CN107909389B - Data exploration and consultation method and system, electronic equipment and storage medium - Google Patents
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Abstract
The invention discloses a data exploration and consultation method, which comprises the following steps: acquiring data input by a user, wherein the data comprises data content and exploration variables; acquiring a pre-storage flow selected by a user, and exploring data through the pre-storage flow; obtaining a question consulted by a user; matching the experts of the pre-stored flow to generate an expert list; the experts comprise a creator, a maintainer and a historical user of a pre-stored flow; acquiring a first expert selected by a user from an expert list, and pushing data, a pre-storage process and a question to the first expert; acquiring the reply content of the first expert, and pushing the reply content to the user; the invention also discloses a data exploration and consultation system, electronic equipment and a computer readable storage medium; the invention improves the quality and efficiency of the consultation service, reduces the risk of invalid consultation and makes the consultation service more professional by sharing standard content and automatically matching experts.
Description
Technical Field
The invention relates to the technical field of electronic information, in particular to a data exploration and consultation method, a data exploration and consultation system, electronic equipment and a storage medium.
Background
With the continuous generation of massive data, scientific research is shifting to data-intensive, and the consultations related to data exploration are increasing. However, in the process of consulting services in data exploration, the effective execution of the consulting services is severely restricted by the problems of lack of sharing standards, specifications and cooperation rules, consulting service scheduling and the like. These defects lead to the situations that the range of the consultative problems is not clearly abstracted by the user, the error exists when the user expresses the consultative problems, the deviation exists when the first expert understands the real consultative problems of the user, and the like, so that the quality and the efficiency of the consultative service are low, and the effect of the consultative service generally needs to be developed after a long time.
Disclosure of Invention
In order to overcome the defects of the prior art, one of the purposes of the invention is to provide a data exploration consultation method, which improves the quality and efficiency of consultation service, reduces the risk of invalid consultation and makes the consultation service more professional by sharing standard content and automatically matching experts.
The second purpose of the invention is to provide a data exploration consultation system, which improves the quality and efficiency of the consultation service, reduces the risk of invalid consultation and makes the consultation service more professional by sharing standard content and automatically matching experts.
The invention also aims to provide the electronic equipment, which improves the quality and efficiency of the consultation service, reduces the risk of invalid consultation and makes the consultation service more professional by sharing standard content and automatically matching experts.
The fourth object of the present invention is to provide a computer-readable storage medium, which improves the quality and efficiency of the counseling service, reduces the risk of invalid counseling, and makes the counseling service more professional by sharing standard contents and automatically matching experts.
One of the purposes of the invention is realized by adopting the following technical scheme:
a data exploration consultation method comprises the following steps:
acquiring data, wherein the data input by a user is acquired, and the data comprises data content and exploration variables;
acquiring a pre-storage flow, acquiring the pre-storage flow selected by a user, and performing data exploration on the data through the pre-storage flow;
obtaining a question, and obtaining a question consulted by a user;
matching experts, matching the experts of the pre-stored flow, and generating an expert list; the experts comprise creators, maintainers and historical users of the pre-stored flow;
acquiring an expert, acquiring a first expert selected by the user from the expert list, and pushing the data, the pre-storage process and the problem to the first expert;
and replying the question, acquiring the reply content of the first expert, and pushing the reply content to the user.
Further, the method also comprises the following steps:
and evaluating the reply, wherein the evaluation of the reply content by the user is obtained, and the evaluation comprises evaluation level and evaluation content.
Further, the data exploration comprises the following steps:
generating a program code, acquiring the operation, method and process program code of a pre-stored process selected by a user, and generating and storing an output program code;
running the program code, running the output program code, and obtaining and storing a running result;
and displaying a result, namely displaying the pre-stored flow, the output program code and the operation result.
Further, the step matching expert specifically comprises: matching the experts of the pre-stored flow to generate an expert list; the experts comprise creators, maintainers and historical users of the pre-stored flow, and the expert list is sorted according to the selected times, consulted times and evaluations of the experts on the pre-stored flow.
Further, the pre-storing process includes nodes, paths, methods and process program codes, the nodes and the paths constitute operations, the method includes a pre-storing method, the pre-storing method includes a statistical method and a method program code, the process program code is used for executing a pre-storing process, and the method program code is used for executing a pre-storing method.
