CN110377659A - A kind of intelligence chart recommender system and method - Google Patents
A kind of intelligence chart recommender system and method Download PDFInfo
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- CN110377659A CN110377659A CN201910680819.XA CN201910680819A CN110377659A CN 110377659 A CN110377659 A CN 110377659A CN 201910680819 A CN201910680819 A CN 201910680819A CN 110377659 A CN110377659 A CN 110377659A
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- 230000000007 visual effect Effects 0.000 claims abstract description 10
- 238000013079 data visualisation Methods 0.000 claims description 5
- 238000010801 machine learning Methods 0.000 claims description 3
- 239000002131 composite material Substances 0.000 claims 1
- 238000012545 processing Methods 0.000 abstract description 2
- 238000007405 data analysis Methods 0.000 description 11
- 238000012800 visualization Methods 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 3
- 238000013507 mapping Methods 0.000 description 2
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/26—Visual data mining; Browsing structured data
Abstract
The invention belongs to computer data processing technology fields, specifically, it is a kind of intelligent chart recommender system and method, module is explored including data field data type, data field type mode combinations module, data content Exploration on Characteristics module, data field type Pattern Matching Module, data content feature recognition module, intelligent chart recommending module, wherein, data field data type explores the Format Type that module is used to explore each field of data-oriented, data field mode combinations module is used to the Format Type of field being combined into a mode to be matched, data content Exploration on Characteristics module is used to explore the content characteristic of data-oriented, data field pattern match mode is for matching the subtype for being suitable for field schema, data content feature recognition module is suitable for the subtype of data content feature for identification, Intelligent chart recommending module is used to recommend Visual Chart according to the result intelligent of matching and identification.
Description
Technical field
The invention belongs to computer data processing technology fields, specifically, being a kind of intelligent chart recommender system and side
Method is rapidly performed by the visualization of data for intelligence, and the technical capability of needs and behaviour when carrying out data visualization is greatly reduced
Make threshold.
Background technique
We are in big data era at present, and all trades and professions are all generating a large amount of data all the time, how from such as
Find that the law of value is the hang-up put in face of each practitioner in the data of this magnanimity, and traditional data visualization
Change when making displaying chart according to data, generally requires mapping personnel and be apparent from various types of charts for data itself
Requirement, while must also have the specialty background of certain data analysis, business intelligence, for example, mapping personnel need it is very clear
Chu Weidu and measurement are any meanings, what meaning comparison dimension and contrast number are, pie chart needs several dimension fields and several
A numeric field, line chart need several dimension fields and several numeric fields, the best illustrated effect requirements dimension values of pie chart
In how many within the scope of etc..These professional knowledge backgrounds considerably increase the difficulty of data analysis, improve data analysis
Threshold so that a large amount of data are unable to get effective analysis.
Summary of the invention
In order to solve the above-mentioned technical problem, the present invention discloses a kind of intelligent chart recommender system and method, user are several
Do not need to have any data analysis, business intelligence specialty background under the premise of, also will can fast and accurately possess
Data are effectively visualized, and user only needs to be desired in visual data entry system, and system can basis
The displaying for recommending Visual Chart progress data of the feature intelligent of the mode and data content itself of field in data, greatly
Ground reduces the difficulty of data analysis, reduces the threshold of data analysis, so that everybody can participate among data analysis.
The specific technical solution that the present invention uses is as follows:
A kind of intelligence chart recommender system, including data field data type explore module, data field type modal sets
Mold block, data content Exploration on Characteristics module, data field type Pattern Matching Module, data content feature recognition module, intelligence
Energy chart recommending module, wherein data field data type explores the format that module is used to explore each field of data-oriented
Type, data field mode combinations module is used to the Format Type of field being combined into a mode to be matched, in data
Hold the content characteristic that Exploration on Characteristics module is used to explore data-oriented, data field pattern match mode is suitable for word for matching
The subtype of stage mode, data content feature recognition module are suitable for the subtype of data content feature, intelligence for identification
Energy chart recommending module is used for the result intelligent recommendation Visual Chart according to matching with identification.
