CN112463954B - Visual multidimensional data display system and method based on semantic recognition - Google Patents
Visual multidimensional data display system and method based on semantic recognition Download PDFInfo
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Abstract
The invention relates to a visual multidimensional data display system and method based on semantic recognition, belongs to the technical field of data processing and display, and solves the problems of low intelligent degree, low data utilization rate and low response speed of the existing data processing and display. The system comprises: the semantic recognition module obtains the query requirement of the user in a multi-round session mode so as to determine a query instruction; the data management module is used for acquiring service data from the service system, carrying out structuring processing to acquire different service scene data packets and storing the data packets in the database; the query module extracts service data from the database according to the query instruction; the analysis module converts the business data into at least one functional chart according to the characteristics of the business data; and operating the display module to display the extracted service data and the functional chart. The system improves the intelligent degree of data processing and displaying, the utilization rate of data and the data response speed.
Description
Technical Field
The invention relates to the technical field of data processing and display, in particular to a visual multidimensional data display system and method based on semantic recognition.
Background
In the prior art, enterprise users face tens of millions of service data and hundreds of millions of multidimensional report data visual graphic display requirements and can only rely on traditional dragging visual display tools for display; in addition, the traditional display tool can not actively guide the user to acquire or recommend valuable data to the user according to the user behavior, and has low consumption, so that the utilization rate of the data is low, and the flexible and changeable data analysis and processing requirements of the user can not be responded quickly, so that the use experience of the user is reduced.
Disclosure of Invention
In view of the above analysis, the present invention aims to provide a visual multidimensional data display system and method based on semantic recognition, which are used for solving the problems of low intelligent degree, low data utilization rate and low corresponding speed of the existing data processing and display method.
In one aspect, the present invention provides a visual multidimensional data presentation system based on semantic recognition, comprising:
the semantic recognition module is used for obtaining the query requirement of the user in a multi-round session mode based on the input instruction of the user and determining a corresponding query instruction; the query instruction comprises a query service scene, a query dimension, a query index, a query date or a query condition;
the data management module is used for acquiring service data from the service system, carrying out structuring processing on the service data to obtain different service scene data packets, and storing the data packets in the database;
the query module is used for extracting corresponding service data from the database according to the query instruction;
the analysis module is used for converting the service data into at least one functional chart according to the extracted characteristics of the service data;
and the operation display module is used for displaying the extracted service data and the function chart obtained by conversion.
Further, the database is further configured to store the determined query instruction, the corresponding extracted service data, and the corresponding function chart;
and the query module is used for directly extracting corresponding service data and a functional chart from the database according to the query instruction after the corresponding query instruction is determined by the semantic recognition module when the user inputs the same query requirement again.
Further, the analysis module is specifically configured to:
when the extracted business data contains years or months, converting the extracted business data into a trend chart by utilizing a trend analysis model;
when the ratio of the service data values in the extracted service data reaches a preset ratio, converting the extracted service data into a duty ratio chart by using a duty ratio analysis model;
and when the extracted service data contains singular values, converting the extracted service data into an outlier chart by utilizing an outlier analysis model.
Further, the service scene comprises an organization and a service type;
the semantic recognition module comprises:
the corpus module is used for respectively carrying out unified processing on the organization related to the historical query data and the standard names of the corresponding service types, respectively carrying out unified processing on the types of the key fields and the standard names corresponding to each service type, obtaining a corresponding standard corpus package and storing the corresponding standard corpus package in the database;
the entry processing module is used for performing word segmentation on the instruction input by the user to obtain a plurality of field information which are sequentially arranged, matching the field information with the organization, the service type and the key field in the corpus, and obtaining a corresponding query instruction according to a matching result.
Further, the semantic recognition module further includes a guidance module:
the guiding module is used for giving an input instruction prompt in a multi-round session mode based on the field information when the entry processing module cannot determine the corresponding query instruction through matching so as to guide a user to supplement the input instruction and transmit the input instruction to the entry management module, so that the corresponding query instruction is obtained; and when a plurality of inquiry instructions are obtained according to the matching result, sending the inquiry instructions to a user, selecting the inquiry instructions by the user through the operation display module, and transmitting the inquiry instructions selected by the user to the inquiry module.
Further, the guiding module is further configured to:
guiding the user to supplement query organization, query service type, query index, query dimension, query date or query condition, and further obtaining the corresponding query instruction.
