CN112749224A - Task-oriented visual recommendation method and device - Google Patents
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Abstract
The invention provides a task-oriented visual recommendation method and device, wherein the method comprises the following steps: performing data characteristic extraction on the task data set to obtain task data characteristic information; converting the task data characteristic information and the task data set into task statements conforming to the programming specification of an answer set; solving the task statements according to a preset visual task rule base to obtain visual chart information; and sequencing the visual chart information according to the technical complexity value to obtain a recommended visual chart. All charts that fit the rule set in the rule base are enumerated by using the Clingo software, where all charts are characterized by the Vega-Lite. Meanwhile, according to the complexity of the chart, columns which are interested by a user and the coverage range of the tasks, various visual ordering schemes are designed, and therefore task-oriented visual recommendation can be accurately and efficiently achieved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a task-oriented visual recommendation method and device.
Background
In the era of data explosion, the amount and dimensionality of data has grown rapidly, but the time and effort available to analysts to explore data has been limited. In the big data era, visualization technology can better serve data information representation and transmission. With the benefit of existing visualization tools (e.g., IBM manual eyes, Tableau and Microsoft Excel, etc.), analysts can perform data analysis intuitively. Meanwhile, the development of visualization is still in an early stage at present, and since people with different visualization knowledge levels are all participating in data analysis, a new visualization hand urgently needs a tool to reduce the threshold of visualization analysis. To achieve this vision, visualization recommendation (VisRec) is one of the key and effective technologies.
Generally, VisRec consists of visualization generation and ordering. The VisRec system should first enumerate all meaningful visualization charts and then sort them according to certain metrics. But to build a practical VisRec system, some troublesome challenges are faced. (1) Huge search space: the graph consists of many independent design decisions, e.g., which markers to use, which visualization channels to apply, etc., all of which combine to generate a large search space. (2) The evaluation criteria were inconsistent: visualization is a mining task, relates to perception information which is difficult to quantify for human beings, and in addition, a unified reference is lacked in the field of visualization at present.
Therefore, how to better implement task-oriented visual recommendation has become an urgent problem to be solved in the industry.
Disclosure of Invention
The invention provides a task-oriented visual recommendation method and device, which are used for solving the problem that task-oriented visual recommendation cannot be effectively realized in the prior art.
The invention provides a task-oriented visual recommendation method, which comprises the following steps:
performing data characteristic extraction on the task data set to obtain task data characteristic information;
converting the task data characteristic information and the task data set into task statements conforming to the programming specification of an answer set;
solving the task statements according to a preset visual task rule base to obtain visual chart information;
and sequencing the visual chart information according to the technical complexity value to obtain a recommended visual chart.
According to the task-oriented visual recommendation method, the step of extracting the data characteristics of the task data set to obtain the task data characteristic information comprises the following steps:
and extracting data type information, data quantity information and data base number information in the task data set to obtain task data characteristic information.
According to the task-oriented visual recommendation method, the preset visual task rule base comprises an existing bottom-layer database, a special industry database and an extended database.
According to the task-oriented visual recommendation method, the task statements are solved according to a preset visual task rule base to obtain visual chart information, and the method specifically comprises the following steps:
solving the task statements through the Clingo software according to a preset visual task rule base to obtain a compliance data set which accords with a rule set;
performing duplicate removal processing on the compliance data set to obtain a duplicate-removed compliance data set;
and converting the de-duplicated compliance data set into a declarative language of Vega-Lite to obtain visual chart information.
According to the task-oriented visual recommendation method, the step of sequencing the visual chart information according to the technical complexity value specifically comprises the following steps:
sorting the visual chart information according to the technical complexity value by a sorting method based on complexity or a sorting method based on reverse complexity;
the sorting method based on the complexity specifically refers to sorting the visualizations according to the complexity values of the chart information from low to high;
the sequencing method based on the reverse complexity is that the visual chart information is clustered by adopting an unsupervised algorithm DBSCAN to obtain visual chart information of multiple categories;
after the visual chart information of each category is sorted according to the sequence of the complexity values from low to high, the visual chart information of each category is sorted;
and then sorting the sorted visual chart information of each category according to the complexity of the visual chart information of each category and the sequence from low to high.
According to the task-oriented visual recommendation method, the method further comprises the following steps:
and sequencing the visual chart information through a sequencing method based on user interest coverage or a sequencing method based on task coverage to obtain a recommended visual chart.