Further, the flow program code calls the method program code to generate an output program code.
The second purpose of the invention is realized by adopting the following technical scheme:
a data exploration and consultation system comprises a pre-storage flow module, a data acquisition module, a flow selection module, a problem acquisition module, an expert matching module, an expert selection module, a reply module and an evaluation module; the flow selection module is connected with the pre-storage flow module, the data acquisition module and the question acquisition module, the question acquisition module is connected with the expert matching module, the expert matching module is connected with the expert selection module, the expert selection module is connected with the reply module, and the reply module is connected with the evaluation module;
the system comprises a data acquisition module, a question acquisition module, a flow selection module, an expert matching module and an evaluation module, wherein the data acquisition module acquires data input by a user, the question acquisition module acquires questions consulted by the user, the flow selection module acquires pre-stored flows in the pre-stored flow module according to the data, the expert matching module matches experts of the pre-stored flows according to the questions to generate an expert list, the expert selection module is used for the user to select a first expert, the reply module is used for the first expert to reply the questions, and the evaluation module is used for the user to evaluate the first expert.
Further, the system also comprises a pre-storing method module, a program code generating module, a program code running module and a result displaying module; the pre-storing method module is connected with the pre-storing flow module, the program code generating module is connected with the flow selecting module and the program code running module, and the program code running module is connected with the result display module;
the pre-storing flow module obtains a pre-storing method and a pre-storing method program code in the pre-storing method module according to the pre-storing flow, the program code generating module generates and stores an output program code, the program code running module runs the output program code to obtain and store a running result, and the result displaying module displays the pre-storing flow, the output program code and the running result.
The third purpose of the invention is realized by adopting the following technical scheme:
an electronic device, comprising: a processor;
a memory; and a program, wherein the program is stored in the memory and configured to be executed by the processor, the program comprising instructions for performing one of the data exploration consultation methods described above.
The fourth purpose of the invention is realized by adopting the following technical scheme:
a computer-readable storage medium having stored thereon a computer program for execution by a processor of a method of data exploration consultation as described above.
Compared with the prior art, the invention has the beneficial effects that:
a data exploration consultation method also relates to a data exploration consultation system, an electronic device and a computer readable storage medium; by sharing standard content and automatically matching experts, a sharing standard, a standard, an assistance rule and a consultation service scheduling method are established, so that the consultation service provided by the invention is more comprehensive, faster in acquisition speed and better in timeliness, and the obtained result is more accurate and reliable, thereby improving the quality and efficiency of the consultation service, reducing the risk of invalid consultation and making the consultation service more professional.
The foregoing description is only an overview of the technical solutions of the present invention, and in order to make the technical solutions of the present invention more clearly understood and to implement them in accordance with the contents of the description, the following detailed description is given with reference to the preferred embodiments of the present invention and the accompanying drawings. The detailed description of the present invention is given in detail by the following examples and the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
FIG. 1 is a main flow chart of a data exploration consultation method of the present invention;
FIG. 2 is a flowchart illustrating a data exploration and consultation method according to an embodiment of the present invention;
FIG. 3 is a flow chart of the average comparison process of two samples according to the present invention;
FIG. 4 is a system block diagram of a data exploration consulting system of the present invention.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and the detailed description, and it should be noted that any combination of the embodiments or technical features described below can be used to form a new embodiment without conflict.
A data exploration consultation method, as shown in fig. 1, comprising the following steps:
acquiring data, wherein the data input by a user is acquired, and the data comprises data content and exploration variables;
acquiring a pre-storage flow, acquiring the pre-storage flow selected by a user, and performing data exploration on data through the pre-storage flow;
obtaining a question, and obtaining a question consulted by a user;
matching experts, matching experts of a pre-stored flow, and generating an expert list; the experts comprise a creator, a maintainer and a historical user of a pre-stored flow;
acquiring experts, acquiring a first expert selected by a user from an expert list, and pushing data, a pre-storage process and a problem to the first expert;
and replying the question, acquiring the reply content of the first expert, and pushing the reply content to the user.
Wherein, the step matching expert specifically comprises the following steps: matching the experts of the pre-stored flow to generate an expert list; the experts comprise creators, maintainers and historical users of the pre-stored flow, and the expert list is sorted according to the selected times, consulted times and evaluation of the experts on the pre-stored flow; and providing an interface for the user to automatically select sorting options in the sorting, wherein the sorting options comprise sorting according to the selected times, sorting according to the consulted times, sorting according to evaluation and the like.