Further, the guiding module is further configured to give a query instruction prompt according to a historical query record of the user, provide the user with a selection through the operation display module, and transmit the query instruction selected by the user to the query module.
Further, the data management module performs a structuring process on the service data to obtain different service scene corpora, including:
determining standard names of dimension information, index information and date information corresponding to each service data in each service scene;
the dimension information, index information and date information corresponding to each service data are processed in a unified way to obtain different service scene data packets which are stored in a database
Further, the term processing module is further configured to:
matching each field information with an organization and a service type in the corpus packet respectively, and determining standard names of the organization and the service type so as to obtain a service scene in a query instruction;
determining standard names of the field information according to the category and the standard names of the key fields in the determined key fields corresponding to the service scene, so as to obtain query dimensions, query indexes and query dates in the query instruction;
and marking the field information which is sequentially arranged based on the obtained standard name, and replacing the corresponding field information, thereby obtaining the query instruction.
On the other hand, the invention provides a visual multidimensional data display method based on semantic recognition, which comprises the following steps:
acquiring the query requirement of a user in a multi-round session mode based on the input instruction of the user, and determining a corresponding query instruction; the query instruction comprises a query service scene, a query dimension, a query index, a query date or a query condition;
acquiring service data from a service system, carrying out structuring processing on the service data to obtain different service scene data packets, and storing the data packets in a database;
extracting corresponding service data from the database according to the query instruction;
converting the service data into at least one functional chart according to the extracted characteristics of the service data;
and displaying the extracted service data and the function chart obtained by conversion through a display.
Compared with the prior art, the invention has at least one of the following beneficial effects:
1. according to the visual multidimensional data display system and method based on semantic recognition, the query intention of the user is obtained in a multi-round session mode so as to determine a corresponding query instruction; in addition, corresponding input instructions or inquiry instruction prompts can be provided for the user according to the historical inquiry records of the user so as to be selected by the user, or corresponding data and charts can be directly displayed to the user according to the historical inquiry records of the user, so that humanization of human-computer interaction is improved, and the response rate of data inquiry is improved;
2. the invention can construct a scenerized data analysis model according to the business characteristics of enterprises, the analysis model can analyze the business data according to the characteristics of the obtained business data and convert the business data into corresponding charts, the steps of manual learning, calculation, chart making and the like are omitted, the data display is diversified, specifically, according to the data characteristics, the algorithm services such as content recommendation, collaborative filtering and the like are provided for realizing active association analysis recommendation, various types of multidimensional data analysis charts can be provided for users with different businesses and different requirements, the presentation mode is accurate and scientific, support is provided for reporting and conveying data information, and the data processing and analysis and intelligent degree and the data utilization rate are improved; in addition, the analysis model is not limited by the client and the display terminal, so that convenience is provided for centralized management of data, the time for data processing is saved, and the data visualization display efficiency is improved.
In the invention, the technical schemes can be mutually combined to realize more preferable combination schemes. Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention may be realized and attained by the structure particularly pointed out in the written description and drawings.
Drawings
The drawings are only for purposes of illustrating particular embodiments and are not to be construed as limiting the invention, like reference numerals being used to refer to like parts throughout the several views.
FIG. 1 is a schematic diagram of a visual multi-dimensional data presentation system based on semantic recognition according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a result of structuring service data according to an embodiment of the present invention;
fig. 3 is a schematic diagram of service data corresponding to other operation fees queried by a user according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of an analysis module according to an embodiment of the present invention, according to the service data shown in FIG. 3;
FIG. 5 is a schematic diagram of a guidance module giving an input instruction prompt in a multi-round session manner according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a visual multidimensional data display method based on semantic recognition according to an embodiment of the present invention.
Detailed Description
Preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, which form a part hereof, and together with the description serve to explain the principles of the invention, and are not intended to limit the scope of the invention.
The invention discloses a visual multidimensional data display system based on semantic recognition. As shown in fig. 1, the system includes:
the semantic recognition module is used for obtaining the query requirement of the user in a multi-round session mode based on the input instruction of the user and determining the corresponding query instruction. The user can input instructions manually or through voice, and the mode of multiple rounds of conversations can be used for determining inquiry instructions by inputting multiple rounds of conversations of the user as a whole. Specifically, the query instruction includes a query service scenario, a query dimension, a query index, a query date, or a query condition. The traffic scenario includes an organization and a traffic type. By way of example, the business scenario may be other operating fee analysis scenarios of company a or marketing campaign user category analysis scenarios of company B, etc.; specifically, the company A and the company B are organizations, other operation cost analysis scenes and marketing activity user category analysis scenes are business types, wherein the other operation cost analysis scenes comprise business activity dimensions and a series of cost element indexes, such as business charge, travel charge, consultation charge and the like; the marketing campaign user category analysis scenario includes a business campaign dimension, a user category dimension, and a series of marketing campaign metrics such as number of users, sales, marketing costs, etc.
