CN107632976B - Method and device for generating context map of experimental circuit problem - Google Patents
Method and device for generating context map of experimental circuit problem Download PDFInfo
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Abstract
The invention discloses a method and a device for generating a context map of an experimental circuit problem, wherein the method comprises the following steps: firstly, presetting the category number and name of a basic experimental circuit according to the equipment condition, and giving 2-3 research problems surrounding a certain basic circuit in a case form; then, extracting keywords, filtering and controlling the scale in the summary text information description of the basic circuit by an experimenter, and finally obtaining important characteristics for describing the problem; finally, clustering, partitioning and layering are carried out on the characteristic quantities to form a venation map describing basic circuit problems; by repeating the steps, the problem which can be researched by the experimental circuit can be classified and layered in advance, a problem-oriented dynamic experimental course system is realized, the workload of an experimental teacher for guiding students to carry out problem analysis is reduced, and the independent practice analysis capability of the students is improved.
Description
Technical Field
The invention relates to the technical field of experimental data management and application, in particular to a method and a device for generating a context diagram of an experimental circuit problem.
Background
In the aspect of experimental teaching, aiming at the design of innovative and exploratory experimental projects, the experiment contents combining new technology and new citation are redesigned in all colleges and universities, and experimental equipment manufacturers develop more novel experimental platforms. These items all suffer from several problems: 1. the method for reflecting on the original framework and replanning the display of the experiment content is not adopted, a brand new experiment content is conceived, the scale of the experiment content is enlarged, and the problem solving capability of students cannot be further improved. 2. Some teachers in colleges and universities unite the technical staff to reconstruct the course content according to the project requirements, but students cannot understand the actual problems of the project. While traditional problems such as 3-5 students sharing one experiment table, some people do not operate the experiment table; the experiment enthusiasm of students is not high, and the experiment is completed passively; the experimental report is basically the transcription of the experimental steps, consumes a great deal of energy of teachers and students, does not save value and the like, and the defects of the existing problems are not solved.
Disclosure of Invention
The invention aims to solve the defects in the prior art and provides a method and a device for generating a context map of an experimental circuit problem.
According to the disclosed embodiment, the first aspect of the invention discloses a method for generating an experimental circuit problem context map, which comprises the following steps:
s1, acquiring text information which respectively describes different experiment basic circuits;
s2, a keyword information extraction step, namely extracting keyword information from the text information of each experimental circuit and filtering the keyword information;
s3, a step of digital processing, namely, carrying out digital processing on the filtered keyword information to obtain a feature vector for describing a circuit problem;
s4, a problem clustering step, namely clustering problems according to the characteristic vectors and controlling the scale of the problems;
and S5, generating a problem venation map with multiple layers surrounding the basic circuit according to the problem clustering result.
Further, the text information acquisition step includes:
a traversal substep, extracting text information in the abnormal data analysis summary of all the student historical experiment reports;
the association substep is used for extracting the name of the experiment basic circuit and the experiment abnormal information;
and a description substep, combining and describing the name of the experimental basic circuit and the text information and the experimental abnormal information in the abnormal data analysis summary.
Further, the keyword information extraction step includes:
a word extraction substep, which is used for resolving as many key words as possible from the experimental abnormal information;
and a comparison substep, comparing the correlation among the keywords to form mutually independent keywords.
Further, the digital processing step comprises:
a word frequency calculating substep, calculating the word frequency of each keyword in the total number of samples, wherein the word frequency represents the frequency of the keywords in the text information;
the method comprises the following steps of (1) calculating a reverse question frequency of each keyword, wherein the reverse question frequency represents the importance degree of the keyword;
a product calculation substep, calculating the product of the word frequency and the inverse problem frequency of each keyword;
and a vector generation substep, which is used for creating a characteristic vector representing the importance degree of the keywords according to the product of the word frequency and the reverse question frequency of each keyword.
Further, the problem clustering step includes:
a preset value substep, setting and storing circuit types and problem scale parameters, and giving association rules of different levels of problems in a case mode as initial values;
a sub-step of dividing each keyword surrounding a certain circuit in the plurality of pieces of sampling sample information into the same region;
a calculating substep, calculating the minimum distance between any two regions to obtain two regions with the minimum distance between the regions;
a region merging sub-step of merging two regions having the smallest distance between the regions into a new region;
wherein the calculating substep and the region merging substep are alternately performed until the number of remaining regions is a preset value.
Further, the step of generating the context map comprises:
classifying, namely, classifying the keyword area information into different types of experimental circuits;
a layering substep of categorizing the keyword regions into different layers surrounding each type of experimental circuit;
and a drawing substep, drawing the tree structure of the keywords and the experimental circuit according to the classification and layering results.