Invention further discloses a kind of intelligent chart recommended methods, comprising the following steps:
Step 1: given data DATA is explored in data field data type and passes through machine learning algorithm pair in module
The data type of each field is identified, obtains the data type of each field；
Step 2: it will wish visual field in data field type mode combinations module by the data of each field
Type is according to obtaining a mode pattern to be matched after mode combinations；
Step 3: data are carried out with the Exploration on Characteristics of data content itself by data content Exploration on Characteristics module, is obtained
Data characteristics model model；
Step 4: carrying out pattern match in all available charts for the mode pattern to be matched obtained before,
Obtain an available chart collection charts ' to be selected；
Step 5: the data characteristics model model obtained before is known in available chart collection charts ' to be selected
It does not match, each chart can obtain the score of a matching degree；
Step 6: after the score that chart is obtained is ranked up, the high chart of intelligent recommendation score carries out data visualization.
Beneficial effects of the present invention: a kind of intelligent chart recommender system and method for present disclosure shield data analysis
Technical term and requirement, breach user profession limitation.It only needs user to choose needs to do visual number
According to system can be visualized according to the field schema of data and the most suitable chart of recommendation of data content feature intelligent.
Detailed description of the invention
Fig. 1 is the embodiment of the present invention flow diagram.
Specific embodiment
In order to deepen the understanding of the present invention, the present invention is done below in conjunction with drawings and examples and is further retouched in detail
It states, the embodiment is only for explaining the present invention, does not constitute and limits to protection scope of the present invention.
A kind of intelligence chart recommender system, including data field data type explore module, data field type modal sets
Mold block, data content Exploration on Characteristics module, data field type Pattern Matching Module, data content feature recognition module, intelligence
Energy chart recommending module, wherein data field data type explores the format that module is used to explore each field of data-oriented
Type, data field mode combinations module is used to the Format Type of field being combined into a mode to be matched, in data
Hold the content characteristic that Exploration on Characteristics module is used to explore data-oriented, data field pattern match mode is suitable for word for matching
The subtype of stage mode, data content feature recognition module are suitable for the subtype of data content feature, intelligence for identification
Energy chart recommending module is used for the result intelligent recommendation Visual Chart according to matching with identification.
A kind of intelligence chart recommended method, comprising the following steps:
Step 1: given data DATA is explored in data field data type and passes through machine learning algorithm pair in module
The data type of each field is identified, obtains the data type of each field；
Step 2: it will wish visual field in data field type mode combinations module by the data of each field
Type is according to obtaining a mode pattern to be matched after mode combinations；
Step 3: data are carried out with the Exploration on Characteristics of data content itself by data content Exploration on Characteristics module, is obtained
Data characteristics model model；
Step 4: carrying out pattern match in all available charts for the mode pattern to be matched obtained before,
Obtain an available chart collection charts ' to be selected；
Step 5: the data characteristics model model obtained before is known in available chart collection charts ' to be selected
It does not match, each chart can obtain the score of a matching degree；
Step 6: after the score that chart is obtained is ranked up, the high chart of intelligent recommendation score carries out data visualization.
Embodiment: as shown in Figure 1, specific step is as follows for a kind of intelligence chart recommended method:
We possess the data set T to visual analyzing first, it is assumed that and one shares 5 fields in T, respectively C1,
C2, C3, C4 and C5, we need to carry out automatic identification, recognizer f to the data type of each field in T at this time
(T), i.e.,
Type (C1 ... C5)=f (T).
At this time we assume that the data type of 5 obtained fields is respectively as follows: character string, date, number, number, number,
That is data type sequence are as follows: String, Date, Number, Number, Number herein can letters for the ease of subsequent descriptions
It is written as SDNNN.
Then user needs that several fields is selected to carry out analysis displaying according to visualization, at this time we assume that user selects
These three fields of C1, C3 and C4 are visualized, then the data field mode P of list of fields to be presented at this time is just
It is character string, number, number.I.e.
P=SNN
Then we will carry out the matching of mode from the pattern base Ps of all existing charts, be the mould of existing chart below
The partial information of formula library Ps:
Is use pattern P=SNN matched in above-mentioned chart mode, and the mode that can be matched to is? N,? ...? N
And? N ... N, but according to data type definitely match, it can be found that mode Q=? N ... N will more meet mould
The matching degree of formula P, so at this time should be using mode Q as the match pattern most met, the subtype that filters out at this time are as follows: basis
Broken line, broken line area stack area, basic column, stack column, scatter plot and radar map.I.e.
