CN115115246A

CN115115246A - Data processing method, data processing device, computer equipment and storage medium

Info

Publication number: CN115115246A
Application number: CN202210803710.2A
Authority: CN
Inventors: 王学慧
Original assignee: Gree Electric Appliances Inc of Zhuhai; Zhuhai Lianyun Technology Co Ltd
Current assignee: Gree Electric Appliances Inc of Zhuhai; Zhuhai Lianyun Technology Co Ltd
Priority date: 2022-07-07
Filing date: 2022-07-07
Publication date: 2022-09-27

Abstract

The application relates to a data processing method, a data processing device, computer equipment and a storage medium. The method comprises the following steps: when a data analysis request initiated by a user is received, statistical data related to a target theme in the data analysis request is counted and obtained, index scores of all attention indexes are calculated and determined according to a plurality of statistical data, the index scores are used for indicating the influence degree of the attention indexes on the target theme, visualization modes of all attention indexes are determined according to the index scores of all attention indexes, different visualization modes are used for highlighting target data corresponding to the attention indexes with larger influence degree on the target theme, the target data comprise statistical data related to the attention indexes, and in this way, the data focused by the user in an analysis result are simply and clearly subjected to targeted visualization, the visualization effect of the data analysis result is optimized, and the time of the user for searching the data focused by the user in mass visualization data is shortened.

Description

Data processing method, data processing device, computer equipment and storage medium

Technical Field

The present application relates to the field of computer technologies, and in particular, to a data processing method and apparatus, a computer device, and a storage medium.

Background

With the rapid development of big data and the internet era, whether the internet is huge or small and medium-sized enterprises, huge data can be generated along with the development of time, the data still is the big data era nowadays, the analysis of the big data cannot be separated from the development of a great number of enterprises, and under the condition of various data generated by the internet, the simple and rapid data analysis becomes one of important trends of the development.

Most of the existing data analysis methods are complex and lack of intuitiveness and convenience. After mass data are analyzed, the analyzed data need to be displayed in a visualization method, most of existing data analysis methods emphasize the analysis of the data, so that visualization processing methods after the data analysis are omitted, and existing visualization methods for analysis results directly perform visualization display on the analysis results, and cannot perform data display in a targeted manner, so that the visualization results become redundant, and the data concerned by a decision maker cannot be provided simply and clearly.

Disclosure of Invention

In order to solve the problem that in the prior art, data concerned by a decision maker in an analysis result cannot be simply and clearly visualized in a targeted manner, the application provides a data processing method, a data processing device, computer equipment and a storage medium.

In a first aspect, the present application provides a data processing method, including:

when a data analysis request sent by a target terminal is received, acquiring a plurality of statistical data related to a target topic in the data analysis request, wherein the statistical data is used for indicating a correlation index related to the target topic, the data analysis request comprises a plurality of attention indexes, and the attention index is any one of the correlation indexes;

determining an index score of each of the interest indexes based on a plurality of the statistical data, wherein the index score is used for indicating the influence degree of the interest index on the target subject;

determining a visualization mode of each attention index according to the index score of each attention index;

and sending the visualization mode of each attention index and the target data corresponding to each attention index to the target terminal, so that the target terminal displays the target data corresponding to each attention index in a visualization interface according to the visualization mode of each attention index, wherein the target data comprises the statistical data related to the attention index.

In a second aspect, the present application provides a data processing apparatus comprising:

the data analysis system comprises a statistic module, a processing module and a processing module, wherein the statistic module is used for acquiring a plurality of statistic data related to a target subject in a data analysis request when the data analysis request sent by a target terminal is received, the statistic data is used for indicating a relevant index related to the target subject, the data analysis request comprises a plurality of attention indexes, and the attention index is any one of the relevant indexes;

a scoring module, configured to determine an index score of each of the interest indicators based on a plurality of the statistical data, where the index score is used to indicate a degree of influence of the interest indicator on the target topic;

the determination module is used for determining a visualization mode of each attention index according to the index score of each attention index;

the display module is configured to send the visualization mode of each attention index and target data corresponding to each attention index to the target terminal, where the target terminal is configured to display the target data corresponding to each attention index in a visualization interface according to the visualization mode of each attention index, and the target data includes the statistical data related to the attention index.