Preferably, the policies corresponding to the multi-round session mode include: the exceeding time clears the history state memory, the exceeding polling times clears the history state memory and the permanent preservation strategy, etc. The history state is mainly used for recording and storing word slot values in word slots, wherein the word slots are slots used for filling in keyword entries in user conversations.
The data management module is used for acquiring service data from the service system, carrying out structuring processing on the service data to obtain different service scene data packets, and storing the different service scene data packets in the database. The business systems refer to business systems of different enterprises or business systems corresponding to different fields in the enterprises. As shown in fig. 2, specifically, the structuring of the service data refers to the unification (or specification) of the scene, dimension, index, date, etc. of the service data. Illustratively, the data in the business system is loaded into the system, and the data is processed according to the unified specification, including synonym transformation, data complete line verification and the like.
And the query module is used for extracting corresponding service data from the database according to the query instruction.
The analysis module actively explores potential rules of the service data based on machine learning, intelligent algorithm, NLP technology and the like, and digs abnormal deviation values, null values, maximum values, minimum values, average values, gradients and the like of various dimension and index combinations under the scene to locate abnormal service data information in the data set. Preferably, the service data may be converted into at least one function chart according to characteristics of the extracted service data. Specifically, different analysis models can be set according to business characteristics of different enterprises.
And the operation display module is used for displaying the extracted service data and the function chart obtained by conversion. Preferably, the operation display module can be a PC end or a mobile phone end for realizing man-machine interaction.
Preferably, the database is further configured to store the determined query instruction, the corresponding extracted service data, and the corresponding function chart.
When the user inputs the same query requirement again, after the semantic recognition module determines the corresponding query instruction, the query module can directly extract the corresponding service data and the function chart from the database according to the query instruction and directly display the service data and the function chart through the operation display module, so that the response speed of data processing and display is improved, and the user experience is improved.
Preferably, the analysis module may include a trend analysis model, a duty cycle analysis model, and an outlier analysis model.
Specifically, when the extracted business data includes a year or month, that is, when there is a change of the queried data with time, the corresponding trend analysis model may convert the extracted business data into a trend chart for reference by the user.
When the ratio of the service data values in the extracted service data reaches a preset ratio, converting the extracted service data into a duty ratio chart by using a duty ratio analysis model for reference of a user. Preferably, the preset proportion can be set in a self-defined manner according to the use requirement. For example, the total cost of a business in the year 2020 is 150 ten thousand, and the cost of the personnel cause is 90 ten thousand, and the ratio of the personnel cause to the cost of other items is more than 50%, so that it is obvious that the difference between the cost of the personnel cause and the cost of other items is obvious, and the corresponding business data is converted into a ratio chart by the ratio analysis model, so that a user can more intuitively determine the dominant ratio data item through the chart.
When the extracted business data contains singular values, the corresponding outlier analysis model may convert the extracted business data into an outlier graph. For example, only electricity consumption business in the business scale factor type cost has a corresponding cost value, and the cost values of other items (such as enterprise management, power supply service, transformer overhaul, intelligent electricity consumption and the like) are all 0, so that the condition that the cost data of the electricity consumption business possibly has abnormality is indicated, and the outlier analysis model converts the cost data into an outlier chart for reference by a user to remind the user that the data possibly has abnormality.
Preferably, when the extracted service data has the characteristics, the analysis module correspondingly converts the service data into a plurality of charts. For example, when the user inquires about other operation fees in february, the obtained business data is shown in fig. 3, which further includes data including corresponding dimensions and corresponding indexes of other operation fees in february and march, and only part of the business data is shown in fig. 3 due to greater space; the analysis module may analyze the characteristics of the queried service data and then convert the characteristics into a corresponding chart, as shown in fig. 4. The intelligent degree of the system is improved, and meanwhile, the work of manually making the table and drawing is lightened. Specifically, fig. 3 includes changes of various other operating costs with months, so the trend analysis model converts the service data into a corresponding trend chart according to the characteristics; the difference value of the personnel movement cost is larger than that of other cost, so that the duty ratio analysis model can convert service data into a corresponding duty ratio chart according to the characteristics; in addition, the policy-cause fees are relatively averaged over three months, so the low variance analysis model can convert business data into an average chart based on the characteristics; and in the several indexes corresponding to the business scale factor dimension, only the electricity utilization business index has a value which is far larger than that of other indexes, and the business data can be converted into an outlier chart according to the characteristic by utilizing an outlier analysis model.