Ps '={ basic broken line, broken line area stack area, basic column, stack column, radar map }
Then we carry out analysis modeling to actual data content feature according to selected field C1, C3, C4, in order to retouch
State it is simple, will be from result data item number, digital magnitude, result data three features of whether strong succession are modeled.Assuming that
It is 10 that we, which analyze after data content feature that discovery data content feature M is result data item number, and the magnitude of field C3 is thousand,
The magnitude of field C4 is also thousand, and result data does not have strong succession, i.e.,
M={ item number 10；Field magnitude 1 is thousand, and field magnitude 2 is thousand；Result data is without strong succession }
Then we will carry out the matching of feature from Ps ', be the characteristic information in Ps ' chart library below:
Identification matching is carried out into upper table according to current data characteristics M, available following result table:
It can be found that wherein the score of basic histogram and stacking histogram is essentially identical, highest arranged side by side, so system this
When automatic will recommend basic histogram and stack the visualization that histogram carries out data.
Since the subtype during actual visualization is much larger than the type in above table, so it is directed to each
Data field type mode and data content characteristic model system can intelligence the most suitable chart of matching, without user
Have very professional data analysis background knowledge, greatly improve the efficiency of data analysis visualization, reduces data analysis
Visually use threshold.
Basic principles and main features and advantage of the invention have been shown and described above.The technical staff of the industry should
Understand, the present invention is not limited to the above embodiments, and the above embodiments and description only describe originals of the invention
Reason, without departing from the spirit and scope of the present invention, various changes and improvements may be made to the invention, these changes and improvements
It all fall within the protetion scope of the claimed invention.The claimed scope of the invention is by appended claims and its equivalent circle
It is fixed.
Claims (2)
1. a kind of intelligence chart recommender system, which is characterized in that explore module, data field class including data field data type
Pattern formula composite module, data content Exploration on Characteristics module, data field type Pattern Matching Module, the identification of data content feature
Module, intelligent chart recommending module, wherein the data field data type explores module for exploring each of data-oriented
The Format Type of field, the data field mode combinations module be used for by the Format Type of field be combined into one it is to be matched
Mode, the data content Exploration on Characteristics module is used to explore the content characteristic of data-oriented, the data field mode
It is used to match the subtype for being suitable for field schema with mode, the data content feature recognition module is suitable for for identification
The subtype of data content feature, the intelligence chart recommending module is used for can according to the result intelligent recommendation of matching and identification
Depending on changing chart.
2. a kind of intelligence chart recommended method, which comprises the following steps:
Step 1: given data DATA is explored in module through machine learning algorithm in data field data type to each
The data type of field is identified, obtains the data type of each field；
Step 2: it will wish visual field in data field type mode combinations module by the data type of each field
According to obtaining a mode pattern to be matched after mode combinations；
Step 3: data are carried out with the Exploration on Characteristics of data content itself by data content Exploration on Characteristics module, obtains data
Characteristic model model；
Step 4: the mode pattern to be matched obtained before is subjected to pattern match in all available charts, is obtained
One available chart collection charts ' to be selected；
Step 5: the data characteristics model model obtained before is carried out to identification in available chart collection charts ' to be selected
Match, each chart can obtain the score of a matching degree；
Step 6: after the score that chart is obtained is ranked up, the high chart of intelligent recommendation score carries out data visualization.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111881311A (en) * | 2020-08-06 | 2020-11-03 | 泰山信息科技有限公司 | Intelligent chart type recommendation method, device, equipment and storage medium |
| CN112256789A (en) * | 2020-10-19 | 2021-01-22 | 杭州比智科技有限公司 | Intelligent visual data analysis method and device |
| CN113986904A (en) * | 2021-11-08 | 2022-01-28 | 深圳赛诺百应科技有限公司 | Business intelligent data analysis system based on Internet |
| WO2023142482A1 (en) * | 2022-01-26 | 2023-08-03 | 华为云计算技术有限公司 | Chart component selection method and data visualization device |
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| WO2023142482A1 (en) * | 2022-01-26 | 2023-08-03 | 华为云计算技术有限公司 | Chart component selection method and data visualization device |
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