In a third aspect, the present application provides a computer device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the following steps when executing the computer program:

In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of:

Based on the data processing method, when a data analysis request initiated by a user is received, statistical data related to a target theme in the data analysis request are counted and obtained, the statistical data are used for indicating correlation indexes related to the target theme, but not all the correlation indexes are indexes concerned by the user, the data analysis request comprises attention indexes concerned mainly by the user, index scores of all the attention indexes are calculated and determined according to a plurality of statistical data, the index scores are used for indicating the influence degrees of the attention indexes on the target theme, and the visualization modes of all the attention indexes are determined according to the index scores of all the attention indexes, namely the influence degrees of different attention indexes on the target theme are different, different visualization modes are respectively adopted to display the target data corresponding to all the attention indexes in a visualization interface, and different visualization modes are used for highlighting the target number corresponding to the attention indexes with larger influence degrees on the target theme According to the method, the target data comprise the statistical data related to the attention indexes, the data which are focused by the user in the analysis result are simply and clearly visualized in a targeted mode, the visualization effect of the data analysis result is optimized, and the time for the user to search the data which are focused by the user in the mass visualization data is shortened.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and together with the description, serve to explain the principles of the invention.

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.

FIG. 1 is a diagram of an application environment of a data processing method in one embodiment;

FIG. 2 is a flow diagram illustrating a data processing method according to one embodiment;

FIG. 3 is a block diagram of a data processing apparatus according to an embodiment;

FIG. 4 is a diagram illustrating an internal structure of a computer device according to an embodiment.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

FIG. 1 is a diagram of an application environment of a data processing method in one embodiment. Referring to fig. 1, the data processing method is applied to a data processing system including a terminal 110 and a data processing device 120, where the data processing device 120 is a device having a data storage function and a data processing function, the data processing device 120 may be provided independently of the terminal 110, for example, may be mounted in a server, or may be integrally provided in the terminal 110, and the data processing device 120 and the terminal 110 establish a communication connection by a wired or wireless method. The terminal 110 may specifically be a desktop terminal 110 or a mobile terminal 110, and the mobile terminal 110 may specifically be at least one of a mobile phone, a tablet computer, a notebook computer, and the like.

In one embodiment, fig. 2 is a flow chart illustrating a data processing method in one embodiment, and referring to fig. 2, a data processing method is provided. The present embodiment is mainly exemplified by applying the method to the data processing apparatus 120 in fig. 1, and the data processing method specifically includes the following steps:

step S210, when receiving a data analysis request sent by the target terminal 110, obtaining a plurality of statistical data related to a target topic in the data analysis request.

The statistical data is used for indicating a relevant index related to the target subject, the data analysis request comprises a plurality of attention indexes, and the attention index is any one of the plurality of relevant indexes.

Specifically, the target terminal 110 is a terminal 110 used by a user, the data analysis request is used to request to obtain a data analysis result corresponding to a target topic required by the user, for example, the target topic is "an increase reason of one month consumption cost of an injection molding manufacturing plant" or "a main influence factor of a corresponding material consumption rate of each workshop of the injection molding manufacturing plant", that is, the target topic is used to instruct a decision maker to initiate the data analysis request, the statistical data is locally stored data, and the statistical data may be data manually uploaded by the user or data automatically uploaded by a detection device detected from an industrial device. The statistical data is used for indicating a relevant index related to the target subject, for example, the statistical data comprises a scrap tonnage and a production tonnage, and the excess consumption rate can be indicated by a ratio between the scrap tonnage and the production tonnage, namely, the excess consumption rate is the relevant index corresponding to the scrap tonnage and the production tonnage. That is, the correlation index is calculated depending on the statistical data.

When data analysis processing is performed according to a data analysis request, a plurality of associated indexes related to a target theme may exist, the data analysis request includes a plurality of attention indexes, and the attention indexes are associated indexes concerned by a user.