Further, the circuit type is an experimental circuit type preset according to the principle that components are minimum and a topological structure is unique.
Further, the problem context map is a hierarchical connection between the basic circuit structure and the word description information, the problem set and the problem.
Further, the problem context map is generated after the complete data acquisition is completed, and the structure of the map is dynamically changed.
According to the disclosed embodiments, a second aspect of the present invention discloses an apparatus for generating an experimental circuit problem context map, the apparatus comprising:
the acquisition module is used for acquiring text information which respectively describes different experimental basic circuits;
the extraction module is used for extracting keyword information from the text information of each experimental circuit and filtering the keyword information;
the processing module is used for carrying out digital processing on the filtered keyword information to obtain a characteristic vector for describing a circuit problem;
the clustering module is used for clustering the problems according to the characteristic vectors and controlling the scale of the problems;
and the generating module is used for generating a multi-level problem venation map surrounding the basic circuit according to the result of the problem clustering.
Further, the acquisition module comprises:
the traversal submodule is used for extracting text information in the abnormal data analysis summary of all the student historical experiment reports;
the correlation submodule is used for extracting the name of the experiment basic circuit and the experiment abnormal information;
and the description submodule is used for carrying out combined description on the experimental basic circuit name and the text information and the experimental abnormal information in the abnormal data analysis summary.
The extraction module comprises:
the word extraction submodule is used for decomposing as many key words as possible from the experimental abnormal information;
and the comparison submodule is used for comparing the correlation among the keywords to form mutually independent keywords.
The processing module comprises:
the word frequency calculation submodule is used for calculating the word frequency of each keyword in the total number of the samples;
the inverse frequency calculation submodule is used for calculating the inverse problem frequency of each keyword;
a product calculating submodule for calculating the product of the word frequency and the inverse problem frequency of each keyword;
and the vector generation submodule is used for creating a characteristic vector representing the importance degree of the keywords according to the product of the word frequency and the reverse question frequency of each keyword.
The clustering module comprises:
the preset value submodule is used for setting and storing the circuit type and the problem scale parameters, and giving association rules of problems in different levels in a case mode to serve as initial values;
the sub-module of the subregion, is used for classifying every key word around a certain circuit in the said multiple sampled sample information as the identity district;
the calculation submodule is used for calculating the minimum distance between any two regions to obtain two regions with the minimum distance between the regions;
a region merging submodule for merging two regions having the smallest distance between the regions into a new region;
and the calculation submodule and the area merging submodule are alternately executed until the number of the remaining areas is a preset value.
The generation module comprises:
the classification submodule is used for classifying the keyword area information into different types of experimental circuits;
the hierarchical submodule is used for arranging the keyword areas to different levels surrounding each type of experimental circuit;
and the drawing submodule is used for drawing the keywords and the experimental circuit into a tree structure according to the classification and layering results.
Compared with the prior art, the invention has the following advantages and effects:
the invention shows a comprehensive problem set which is not excessive when a specific circuit experiment is implemented by generating a context map, and prompts students to enter an experiment scene which takes specific problems as entry points and aims at solving the problems. The relation between the problem layers reflects the direction of deep research needed for solving the problems, and is beneficial to observing and guiding the development of innovative thinking. Although an experimenter conducts an experimental project at the same time, different behavior patterns are caused due to the difference of attention points, and a meaningful thinking collision atmosphere is created.
Drawings
FIG. 1 is a flow chart of a method for generating an experimental circuit problem context according to the present disclosure;
FIG. 2 is a context diagram of a method for generating a context diagram of an experimental circuit problem surrounding a base circuit according to the present disclosure;
FIG. 3 is a flow chart of an application of the present invention;
FIG. 4 is a block diagram of an implementation function of an apparatus for generating an experimental circuit problem context according to the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, 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.
Example one
The embodiment of the invention discloses a design method for transition from traditional classical principle demonstration experiment contents to culture innovation capability experiment contents, and an experiment teacher can help students reconstruct experiments through a venation map. Different subjects are designed in the teaching content in each experiment, so that students can understand real problems, real scenes in application are reconstructed, and the capabilities of finding and solving the problems are formed. The method is mainly characterized in that an experiment content system is reconstructed on the basis of original equipment and original advantages, concrete experiment contents are deeply displayed, students are helped to put forward new problems in application, and the optimal scheme of problem solution is approached in a round-by-round mode. So that the whole experimental process can be refined as follows: the method is characterized in that a conventional experiment, namely the problem is found, the existing solution is practiced, the problem is found, the new solution is proposed, mathematical and chemical summarization is carried out, and the practical experience of an experimenter is improved.
A method of generating an experimental circuit problem context graph, the method comprising:
s1, acquiring text information which respectively describes different experiment basic circuits; the collected data is real record and feedback information which occurs in the last half year and exists in a large number of experimental participants, and the data comprises all preset experimental types and problem descriptions.