The task-oriented visual recommendation device provided by the invention comprises: the extraction module is used for extracting data characteristics of the task data set to obtain task data characteristic information;
the conversion module is used for converting the task data characteristic information and the task data set into task statements conforming to the programming specification of an answer set;
the solving module is used for solving the task statements according to a preset visual task rule base to obtain visual chart information;
and the recommendation module is used for sequencing the visual chart information according to the technical complexity value to obtain a recommended visual chart.
The invention further provides an electronic device, which comprises a memory, a processor and a computer program stored on the memory and capable of running on the processor, wherein the processor executes the program to realize the steps of any one of the task-oriented visual recommendation methods.
The invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when being executed by a processor, carries out the steps of the task-oriented visual recommendation method according to any one of the preceding claims.
According to the task-oriented visual recommendation method and device, all charts which accord with the rule set in the rule base are enumerated by utilizing the Clingo software, wherein all charts are represented by Vega-Lite. Meanwhile, according to the complexity of the chart, columns which are interested by a user and the coverage range of the tasks, various visual ordering schemes are designed, and therefore task-oriented visual recommendation can be accurately and efficiently achieved.
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In order to more clearly illustrate the technical solutions of the present invention or the prior art, the drawings needed for the description of the embodiments or the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a flowchart illustrating a task-oriented visual recommendation method according to the present invention;
FIG. 2 is a schematic diagram of a ranking method corresponding to each analysis character provided by the present invention;
FIG. 3 is a task-oriented visual recommendation device provided by the present invention;
fig. 4 is a schematic physical structure diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. 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 invention.
Fig. 1 is a schematic flowchart of a task-oriented visualization recommendation method provided by the present invention, as shown in fig. 1, including:
step S1, extracting data characteristics of the task data set to obtain task data characteristic information;
step S2, converting the task data characteristic information and the task data set into task statements conforming to the programming specification of an answer set;
step S3, solving the task statements according to a preset visual task rule base to obtain visual chart information;
and step S4, sequencing the visual chart information according to the technical complexity value to obtain a recommended visual chart.
Specifically, the preset visualization task rule base described in the present invention may specifically include: the existing bottom database, the special industry database and the extended database.
The existing underlying database is actually a database determined according to the empirical academic research, for example, existing works such as Draco maintain a relatively complete knowledge base conforming to the programming specification of the answer set, including domain declaration of visualization attributes, definition of search space, various constraints for limiting the search space, and output specification.
The special industry database refers to a guide of a special visual practice of each special industry, for example, a visual exclusive database of each industry such as media, finance, geography, engineering and the like.
The extended database can be used for customizing the rule database, full-automatic recommendation can be performed, and a user only needs to input a data set. However, for user friendliness, the present invention allows the input section to specify rules including data columns and tasks of interest, which helps to limit the search space to within the user interest specification.
The method automatically extracts task data characteristic information according to the input of the task data set, wherein the task data characteristic information comprises data types, quantity, cardinality and the like.
And after extracting the task data characteristic information, converting the task data set and the data characteristic into a task statement which conforms to the programming specification of the answer set, and enabling the task statement to be used as the input of the Clingo software.
A specific conversion mode is to define a tag of answer set programming to describe the data characteristics, such as fieldtype (A, B) indicates that the type of variable A is B.
And the Clingo software receives the task statements input by the user and a preset visual task rule base to solve, and outputs all results conforming to the rule set.
The output of Clingo is converted to the declarative language of Vega-Lite to characterize the visual chart.
The specific conversion mode is that statements which are output by Clingo and conform to the programming specification of the answer set are mapped to each label of Vega-Lite, and finally, a complete Vega-Lite statement is formed.
If a plurality of tasks exist in the task data set, all the visual charts need to be deduplicated at the end of the visual generation module to obtain visual icon information.
In the invention, according to the idea of linear programming, corresponding technical complexity cost is generated for each component of Vega-Lite, and the calculation complexity of each chart is calculated as the sum of the corresponding cost values of each Vega-Lite component.
The visual icon information of the invention is composed of a Vega-Lite component, which is specifically as follows:
marking: in order to better assist the data analyst, the invention enriches the recommendable chart types as much as possible, and finally selects 14 types of markers after merging and filtering all markers supported by Vega-Lite: arc, area, bar, box plot, circle, error band, error bar, geoshape, line, point, rect, rule, text, and tick. In addition, the present invention supports composition charts in certain tasks.
A channel: in visualization analysis, rational application of visualization channels is one of the key factors in designing excellent visualizations. Visualization channels include position, color, size, shape, slope, texture, and animation, and the first four are consistently considered to generally satisfy the requirements of the visualization design. Thus, for simplicity, the visual channels in the present invention introduce only coordinate axes (x and y) and legends (color, size, and shape). It is worth mentioning that only a maximum of two legends can be introduced into a single chart.