Step S220, determining an index score of each of the attention indexes based on a plurality of the statistical data.

Wherein the indicator score is used to indicate a degree of influence of the indicator of interest on the target topic.

Specifically, a plurality of statistical data related to the target topic are analyzed, and an index score of each attention index relative to the target topic is determined, where the level of the index score determines the influence degree of each attention index on the target topic, for example, the higher the index score is, the greater the influence degree on the target topic is, or the lower the index score is, the greater the influence degree on the target topic is.

Step S230, determining a visualization mode of each of the attention indexes according to the index score of each of the attention indexes.

Specifically, the influence degrees on the target theme are different, the corresponding visualization modes are also different, the corresponding visualization mode for the attention index with the larger influence degree is used for displaying the corresponding data of the attention index in a key mode, otherwise, the corresponding visualization mode for the attention index with the smaller influence degree is only used for displaying the corresponding data of the attention index as auxiliary data, and different visual experiences are provided for the user through different visualization modes.

Step S240, sending the visualization mode of each attention index and the target data corresponding to each attention index to the target terminal 110.

The target terminal 110 is configured to display, in a visualization interface, target data corresponding to each attention index according to a visualization mode of each attention index, where the target data includes the statistical data related to the attention index.

Specifically, the target data is used to indicate data related to an attention index in the data analysis result, for example, the target topic is "cause of rise of one month consumption cost of the injection molding manufacturing plant", the data analysis result includes a plurality of attention indexes that affect the one month consumption cost of the injection molding manufacturing plant, but only the target data related to the attention index of the user with a strong attention in the data analysis result is fed back to the target terminal 110, and the target data is displayed in a targeted manner in the visualization interface of the target terminal 110 according to the visualization mode corresponding to each attention index, so that the data with a strong attention of the user is visualized in a targeted manner, the visualization effect of the data analysis result is optimized, and the time for the user to search the data with a strong attention in the mass visualization data is shortened.

For example, the related indexes related to the consumption cost of the injection molding manufacturing plant include indexes such as material consumption rate, total consumption amount, consumption amount ring ratio, material excess consumption rate, productivity, rejection rate and the like, but the attention indexes include material excess consumption rate, productivity and rejection rate, data analysis is performed only on the three attention indexes which are mainly focused by the user, so as to determine the influence degrees of the three attention indexes on the consumption cost, the visualization modes corresponding to the three attention indexes are determined according to the influence degrees, the target data corresponding to each attention index are displayed in a visualization interface of the target terminal 110 in a distinguishing manner according to the visualization modes corresponding to the three attention indexes, the correlation between the three attention indexes and the target theme is simply and clearly displayed to the user, if all the indexes related to the consumption cost in the data analysis result are displayed in a non-distinguishing manner according to the same visualization mode, the user needs to search data related to the attention index in the mass data, so that the visual display of the data analysis result becomes redundant, and therefore the targeted visual processing is performed on the data analysis result according to the user requirement based on the method, and the phenomenon that the visual data is gorgeous and unrealistic is avoided.

In one embodiment, the determining an index score of each of the indexes of interest based on a plurality of the statistical data, i.e. step S220, includes:

step S2201, determining, based on a plurality of statistical data, composition data corresponding to the attention index, where the composition data is the statistical data whose data type is the attention index;

step S2202, a weighted sum is performed on each of the component data, and an index score corresponding to the attention index is obtained.

Specifically, referring to the above example, if the attention index is a material excess consumption rate, the corresponding component data is the material excess consumption rate corresponding to each workshop, that is, the attention index and the corresponding component data indicate the same data type, but correspond to different statistical objects, that is, the attention index is used to indicate the material excess consumption rates corresponding to all the workshops, the component data is used to indicate the material excess consumption rates corresponding to each workshop, each component data corresponds to a weight coefficient, and each component data is weighted and summed according to the weight coefficient corresponding to each component data to obtain an index score corresponding to the attention index.

In this way, the index score of the material excess rate, the index score of the productivity and the index score of the rejection rate are calculated, and the index having the greatest influence on the consumption cost can be determined according to the index scores of the three indexes.