Wherein the step comprises the following substeps:
a traversal substep, extracting text information in the abnormal data analysis summary of all the student historical experiment reports;
the association substep is used for extracting the name of the experiment basic circuit and the experiment abnormal information;
and a description substep, combining and describing the name of the experimental basic circuit and the text information and the experimental abnormal information in the abnormal data analysis summary.
S2, a keyword information extraction step, namely extracting keyword information from the text information of each experimental circuit and filtering the keyword information;
wherein the step comprises the following substeps:
a word extraction substep, which is used for resolving as many key words as possible from the experimental abnormal information;
and a comparison substep, comparing the correlation among the keywords to form mutually independent keywords.
S3, a step of digital processing, namely, carrying out digital processing on the filtered keyword information to obtain a feature vector for describing a circuit problem;
wherein the step comprises the following substeps:
a word frequency calculating substep, calculating the word frequency of each keyword in the total number of samples, wherein the word frequency represents the frequency of the keywords in the text information;
the method comprises the following steps of (1) calculating a reverse question frequency of each keyword, wherein the reverse question frequency represents the importance degree of the keyword;
a product calculation substep, calculating the product of the word frequency and the inverse problem frequency of each keyword;
and a vector generation substep, which is used for creating a characteristic vector representing the importance degree of the keywords according to the product of the word frequency and the reverse question frequency of each keyword.
The feature vector of the above problem is composed of the product of the word frequency of the participle and the inverse document of the participle in the text information in the circuit description module.
S4, a problem clustering step, namely clustering problems according to the characteristic vectors and controlling the scale of the problems;
wherein the step comprises the following substeps:
a preset value substep, setting and storing circuit types and problem scale parameters, and giving association rules of different levels of problems in a case mode as initial values;
when the preset value or the rule of the problem description is changed, the graph structure is greatly changed.
In this embodiment, the type of the experimental circuit needs to be preset according to the principle that the number of components is minimum and the topology is unique.
A sub-step of dividing each keyword surrounding a certain circuit in the plurality of pieces of sampling sample information into the same region;
a calculating substep, calculating the minimum distance between any two regions to obtain two regions with the minimum distance between the regions;
a region merging sub-step of merging two regions having the smallest distance between the regions into a new region;
wherein the calculating substep and the region merging substep are alternately performed until the number of remaining regions is a preset value.
And S5, generating a problem venation map with multiple layers surrounding the basic circuit according to the problem clustering result.
Wherein the step comprises the following substeps:
classifying, namely, classifying the keyword area information into different types of experimental circuits;
a layering substep of categorizing the keyword regions into different layers surrounding each type of experimental circuit;
and a drawing substep, drawing the tree structure of the keywords and the experimental circuit according to the classification and layering results.
The problem context map is a hierarchical connection between the basic circuit structure and the word description information, the problem set and the problem.
Moreover, the problem context graph is generated after the complete data acquisition is completed, and the graph structure is dynamically changed.
Example two
Referring to fig. 1, the method for generating a context map of an experimental circuit problem according to the present invention includes the following steps:
and step T1, collecting the experimental report information of the students aiming at the experimental process data and analysis, and collecting the problems possibly occurring in different experimental circuits.
And step T2, classifying, filtering and analyzing the problems. Firstly, determining which experimental circuit the problem surrounds, then carrying out comparison analysis on the problem and the stored problems, removing repeated problems, carrying out pairwise comparison between the problems again, combining similar and similar problems, and finally forming a problem sample.
And step T3, the teacher summarizes at least two (generally 2-3) questions as primary classification initial values, and the primary classification initial values are recorded as question 1 and question 2.
And step T4, the teacher summarizes at least two questions as secondary classification initial values, and the secondary classification initial values are marked as question 1.1 and question 1.2.
Step T5, and similarly, the teacher summarizes at least two questions as initial values of the nth class, which are recorded as question 1.1.1 … 1 and question 1.1.1 … 2.
Step T6, the question sample refers to the generation rules of question 1 and question 2, and is arranged in a level of one level around a certain circuit.
And step T7, referring to the problem 1.1 and the generation rule of the problem 1.2, and classifying the problem sample into a secondary level surrounding a certain circuit.
Step T8, question sample refer to the generation rules of question 1.1.1 … 1, question 1.1.1 … 2, put in the N-level hierarchy around a certain circuit.
Step T9, based on the results, generates a problem context map around each experimental circuit.
Performing the above steps 2-9 after each acquisition of experimental data, step T10, may cause the problem to change from different hierarchical levels.