Wherein, the reply content comprises image and text, voice, video, telephone, off-line and third-party communication.
For the method, the user can better and faster select the expert to be consulted by sharing the standard specification content and automatically matching the expert, the expert can better and faster understand the consulted problem and store the consulted records, so that the sharing standard, the specification, the assistance rule and the consulted service scheduling method are established, the consulted service provided by the invention is more comprehensive, the acquisition speed is higher, the timeliness is better, the obtained result is more accurate and reliable, the quality and the efficiency of the consulted service are improved, the risk of invalid consultation is reduced, and the consulted service is more professional.
As shown in fig. 2, the method further comprises the following steps:
and evaluating the reply, namely acquiring the evaluation of the reply content by the user, wherein the evaluation comprises evaluation level and evaluation content.
And evaluating the expert by the user, wherein the evaluation level refers to the overall satisfaction degree of the reply content, the evaluation content refers to the specific content of the evaluation, and the evaluation is stored and displayed on the system and is used as a reference standard of other users.
As shown in fig. 2, the data exploration includes the following steps:
generating a program code, acquiring the operation, method and process program code of a pre-stored process selected by a user, and generating and storing an output program code;
running the program code, running the output program code, and obtaining and storing a running result;
and displaying a result, namely displaying a pre-stored flow, outputting a program code and an operation result.
The method comprises a pre-storing method, wherein the pre-storing method comprises a statistical method and a method program code, the flow program code is used for executing the pre-storing flow, and the method program code is used for executing the pre-storing method.
The flow program code calls the method program code to generate an output program code.
For the method, the first embodiment of the invention is used for research data exploration and consultation, and in daily scientific research work, researchers often need to find relevant professionals for consultation about problems in the data exploration process; the following steps are performed when researching hypertension scientific research data:
acquiring data, acquiring systolic pressure and diastolic pressure data contents and exploration variables of a hypertension patient group and a normal control group input by a user;
acquiring a pre-storage process, acquiring an average number comparison process of two samples selected by a user, and performing data exploration on data through the average number comparison process of the two samples;
obtaining a question, obtaining a question consulted by a user, such as a question consulted by a user: why did the mean comparison of the two samples yield the result of the Wilcoxon rank-sum test, not the result of the t test? "
Matching experts, namely matching experts in the average number comparison process of the two samples to generate an expert list; the experts comprise a creator and a maintainer of the average number comparison process of the two samples and a user using the average number comparison process of the two samples in the past;
acquiring experts, acquiring a first expert selected by a user from an expert list, and pushing data, a pre-storage process and a problem to the first expert;
and replying the question, acquiring the reply content of the first expert, pushing the reply content to the user, and replying the question by the first expert in a picture-text mode: "because three preconditions need to be satisfied using t-test, when data does not conform to normal distribution, t-test cannot be used, and Wilcoxon rank-sum test, which has no specific requirement on data distribution, is used. "
Meanwhile, for the embodiment, the method further comprises the following steps:
and evaluating the reply, wherein the evaluation of the reply content by the user is obtained, the evaluation comprises an evaluation grade and an evaluation content, for example, the evaluation grade of the user to experts is 'good', and the evaluation content is as follows: "answer professional, simple and complete. "
The specific steps of data exploration through the two-sample average comparison process are as follows:
generating a program code, acquiring the operation, the method and the process program code of the mean comparison process of the two samples, and generating and storing a corresponding output program code;
and running the program code, and running the output program code of the mean comparison process of the two samples to obtain and store a corresponding running result.
And storing the result, and displaying the average number comparison process of the two samples, the corresponding output program code and the corresponding operation result.
When exploring hypertension scientific research data, the specific steps of the mean comparison process of the two samples are shown in fig. 3, and in the whole process, for the mean comparison process of the two samples, the systolic pressure data and the diastolic pressure data of a hypertension patient group and a normal control group use t test when the data accord with normal distribution and variance homogeneity; when the normal distribution is met but the variance homogeneity is not met, a Welch approximate t test is used; when not normally distributed, Wilcoxon rank-sum test is used.