Preferably, the analysis module converts the extracted business data into a corresponding chart by:
determining the display dimension of the chart according to the query dimension, the query condition and the display mode (ascending order or descending order); and determining the display measurement of the chart according to the query dimension, the query index, the query condition and the display mode, wherein the display mode adopts a visual mode, and preferably comprises cards, lists, column charts, bar charts, line charts, pie charts, ring charts, scatter charts, tree charts and the like. Preferably, priorities of a plurality of default display modes of the analysis model are preset, if the visualization mode is empty or conflicts with the display dimension measurement number of the analysis model, the display dimension number is judged, if 0 display dimensions are judged, 1 display dimension is displayed by default, 1 display dimension or measurement value is larger than or equal to 1 display dimension or measurement value is larger than a 2 default list, and the default display dimensions are converted into a line graph when the dimensions are time.
Preferably, the semantic recognition module includes:
the corpus module is used for respectively carrying out unified processing on the organization related to the historical query data and the standard names of the corresponding service types, respectively carrying out unified processing on the types of the key fields and the standard names corresponding to each service type, obtaining the corresponding standard corpus package and storing the corresponding standard corpus package in the database. For example, the names of the companies a may be various, the names of a certain part of the companies a may be various, the various names are unified into a standard name, and the corresponding service types are treated the same. Specifically, each service type includes a key field of a type including time, dimension, index, etc. Exemplary, the types of key fields corresponding to the last year, the present month, the month and the last month are all time, and the present month, the present month and the present month are unified into a standard name of 'present month'; the types of key fields corresponding to the business charge, the travel charge, the accommodation charge, the traffic charge and the catering charge are all used as indexes, and the travel charge, the accommodation charge, the traffic charge and the catering charge are unified into a standard name of 'travel charge'.
The entry processing module is used for performing word segmentation on the instruction input by the user to obtain a plurality of field information which are sequentially arranged, matching the field information with the organization, the service type and the key field in the corpus, and obtaining a corresponding query instruction according to a matching result.
Specifically, each field of information is respectively matched with an organization and a service type in a corpus, and standard names of the organization and the service type are determined, so that a service scene in a query instruction is obtained. Specifically, when the user queries the company or related data in the company, the corresponding organization standard name does not need to be determined, and in addition, the corresponding service type can be determined according to the specific characteristics of certain field information.
And determining the standard name of the field information according to the category and the standard name of the key field in the key field corresponding to the determined service scene, thereby obtaining the query dimension, the query index and the query date in the query instruction.
And marking the field information which is sequentially arranged based on the obtained standard name, and replacing the corresponding field information, thereby obtaining the query instruction.
Illustratively, the user inputs instructions: i look for business activities with a monthly transaction fee greater than 10 and a travel fee less than 100 and descending in order of transaction fee. The specific process of obtaining the query instruction according to the instruction is as follows:
step 1, performing an input instruction and obtaining a plurality of field information which are sequentially arranged: this month, charge, greater than 10, travel, less than 100, business, charge, descending order.
And 2, determining the corresponding service type as multidimensional analysis of other operation fees according to the travel fees and the transaction fees.
And step 3, determining the query dimension as the business activity according to the field information business activity.
And 4, determining inquiry indexes as the travel fees and the working fees according to the field information travel fees and the working fees.
And 5, determining the inquiry time of the month according to the field information as the month, wherein the month is the month when the user inquires.
And 6, checking the conditions of greater than 10, less than 100 according to the field information, wherein the checking conditions are that the fee is greater than 10 and the fee is less than 100.
And 7, determining the data display form of the query to be displayed in descending order of the transaction fee according to the field information transaction fee.
Step 8, carrying out text labeling on the field information so as to obtain a corresponding query instruction:
i look up the month < query time > the < query index > business activity of < query dimension > business activity of < query index > business fee < query index > value < 10 > and < query index > business travel fee < query index > is less than < query index > value < 100 > and in descending order of < query index > business fee < presentation form >.
