraction of the segmented text according to the preset part-of-speech rules to obtain target keywords includes: Performing part-of-speech tagging on each segmentation word in the segmentation text to obtain a segmentation text containing the part-of-speech tag; The segmented text of the noun part of speech is screened out from the segmented text containing the part-of-speech tag and used as the target keyword.

4. The data visualization configuration method according to claim 3, wherein: The step of performing part-of-speech tagging on each word in the word segmentation text to obtain a word segmentation text containing part-of-speech tags includes: Performing vector conversion on each word in the word segmentation text to obtain a word vector set; Obtaining the feature vector corresponding to each word segmentation according to the word vector set; Mapping the feature vector to the corresponding part-of-speech tag of each word according to a preset part-of-speech tag model; Part-of-speech tagging is performed on the word vector set according to the part-of-speech tag to obtain a word segmentation text containing the part-of-speech tag.

5. The data visualization configuration method according to claim 1, wherein: The fuzzy query is performed in a preset database according to the target keyword to obtain the query field, including: Constructing a fuzzy query statement based on the target keyword and preset wildcards; According to the fuzzy query statement, a query field containing the target keyword is searched in a query field set stored in a preset database to obtain a target query field.

6. The data visualization configuration method according to claim 1, wherein: The step of performing a data query in the database according to the query field to obtain target data includes: Obtaining a configured query file corresponding to the query field; Parsing the configured query file to obtain a corresponding preset database query statement; Perform data query in the database according to the database query statement and the query field to obtain target data.

7. The data visualization configuration method according to claim 1, wherein: The displaying of the target data returned by the database on a visual interface includes: performing data preprocessing on the target data to obtain processed target data; The processed target data is bound to a preset chart configuration item to generate a visual chart.

8. A data visualization configuration device, characterized in that: The device comprises: The word segmentation module is used to segment the preset target text to obtain the segmented text; A keyword extraction module is used to extract keywords from the segmented text according to preset part-of-speech rules to obtain target keywords; A fuzzy query module, configured to perform a fuzzy query in a preset database based on the target keyword to obtain a query field; A data query module, configured to perform data query in the database according to the query field to obtain target data; A visualization display module is used to display the target data returned by the database on a visualization interface.

9. An electronic device, characterized in that: The electronic device comprises: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to perform a data visualization configuration method according to any one of claims 1 to 7.

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

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