Conversion: the data transformation may generate new values through various operations. All conversion operations of Vega-Lite embodied in the present invention include: bucketing, aggregation, sorting, stacking, regression, and scaling.
The invention provides various different methods for sequencing the visual icons, so that the final visual recommendation scheme can better meet the requirements of users.
The invention enumerates all charts that fit the rule set in the rule base by using the Clingo software, wherein all charts are characterized by using the Vega-Lite. Meanwhile, according to the complexity of the chart, columns which are interested by a user and the coverage range of the tasks, various visual ordering schemes are designed, and therefore task-oriented visual recommendation can be accurately and efficiently achieved.
Based on any of the embodiments, the step of sorting the visualized chart information according to the technical complexity value specifically includes:
sorting the visual chart information according to the technical complexity value by a sorting method based on complexity or a sorting method based on reverse complexity;
the sorting method based on the complexity specifically refers to sorting the visualizations according to the complexity values of the chart information from low to high;
the sequencing method based on the reverse complexity is that the visual chart information is clustered by adopting an unsupervised algorithm DBSCAN to obtain visual chart information of multiple categories;
after the visual chart information of each category is sorted according to the sequence of the complexity values from low to high, the visual chart information of each category is sorted;
and then sorting the sorted visual chart information of each category according to the complexity of the visual chart information of each category and the sequence from low to high.
Based on any of the above embodiments, the method further comprises:
and sequencing the visual chart information through a sequencing method based on user interest coverage or a sequencing method based on task coverage to obtain a recommended visual chart.
Fig. 2 is a schematic diagram of a ranking method corresponding to each analysis person provided by the present invention, and as shown in fig. 2, the present invention provides four ranking methods, which are respectively: complexity-based ranking, inverse complexity-based ranking, user interest coverage-based ranking, and task coverage-based ranking.
Specifically, complexity-based ranking: the ranking scheme ranks the visualizations according to the complexity value of the chart from low to high. In performing visual analysis, people tend to view a chart as a whole and want to know the information in the chart in a short time. The lower the complexity of the chart, the easier it is to understand, which conforms to the habit of people observing charts.
Reverse complexity based ordering: overall, the graphs with higher complexity values are ranked in the top row in this scheme. But instead of directly reverse ordering the complexity-based ranking scheme results directly, an unsupervised algorithm DBSCAN is first used to cluster all the results into several categories, where the visual charts in one category are similar to each other (e.g., only the axes need to be swapped or the aggregation method replaced, etc.). The visual charts are then sorted in reverse order by category while keeping the ordering within the categories unchanged.
Ranking based on user interest coverage: the scheme is primarily concerned with the interest columns entered by the user. Users generally want the chart to show as many columns of interest as possible. Therefore, if the chart cannot show all columns of interest to the user, it will be given a certain penalty value. The new graph complexity values s' are: s' ═ s \ N1/N2) In which N is1Is the number of columns of data, N, contained in a single chart2Is the number of usersThe number of columns of data of interest, s, is the initial complexity of the chart. The charts are finally sorted from low to high by s'.
Ranking based on task coverage: for multiple tasks, if a chart appears in the recommendation list for multiple tasks, it must have a general meaning and should be top ranked. Before sorting through this scheme, the recommendation lists for all tasks need to be merged and deleted first, and then the same graph averages the complexity. On this basis, all charts are first sorted by coverage for the tasks in the task library, while those charts with the same task coverage are then sorted internally by complexity.
According to the invention, through various different sorting modes, a better visual recommendation scheme can be generated by combining the user requirements.
Fig. 3 is a task-oriented visual recommendation apparatus provided in the present invention, as shown in fig. 3, including: an extraction module 310, a conversion module 320, a solving module 330, and a recommendation module 340; the extraction module 310 is configured to perform data feature extraction on a task data set to obtain task data feature information; the conversion module 320 is configured to convert the task data feature information and the task data set into a task statement meeting an answer set programming specification; the solving module 330 is configured to solve the task statement according to a preset visualization task rule base to obtain visualization chart information; the recommending module 340 is configured to sort the visual chart information according to the technical complexity value to obtain a recommended visual chart.
The invention enumerates all charts that fit the rule set in the rule base by using the Clingo software, wherein all charts are characterized by using the Vega-Lite. Meanwhile, according to the complexity of the chart, columns which are interested by a user and the coverage range of the tasks, various visual ordering schemes are designed, and therefore task-oriented visual recommendation can be accurately and efficiently achieved.