Preferably, the semantic recognition module further comprises a guidance module:
when the entry processing module cannot determine the corresponding query instruction through matching, as shown in fig. 5, the guiding module is configured to give an input instruction prompt in a multi-round session manner based on field information, so as to guide a user to supplement the input instruction and transmit the input instruction to the entry management module, thereby obtaining the corresponding query instruction.
In addition, when the entry processing module obtains a plurality of inquiry instructions according to the matching result, the guiding module can send the plurality of inquiry instructions to the user, the user can select the inquiry instructions through the operation display module, and the inquiry instructions selected by the user are transmitted to the inquiry module.
Preferably, the guiding module gives the input instruction prompt in a multi-round session mode, including:
guiding the user to supplement query organization, query service type, query index, query dimension, query date or query condition, and further obtaining the corresponding query instruction.
Preferably, the guiding module performs machine learning based on the historical query record of the user, so that when the user inputs an incomplete instruction, a query instruction prompt can be given according to the historical query record of the user, the user can select the query instruction through the operation display module, the query instruction selected by the user is transmitted to the query module, and other query instructions related to the query instruction are recommended to the user, so that data query references are provided for the user, and the use efficiency of the data is improved.
Preferably, the data management module performs structural processing on service data to obtain different service scene corpus packages, including:
and determining standard names of dimension information, index information and date information corresponding to each service data in each service scene.
And carrying out unified processing on dimension information, index information and date information corresponding to each service data to obtain different service scene data packets, and storing the different service scene data packets in a database.
The invention discloses a visual multidimensional data display method based on semantic recognition.
Since the method embodiment is the same as the system embodiment described above, the details of the method embodiment will be referred to the system embodiment, and will not be described herein.
As shown in fig. 6, the method comprises the steps of:
acquiring the query requirement of a user in a multi-round session mode based on the input instruction of the user, and determining a corresponding query instruction; the query instruction comprises a query service scene, a query dimension, a query index, a query date or a query condition.
And acquiring service data from the service system, carrying out structuring processing on the service data to obtain different service scene data packets, and storing the different service scene data packets in a database.
And extracting corresponding service data from the database according to the query instruction.
And converting the service data into at least one functional chart according to the characteristics of the extracted service data.
And displaying the extracted service data and the function chart obtained by conversion through a display.
Compared with the prior art, the visual multidimensional data display system and method based on semantic recognition provided by the invention have the advantages that on one hand, the query intention of a user is obtained in a multi-round session mode so as to determine a corresponding query instruction; in addition, corresponding input instructions or inquiry instruction prompts can be provided for the user according to the historical inquiry records of the user so as to be selected by the user, or corresponding data and charts can be directly displayed to the user according to the historical inquiry records of the user, so that humanization of human-computer interaction is improved, and the response rate of data inquiry is improved; on the other hand, the invention can construct a scene data analysis model according to the business characteristics of enterprises, the analysis model can analyze the business data according to the characteristics of the obtained business data and convert the business data into corresponding charts, the steps of manual learning, calculation, chart making and the like are omitted, the data display is diversified, specifically, according to the data characteristics, the algorithm services based on content recommendation, collaborative filtering and the like are provided to realize active association analysis recommendation, various multi-dimensional data analysis charts can be provided for users with different businesses and different requirements, the presentation mode is accurate and scientific, support is provided for reporting and conveying data information, and the data processing and analysis and intelligent degree and the data utilization rate are improved; in addition, the analysis model is not limited by the client and the display terminal, so that convenience is provided for centralized management of data, the time for data processing is saved, and the data visualization display efficiency is improved.
Those skilled in the art will appreciate that all or part of the flow of the methods of the embodiments described above may be accomplished by way of a computer program to instruct associated hardware, where the program may be stored on a computer readable storage medium. Wherein the computer readable storage medium is a magnetic disk, an optical disk, a read-only memory or a random access memory, etc.
The present invention is not limited to the above-mentioned embodiments, and any changes or substitutions that can be easily understood by those skilled in the art within the technical scope of the present invention are intended to be included in the scope of the present invention.