In one embodiment, the visualization mode includes a layout region, and the step S230 of determining the visualization mode of each of the attention indexes according to the index score of each of the attention indexes includes:

step S2301, according to the index score of each attention index, determining a layout area of the target data corresponding to each attention index in the visual interface.

Step S2301 specifically includes:

step S2301-1, dividing the plurality of attention indexes into key indexes and non-key indexes according to the index scores of the attention indexes.

Step S2301-2, the layout area corresponding to the key indexes is determined as a core area in the visual interface.

Step S2301-3, the layout region corresponding to the non-key index is determined as a distribution region in the visual interface except the core region.

The important index is any one of the plurality of attention indexes, the non-important index is the attention index except the important index in the plurality of attention indexes, and the distribution area is the area except the core area in the visual interface.

Specifically, in the visual interface, the target data are located in different layout areas, which have different visual experiences for the user, and the browsing habit of the user is usually from top to bottom, from left to right, and from center to boundary, so the layout area of the target data corresponding to each attention index in the visual interface is determined according to the browsing habit, the target data corresponding to the attention index having the largest influence on the target theme is located in the area that is most easily browsed in the visual interface, the target data corresponding to the attention index having the smallest influence on the target theme is located in other areas in the visual interface, and the target data corresponding to the attention index having different scores are subjected to different visual processing through different layout areas, so that the attention index having the largest influence on the target theme is highlighted in a key manner, and the user can quickly know the focus data concerned by the user.

The attention index with the highest index score is used as a key index, or the attention index with the lowest index score is used as a key index, in this embodiment, the attention index with the lowest index score is used as a key index example, and the attention index with the index score higher than the corresponding index score of the key index is used as a non-key index.

The typesetting area corresponding to the key indexes is determined as the core area in the visual interface, the core area is the area which is usually most easily and intuitively seen by the user, namely the core area can be the top area, the center area or the left area in the visual interface according to the browsing habits of the user, in the embodiment, the core area is the center area in the visual interface, therefore, the target data corresponding to the key indexes is displayed in the center area in the visual interface, the other distribution areas except the center area are taken as the typesetting area corresponding to the non-key indexes, namely, the target data corresponding to the non-key indexes are distributed and displayed in the visual interface around the target data corresponding to the key indexes, so that the user can intuitively and quickly see the target data corresponding to the key indexes which have the largest influence on the target theme in the visual interface, under the condition of ensuring that the target time corresponding to the key indexes is positioned in the visual center in the visual interface, the corresponding target data of different non-key indexes are ensured to be in a balanced state at different spatial positions in the whole visual interface, so that the aesthetic feeling of the visual effect is improved.

In one embodiment, the visualization mode further includes displaying a color, and after determining, according to the index score of each of the attention indexes, that each of the attention indexes corresponds to a layout region of the target data in the visualization interface, i.e., after step S2301, the method further includes:

step S2302, in each layout area, determining a display color of each sub-data in the corresponding layout area according to an influence degree of different sub-data in each target data on the corresponding attention index, where the sub-data in the target data is the statistical data related to the corresponding attention index.

Specifically, the display of the target data in each layout area is also displayed in a distinguishing manner according to the representation intensity, the subdata in the target data is statistical data related to the corresponding attention index, the influence degrees of different subdata on the corresponding attention index are different, the display color with a brighter color and a darker color is determined for the subdata with a larger influence degree, the influence degree of the subdata on the corresponding attention index is expressed through the gorgeous degree of the color or the shade of the color, and a user can visually see part of data with a prominent color from the plurality of data.

For example, in the analysis process of why the material consumption cost is increased as described above, each attention index includes a plurality of workshops, that is, the attention index of the material excess rate includes the excess rates of the plurality of workshops and the excess rate ranks of the workshops, the excess rate ranks of the workshops can be distinguished according to the display colors, according to the general knowledge of people, the deeper the color of the same color system, the higher the rank, and the difference between the excess rates of the workshops is more visually displayed through the shade conversion of different colors.