When a user conducts data exploration, a plurality of processes which need to be conducted for hypertension scientific research data exploration are needed, for example, a two-sample rate comparison process, a two-sample survival time comparison process and the like.
The second embodiment of the invention is used for health data exploration, and on the basis of the first embodiment, the processes, methods and problems related to hypertension scientific research data exploration in the first embodiment are changed into the corresponding processes, methods and problems related to health data exploration, so that the users can conduct exploration research on the health data.
The third embodiment of the invention is used for educational data exploration, and on the basis of the first embodiment, the processes, methods, problems and the like of the hypertension scientific research data exploration in the first embodiment are changed into the corresponding processes, methods and problems of the educational data exploration, so that users can conduct exploration research on the educational data.
A data exploration and consultation system is shown in FIG. 4 and comprises a pre-storage flow module, a data acquisition module, a flow selection module, a problem acquisition module, an expert matching module, an expert selection module, a reply module and an evaluation module; the flow selection module is connected with the pre-storage flow module, the data acquisition module and the problem acquisition module, the problem acquisition module is connected with the expert matching module, the expert matching module is connected with the expert selection module, the expert selection module is connected with the reply module, and the reply module is connected with the evaluation module.
The system comprises a data acquisition module, a problem acquisition module, a flow selection module, an expert matching module, a reply module and an evaluation module, wherein the data acquisition module acquires data input by a user, the problem acquisition module acquires a problem consulted by the user, the flow selection module acquires a pre-stored flow in a pre-stored flow module according to the data, the expert matching module matches an expert of the pre-stored flow according to the problem to generate an expert list, the expert selection module is used for the user to select a first expert, the reply module is used for the first expert to reply the problem.
Meanwhile, for the present embodiment, the data exploration system further includes a pre-storing method module, a program code generating module, a program code operating module and a result displaying module, where the pre-storing method module is connected to the pre-storing flow module, the flow selecting module is connected to the program code generating module, the program code generating module is connected to the program code operating module, the program code operating module is connected to the result displaying module, the pre-storing method and the program code in the pre-storing method module are obtained through the pre-storing flow module, the output program code is generated and stored through the program code generating module, the output program code is operated through the program code operating module to obtain and store the operating result, and the pre-storing flow, the output program code and the operating result are displayed through the result displaying module, so as to perform data exploration on the data.
An electronic device, comprising: a processor; a memory; and a program, wherein the program is stored in the memory and configured to be executed by the processor, the program comprising instructions for performing one of the data exploration consulting methods described above; a computer-readable storage medium having stored thereon a computer program for execution by a processor of a method of data exploration consultation as described above.
A data exploration consultation method also relates to a data exploration consultation system, an electronic device and a computer readable storage medium; by sharing standard content and automatically matching experts, a sharing standard, a standard, an assistance rule and a consultation service scheduling method are established, so that the consultation service provided by the invention is more comprehensive, faster in acquisition speed and better in timeliness, and the obtained result is more accurate and reliable, thereby improving the quality and efficiency of the consultation service, reducing the risk of invalid consultation and making the consultation service more professional.
The foregoing is merely a preferred embodiment of the invention and is not intended to limit the invention in any manner; those skilled in the art can readily practice the invention as shown and described in the drawings and detailed description herein; however, those skilled in the art should appreciate that they can readily use the disclosed conception and specific embodiments as a basis for designing or modifying other structures for carrying out the same purposes of the present invention without departing from the scope of the invention as defined by the appended claims; meanwhile, any changes, modifications, and evolutions of the equivalent changes of the above embodiments according to the actual techniques of the present invention are still within the protection scope of the technical solution of the present invention.
Claims (7)
1. A data exploration consultation method is characterized by comprising the following steps:
acquiring data, wherein the data input by a user is acquired, and the data comprises data content and exploration variables;
acquiring a pre-storage flow, acquiring the pre-storage flow selected by a user, and performing data exploration on the data through the pre-storage flow;
obtaining a question, and obtaining a question consulted by a user;
matching experts, matching the experts of the pre-stored flow, and generating an expert list; the experts comprise creators, maintainers and historical users of the pre-stored flow;
acquiring an expert, acquiring a first expert selected by the user from the expert list, and pushing the data, the pre-storage process and the problem to the first expert;
replying the question, acquiring the reply content of the first expert, and pushing the reply content to the user;
the pre-storing process comprises nodes, paths, methods and process program codes, wherein the nodes and the paths form operations, the method comprises a pre-storing method, the pre-storing method comprises a statistical method and a method program code, the process program code is used for executing the pre-storing process, and the method program code is used for executing the pre-storing method;
the data exploration comprises the following steps:
generating a program code, acquiring the operation, method and process program code of a pre-stored process selected by a user, and generating and storing an output program code;
running the program code, running the output program code, and obtaining and storing a running result;
and displaying a result, namely displaying the pre-stored flow, the output program code and the operation result.