Fig. 4 is a schematic physical structure diagram of an electronic device provided in the present invention, and as shown in fig. 4, the electronic device may include: a processor (processor)410, a communication Interface 420, a memory (memory)430 and a communication bus 440, wherein the processor 410, the communication Interface 420 and the memory 430 are communicated with each other via the communication bus 440. The processor 410 may invoke logic instructions in the memory 430 to perform a task-oriented visual recommendation method comprising: performing data characteristic extraction on the task data set to obtain task data characteristic information; converting the task data characteristic information and the task data set into task statements conforming to the programming specification of an answer set; solving the task statements according to a preset visual task rule base to obtain visual chart information; and sequencing the visual chart information according to the technical complexity value to obtain a recommended visual chart.
In addition, the logic instructions in the memory 430 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions which, when executed by a computer, enable the computer to perform the task-oriented visual recommendation method provided by the above methods, the method comprising: performing data characteristic extraction on the task data set to obtain task data characteristic information; converting the task data characteristic information and the task data set into task statements conforming to the programming specification of an answer set; solving the task statements according to a preset visual task rule base to obtain visual chart information; and sequencing the visual chart information according to the technical complexity value to obtain a recommended visual chart.
In yet another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to perform the task-oriented visual recommendation method provided in the above embodiments, the method including: performing data characteristic extraction on the task data set to obtain task data characteristic information; converting the task data characteristic information and the task data set into task statements conforming to the programming specification of an answer set; solving the task statements according to a preset visual task rule base to obtain visual chart information; and sequencing the visual chart information according to the technical complexity value to obtain a recommended visual chart.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, but not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A task-oriented visual recommendation method is characterized by comprising the following steps:
performing data characteristic extraction on the task data set to obtain task data characteristic information;
converting the task data characteristic information and the task data set into task statements conforming to the programming specification of an answer set;
solving the task statements according to a preset visual task rule base to obtain visual chart information;
and sequencing the visual chart information according to the technical complexity value to obtain a recommended visual chart.
2. The task-oriented visual recommendation method according to claim 1, wherein the step of performing data feature extraction on the task data set to obtain task data feature information specifically comprises:
and extracting data type information, data quantity information and data base number information in the task data set to obtain task data characteristic information.
3. The task-oriented visual recommendation method according to claim 1, wherein the preset visual task rule base comprises an existing underlying database, a special industry database and an extended database.
4. The task-oriented visual recommendation method according to claim 1, wherein the step of solving the task statements according to a preset visual task rule base to obtain visual chart information specifically comprises:
solving the task statements through the Clingo software according to a preset visual task rule base to obtain a compliance data set which accords with a rule set;
performing duplicate removal processing on the compliance data set to obtain a duplicate-removed compliance data set;
and converting the de-duplicated compliance data set into a declarative language of Vega-Lite to obtain visual chart information.
5. The task-oriented visualization recommendation method according to claim 4, wherein the step of sorting the visualization chart information according to the technical complexity value specifically comprises:
sorting the visual chart information according to the technical complexity value by a sorting method based on complexity or a sorting method based on reverse complexity;
the sorting method based on the complexity specifically refers to sorting the visualizations according to the complexity values of the chart information from low to high;
the sequencing method based on the reverse complexity is that the visual chart information is clustered by adopting an unsupervised algorithm DBSCAN to obtain visual chart information of multiple categories;
after the visual chart information of each category is sorted according to the sequence of the complexity values from low to high, the visual chart information of each category is sorted;
and then sorting the sorted visual chart information of each category according to the complexity of the visual chart information of each category and the sequence from low to high.
6. The task-oriented visual recommendation method according to claim 4, further comprising:
and sequencing the visual chart information through a sequencing method based on user interest coverage or a sequencing method based on task coverage to obtain a recommended visual chart.
7. A task-oriented visual recommendation device, comprising:
the extraction module is used for extracting data characteristics of the task data set to obtain task data characteristic information;
the conversion module is used for converting the task data characteristic information and the task data set into task statements conforming to the programming specification of an answer set;
the solving module is used for solving the task statements according to a preset visual task rule base to obtain visual chart information;
and the recommendation module is used for sequencing the visual chart information according to the technical complexity value to obtain a recommended visual chart.
8. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the task oriented visual recommendation method according to any one of claims 1 to 6 when executing the program.
9. A non-transitory computer readable storage medium, having stored thereon a computer program, wherein the computer program, when being executed by a processor, is adapted to carry out the steps of the task oriented visual recommendation method according to any one of claims 1 to 6.
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