In one embodiment, the visualization mode further includes a display form, and after determining, according to the index score of each of the interest indexes, that each of the interest indexes corresponds to a layout region of the target data in the visualization interface, i.e., after step S2301, the method further includes:

step S2303, determining knowledge fields corresponding to the target data;

step S2304, determining the display form of each target data in the corresponding typesetting area according to the knowledge field of each target data.

Specifically, the knowledge fields specifically include, but are not limited to, the fields of manufacturing industry, medical treatment, meteorology, geography, computer simulation, education, aviation, e-commerce and the like, data of different knowledge fields correspond to different display forms, the display forms include graphic model display and graph display, the graph display is to use a graphic table to present corresponding data, the graphic simulation display is to use a picture as a background of a composition area, and display corresponding text data at each position on the picture to simulate the distribution condition of each text data in a corresponding actual area of the picture.

In one embodiment, the determining the display form of each target data in the corresponding layout area according to the knowledge domain of each target data, namely step S2304, includes:

step S2304-1, when the knowledge field of the target data is a first preset field, determining that the display form of the target data in the corresponding typesetting area is image-text simulation display;

step S2304-2, when the knowledge field of the target data is a second preset field, determining that the display form of the target data in the corresponding typesetting area is diagram display.

Specifically, the first preset field is used for indicating the knowledge field related to the spatial region, specifically including medical rescue, fire protection, weather, hydromechanics, traffic, and the like, for example, the spatial picture corresponding to the weather is used as the background in the composition region, and the weather data of each region is displayed on the spatial picture, so that the weather condition of each region in the spatial picture can be visually displayed to the user.

The second preset field is used for indicating the knowledge field related to data statistics, specifically comprises manufacturing industry, education, scientific research, diet and the like, the consumption cost of the injection molding manufacturing plant can be displayed by using a chart, different target data correspond to different charts, the chart comprises a snakelike chart, a bar graph, a fine line graph, a pie graph, a tree graph and the like, and the bar graph is selected when the data volume of subdata is small; selecting a fine line graph if the data volume of the subdata is large and each subdata is continuous; the data proportion condition expressed by using a pie chart can be considered; if the exact comparison is not required to be emphasized and the data size of the subdata is small, a bar graph can be used; the dependency relationship between data can be expressed by a tree graph.

In an embodiment, after the step S240 of sending the visualization mode of each of the attention indexes and the target data corresponding to each of the attention indexes to the target terminal 110, the method further includes:

step S250, generating a visualization analysis report corresponding to the data analysis request, where the visualization analysis report includes a determination procedure of a visualization mode corresponding to each attention index;

step S260, when a visual analysis request successfully matched with the data analysis request is received, adjusting the visual analysis report according to the visual analysis request to obtain a visual analysis template;

step S270, responding the visualization analysis request based on the visualization analysis template.

Specifically, a data analysis process, a determination process of scoring corresponding indexes of each attention index and a determination process of a corresponding visualization mode of each attention index are recorded, so that a visualization analysis report corresponding to a data analysis request is formed, when a visualization analysis request similar to the data analysis request is received next time, the visualization analysis report is adaptively adjusted according to the similar data analysis request, an adaptive visualization analysis template is obtained, data visualization processing is performed according to the visualization analysis template, so that a visualization result corresponding to the similar data analysis request can be quickly obtained, an iterative optimization visualization result is realized, and the visualization efficiency of the data analysis result is improved.

In a specific embodiment, when the target topic is the rising cause of the consumption cost of one month in an injection molding manufacturing plant, the data of the plant material consumption rate needs to be analyzed, a layer-by-layer progressive manner can be adopted for analysis, the total consumption amount and the consumption amount ring ratio of each month are firstly checked, whether the rising of the material excess consumption rate, the glue block production rate or the rejection rate is related to the rising of the consumption amount is analyzed and determined, the concerned indicators are represented by a graph through creating a graph component, the indicator score of each concerned indicator is determined, so that the consumption rate is found out as a possible factor causing the rising of the cost, but the consumption rate is unknown due to which plant consumption rate, so that the abnormal data area of a certain month is analyzed again, a space visualization is needed, namely, a graph-text simulation display is adopted, the plant field is converted into a geographic role, a plant distribution map is selected as a background, and respectively substituting the workshop position field into a horizontal axis and a vertical axis, calculating the workshop cost index field, and adjusting the color and the label of the workshop cost index field, so that the color is adjusted to be gradually changed in the area to show the influence degree of each workshop on the consumption cost.