2. The method of claim 1, further comprising the steps of:
and evaluating the reply, wherein the evaluation of the reply content by the user is obtained, and the evaluation comprises evaluation level and evaluation content.
3. The method as claimed in claim 1, wherein the expert list in the specific process of matching experts is sorted according to the number of times the expert has selected, consulted and evaluated in the pre-storing process.
4. The method of claim 1, wherein: and the flow program code calls the method program code to generate an output program code.
5. A data exploration advisory system, characterized by: the system comprises a pre-storage flow module, a data acquisition module, a flow selection module, a problem acquisition module, an expert matching module, an expert selection module, a reply module and an evaluation module; the flow selection module is connected with the pre-storage flow module, the data acquisition module and the question acquisition module, the question acquisition module is connected with the expert matching module, the expert matching module is connected with the expert selection module, the expert selection module is connected with the reply module, and the reply module is connected with the evaluation module;
the system comprises a data acquisition module, a question acquisition module, a flow selection module, an expert matching module and an evaluation module, wherein the data acquisition module acquires data input by a user, the question acquisition module acquires questions consulted by the user, the flow selection module acquires pre-stored flows in the pre-stored flow module according to the data, the expert matching module matches experts of the pre-stored flows according to the questions to generate an expert list, the expert selection module is used for the user to select a first expert, the reply module is used for the first expert to reply the questions, and the evaluation module is used for the user to evaluate the first expert;
the system also comprises a pre-storage method module, a program code generation module, a program code operation module and a result display module; the pre-storing method module is connected with the pre-storing flow module, the program code generating module is connected with the flow selecting module and the program code running module, and the program code running module is connected with the result display module;
the pre-storing flow module obtains a pre-storing method and a pre-storing method program code in the pre-storing method module according to the pre-storing flow, the program code generating module generates and stores an output program code, the program code running module runs the output program code to obtain and store a running result, and the result display module displays the pre-storing flow, the output program code and the running result.
6. An electronic device, characterized by comprising: a processor;
a memory; and a program, wherein the program is stored in the memory and configured to be executed by the processor, the program comprising instructions for carrying out the method of any one of claims 1-4.
7. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program is executed by a processor for performing the method according to any of claims 1-4.
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| PCT/CN2018/102990 WO2019085620A1 (en) | 2017-10-31 | 2018-08-29 | Data exploration consulting method and system, electronic device, and storage medium |
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| CN106295147A (en) * | 2016-07-29 | 2017-01-04 | 广州比特软件科技有限公司 | The medical expert's personalized recommendation method solved based on big data and system |
| CN106708924A (en) * | 2016-11-09 | 2017-05-24 | 上海知邦信息科技有限公司 | Consultation system and consultation method |
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| CN103324754A (en) * | 2013-07-08 | 2013-09-25 | 贵州森威商贸有限公司 | Self-service real-time health condition response system |
| CN103401873A (en) * | 2013-08-07 | 2013-11-20 | 上海法度网络科技有限公司 | System and method for realizing stream media expert service based on network |
| CN106778083A (en) * | 2016-11-28 | 2017-05-31 | 墨宝股份有限公司 | A kind of method and device for automatically generating genetic test report |
| CN107909389B (en) * | 2017-10-31 | 2020-03-17 | 深圳市宇数科技有限公司 | Data exploration and consultation method and system, electronic equipment and storage medium |
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| CN106295147A (en) * | 2016-07-29 | 2017-01-04 | 广州比特软件科技有限公司 | The medical expert's personalized recommendation method solved based on big data and system |
| CN106708924A (en) * | 2016-11-09 | 2017-05-24 | 上海知邦信息科技有限公司 | Consultation system and consultation method |
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