Claims (4)
1. A visual multi-dimensional data presentation system based on semantic recognition, comprising:
the semantic recognition module is used for obtaining the query requirement of the user in a multi-round session mode based on the input instruction of the user and determining a corresponding query instruction; the query instruction comprises a query service scene, a query dimension, a query index, a query date or a query condition; the service scene comprises an organization and a service type;
the data management module is used for acquiring service data from the service system, carrying out structuring processing on the service data to obtain different service scene data packets, and storing the data packets in the database;
the query module is used for extracting corresponding service data from the database according to the query instruction;
the analysis module is used for converting the service data into at least one functional chart according to the extracted characteristics of the service data;
the operation display module is used for displaying the extracted service data and the function chart obtained by conversion;
the analysis module is specifically used for:
mining abnormal deviation values, null values, maximum values, minimum values, average values and gradients of various dimensions and index combinations under a scene of the service data, and positioning abnormal service data information in the data set;
when the extracted business data contains years or months, converting the extracted business data into a trend chart by utilizing a trend analysis model;
when the ratio of the service data values in the extracted service data reaches a preset ratio, converting the extracted service data into a duty ratio chart by using a duty ratio analysis model;
when the extracted business data contains singular values, the data may have abnormality, and the extracted business data is converted into an outlier chart by using an outlier analysis model to remind a user that the data may have abnormality;
the semantic recognition module comprises:
the corpus module is used for respectively carrying out unified processing on the organization related to the historical query data and the standard names of the corresponding service types, respectively carrying out unified processing on the types of the key fields and the standard names corresponding to each service type, obtaining a corresponding standard corpus package and storing the corresponding standard corpus package in the database;
the entry processing module is used for word segmentation of an instruction input by a user to obtain a plurality of field information which are sequentially arranged, matching the field information with the organization, the service type and the key field in the standard corpus, and obtaining a corresponding query instruction according to a matching result;
the semantic recognition module further comprises a guiding module:
the guiding module is used for: when the entry processing module cannot determine the corresponding query instruction through matching, an input instruction prompt is given in a multi-round session mode based on the field information so as to guide a user to supplement the input instruction and transmit the input instruction to the entry processing module, and then the corresponding query instruction is obtained; when a plurality of inquiry instructions are obtained according to the matching result, the inquiry instructions are sent to a user, the user selects the inquiry instructions through the operation display module, the inquiry instructions selected by the user are transmitted to the inquiry module, and other inquiry instructions associated with the inquiry instructions are recommended to the user;
the guidance module is further configured to:
guiding a user to supplement query organization, query service type, query index, query dimension, query date or query condition, and further obtaining a corresponding query instruction;
the data management module performs structural processing on the service data to obtain different service scene corpus packages, and the data management module comprises:
determining standard names of dimension information, index information and date information corresponding to each service data in each service scene;
carrying out unified processing on the dimension information, the index information and the date information corresponding to each service data to obtain different service scene data packets, including synonym conversion and complete data line verification, and storing the data packets in a database;
the term processing module is further configured to:
matching each field information with an organization and a service type in the corpus packet respectively, and determining standard names of the organization and the service type so as to obtain a service scene in a query instruction;
determining standard names of the field information according to the category and the standard names of the key fields in the determined key fields corresponding to the service scene, so as to obtain query dimensions, query indexes and query dates in the query instruction;
and marking the field information which is sequentially arranged based on the obtained standard name, and replacing the corresponding field information, thereby obtaining the query instruction.
2. The visual multi-dimensional data presentation system of claim 1, wherein,
the database is also used for storing the determined query instruction, the corresponding extracted service data and the corresponding function chart;
and the query module is used for directly extracting corresponding service data and a functional chart from the database according to the query instruction after the corresponding query instruction is determined by the semantic recognition module when the user inputs the same query requirement again.
3. The visual multi-dimensional data display system according to claim 1, wherein the guidance module is further configured to give a query instruction prompt according to a historical query record of a user, provide the query instruction prompt for the user to select through the operation display module, and transmit the query instruction selected by the user to the query module.
4. A method of semantic recognition based visualization of a visualization multidimensional data presentation system in accordance with claim 1, comprising:
acquiring the query requirement of a user in a multi-round session mode based on the input instruction of the user, and determining a corresponding query instruction; the query instruction comprises a query service scene, a query dimension, a query index, a query date or a query condition;
acquiring service data from a service system, carrying out structuring processing on the service data to obtain different service scene data packets, and storing the data packets in a database;
extracting corresponding service data from the database according to the query instruction;
converting the service data into at least one functional chart according to the extracted characteristics of the service data;
and displaying the extracted service data and the function chart obtained by conversion through a display.
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