After the analysis processing, the material consumption rate is determined as an important index, the adhesive block production rate and the rejection rate are determined as non-important indexes, the central area in the visual interface is determined as a visual area of the important index, the peripheral area of the central area is used as a visual area of the adhesive block production rate, the rejection rate and each workshop score ranking, the display color and the display form of data are determined in each visual area, so that the visual mode of each concerned index is determined, and the target terminal 110 is displayed according to the visual mode.

FIG. 2 is a flow diagram illustrating a data processing method according to an embodiment. It should be understood that, although the steps in the flowchart of fig. 2 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not limited to being performed in the exact order illustrated and, unless explicitly stated herein, may be performed in other orders. Moreover, at least a portion of the steps in fig. 2 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

In one embodiment, as shown in fig. 3, there is provided a data processing apparatus 120 comprising:

a statistics module 310, configured to, when a data analysis request sent by a target terminal 110 is received, obtain a plurality of statistics data related to a target topic in the data analysis request, where the statistics data is used to indicate a correlation index related to the target topic, the data analysis request includes a plurality of attention indexes, and the attention index is any one of the correlation indexes;

a scoring module 320, configured to determine an index score of each of the interest indicators based on a plurality of the statistical data, where the index score is used to indicate a degree of influence of the interest indicators on the target topic;

a determining module 330, configured to determine a visualization mode of each of the attention indexes according to the index score of each of the attention indexes;

the display module 340 is configured to send the visualization mode of each attention index and the target data corresponding to each attention index to the target terminal 110, where the target terminal 110 is configured to display the target data corresponding to each attention index in a visualization interface according to the visualization mode of each attention index, and the target data includes the statistical data related to the attention index.

In one embodiment, the scoring module 320 is specifically configured to:

determining composition data corresponding to the attention index based on a plurality of statistical data, wherein the composition data is the statistical data of which the data type is the attention index;

and carrying out weighted summation on each composition data to obtain an index score corresponding to the attention index.

In one embodiment, the determining module 330 is specifically configured to:

determining a layout area of the target data corresponding to each attention index in the visual interface according to the index score of each attention index;

the determining the layout area of the target data corresponding to each attention index in the visual interface according to the index score of each attention index includes:

dividing the plurality of attention indexes into a key index and a non-key index according to the index scores of the attention indexes, wherein the key index is any one of the plurality of attention indexes, and the non-key index is the attention index except the key index in the plurality of attention indexes;

determining a typesetting area corresponding to the key index as a core area in the visual interface;

and determining the typesetting area corresponding to the non-key index as a distribution area except the core area in the visual interface, wherein the distribution area is an area except the core area in the visual interface.

In one embodiment, the determining module 330 is specifically configured to:

and in each typesetting area, determining the display color of each subdata in the corresponding typesetting area according to the influence degree of different subdata in the target data on the corresponding attention index, wherein the subdata in the target data is the statistical data related to the corresponding attention index.

In one embodiment, the determining module 330 is specifically configured to:

determining a knowledge field corresponding to each target data;

and determining the display form of each target data in the corresponding typesetting area according to the knowledge field of each target data.

In one embodiment, the determining module 330 is specifically configured to:

when the knowledge field of the target data is a first preset field, determining that the display form of the target data in the corresponding typesetting area is image-text simulation display;

and when the knowledge field of the target data is a second preset field, determining that the display form of the target data in the corresponding typesetting area is chart display.

In one embodiment, the apparatus further comprises a generation module to:

generating a visual analysis report corresponding to the data analysis request, wherein the visual analysis report comprises a determination process of a visual mode corresponding to each attention index;

when a visual analysis request successfully matched with the data analysis request is received, adjusting the visual analysis report according to the visual analysis request to obtain a visual analysis template;

responding to the visualization analysis request based on the visualization analysis template.

FIG. 4 is a diagram illustrating an internal structure of a computer device in one embodiment. The computer device may specifically be the data processing apparatus 120 in fig. 1. As shown in fig. 4, the computer apparatus includes a processor, a memory, a network interface, an input device, and a display screen connected through a system bus. Wherein the memory includes a non-volatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program which, when executed by the processor, causes the processor to implement the data processing method. The internal memory may also have stored therein a computer program that, when executed by the processor, causes the processor to perform a data processing method. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.

Those skilled in the art will appreciate that the architecture shown in fig. 4 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.

In one embodiment, the data processing apparatus 120 provided in the present application may be implemented in the form of a computer program, and the computer program may be run on a computer device as shown in fig. 4. The memory of the computer device may store various program modules constituting the data processing apparatus 120, such as the statistics module 310, the scoring module 320, the determination module 330, and the display module 340 shown in fig. 3. The computer program constituted by the respective program modules causes the processor to execute the steps in the data processing method of the respective embodiments of the present application described in the present specification.

The computer device shown in fig. 4 may be executed by the statistics module 310 in the data processing apparatus 120 shown in fig. 3, when receiving a data analysis request sent by a target terminal 110, obtaining a plurality of statistics data related to a target topic in the data analysis request, where the statistics data is used to indicate a correlation index related to the target topic, and the data analysis request includes a plurality of attention indexes, where the attention index is any one of the plurality of correlation indexes. The computer device may perform, through the scoring module 320, determining an indicator score for each of the indicators of interest based on a plurality of the statistical data, wherein the indicator score is indicative of a degree of influence of the indicators of interest on the target topic. The computer device may determine a visualization mode for each of the indicators of interest by performing an indicator score according to each of the indicators of interest via the determination module 330. The computer device may execute, by using the display module 340, sending a visualization mode of each of the interest indicators and target data corresponding to each of the interest indicators to the target terminal 110, where the target terminal 110 is configured to display the target data corresponding to each of the interest indicators in a visualization interface according to the visualization mode of each of the interest indicators, and the target data includes the statistical data related to the interest indicators.

In one embodiment, a computer device is provided, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the method of any of the above embodiments when executing the computer program.

In an embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which computer program, when being executed by a processor, carries out the method of any of the above embodiments.

It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by instructing the relevant hardware through a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. 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 a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), double-rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), synchronous Link (Synchlink) DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and bus dynamic RAM (RDRAM).

It is noted that, in this document, relational terms such as "first" and "second," and the like, are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.

The foregoing are merely exemplary embodiments of the present invention, which enable those skilled in the art to understand or practice the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method of data processing, the method comprising:

2. The method of claim 1, wherein said determining an indicator score for each of said indicators of interest based on a plurality of said statistical data comprises:

determining composition data corresponding to the attention index based on a plurality of statistical data, wherein the composition data are the statistical data of which the data type is the attention index;

3. The method according to claim 2, wherein the visualization mode includes a layout region, and the determining the visualization mode for each of the interest indicators according to the indicator score for each of the interest indicators includes:

4. The method according to claim 3, wherein the visualization mode further includes displaying a color, and the determining of each of the attention indexes follows the layout region of the corresponding target data in the visualization interface according to the index score of each of the attention indexes, and the method further includes:

5. The method according to claim 4, wherein the visualization mode further includes a display form, and the method further includes determining, according to the index score of each of the interest indexes, that each of the interest indexes follows the layout region of the corresponding target data in the visualization interface, and the method further includes:

determining a knowledge field corresponding to each target data;

6. The method according to claim 5, wherein the determining the display form of each target data in the corresponding layout area according to the knowledge domain of each target data comprises:

7. The method according to claim 1, wherein the sending of the visualization mode of each of the interest indicators and the target data corresponding to each of the interest indicators to the target terminal further comprises:

8. A data processing apparatus, characterized in that the apparatus comprises:

9. A computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the steps of the method of any of claims 1 to 7 are implemented when the computer program is executed by the processor.

10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 7.