Referring to fig. 2, a teacher gives preset values of relevant questions as a guiding case by taking a teacher-student working line as a boundary. Namely, several common problems are proposed and marked as 1, 2 and 3, then analysis is carried out on the basis of the problem 1, and other problems needing to be solved firstly are refined and solved, and marked as 1.1, 1.2 and 1.3. In the form of case analysis, solutions to problems 1.1, 1.2, 1.3 are given, and finally problem 1 is solved. Similarly, question 2 is presented and part of question 2.1 that solves question 2 is presented, the other part being perfected by the student. Similarly, question 3 is presented, and the student completes the work to find out that this question is to be solved. Further, the questions are presented independently by the students. Finally, these problems are summed to form a context map for a certain underlying circuit. The venation diagram embodies the process of 'teacher guide and student thinking', and with the progress of experiments, the transition from 'teacher leading' to 'student leading' is realized.
Referring to fig. 3, the user applies the context map of the experimental problem in such a way that the experimenter determines the basic circuit to be researched and the problem of interest according to the context map structure in which only the preset value region is drawn, and then designs the experimental contents with the problem as an important point of interest, which may be modulation of parameters, fine adjustment of structure, adjustment of control parameters, and the like. The experimenter performs the experiment, records the data, and finally summarizes selected questions. It is possible to give a complete solution in the summary, it is also possible to give a partial solution to only one side of the problem or to give a newly discovered other problem. By collecting and collating the summary information from the round of experimenters, a context map can be generated around each of the base circuits. The context map changes with the continuous resolution of old problems and the continuous proposition of new problems.
EXAMPLE III
As shown in fig. 4, the generating device of the experimental circuit problem context diagram proposed by the present invention comprises:
the acquisition module is used for acquiring text information which respectively describes different experimental basic circuits;
the extraction module is used for extracting keyword information from the text information of each experimental circuit and filtering the keyword information;
the processing module is used for carrying out digital processing on the filtered keyword information to obtain a characteristic vector for describing a circuit problem;
the clustering module is used for clustering the problems according to the characteristic vectors and controlling the scale of the problems;
and the generation module generates a multi-level problem venation map surrounding the basic circuit according to the problem clustering result.
Wherein, the collection module includes:
the traversal submodule is used for extracting text information in the abnormal data analysis summary of all the student historical experiment reports;
the correlation submodule is used for extracting the name of the experiment basic circuit and the experiment abnormal information;
and the description submodule is used for combining and describing the experiment basic circuit name and the abnormal text information.
Wherein, the extraction module comprises:
the word extraction submodule is used for decomposing as many key words as possible from the experimental abnormal information;
and the comparison submodule is used for comparing the correlation among the keywords to form mutually independent keywords.
Wherein, the processing module comprises:
the word frequency calculation submodule is used for calculating the word frequency of each keyword in the total number of the samples;
the inverse frequency calculation submodule is used for calculating the inverse problem frequency of each keyword;
a product calculating submodule for calculating the product of the word frequency and the inverse problem frequency of each keyword;
and the vector generation submodule is used for creating a characteristic vector representing the importance degree of the keywords according to the product of the word frequency and the reverse question frequency of each keyword.
Wherein, the clustering module comprises:
the preset value submodule is used for setting and storing the circuit type and the problem scale parameters, and giving association rules of problems in different levels in a case mode to serve as initial values;
the sub-module of the subregion, is used for classifying every key word around a certain circuit in the said multiple sampled sample information as the identity district;
the calculation submodule is used for calculating the minimum distance between any two regions to obtain two regions with the minimum distance between the regions;
a region merging submodule for merging two regions having the smallest distance between the regions into a new region;
and the calculation submodule and the area merging submodule are alternately executed until the number of the remaining areas is a preset value.
Wherein, the generating module comprises:
the classification submodule is used for classifying the keyword area information into different types of experimental circuits;
the hierarchical submodule is used for arranging the keyword areas to different levels surrounding each type of experimental circuit;
and the drawing submodule is used for drawing the keywords and the experimental circuit into a tree structure according to the classification and layering results.
It should be noted that, in the above apparatus embodiment, each included module and sub-module are only divided according to functional logic, but are not limited to the above division as long as the corresponding function can be implemented; in addition, the specific names of the modules and sub-modules are only for the convenience of distinguishing from each other and are not used to limit the protection scope of the present invention.
The above embodiments are preferred embodiments of the present invention, but the present invention is not limited to the above embodiments, and any other changes, modifications, substitutions, combinations, and simplifications which do not depart from the spirit and principle of the present invention should be construed as equivalents thereof, and all such changes, modifications, substitutions, combinations, and simplifications are intended to be included in the scope of the present invention.
Claims (9)
1. A method for generating a context map of an experimental circuit problem, the method comprising:
s1, acquiring text information which respectively describes different experiment basic circuits;
s2, a keyword information extraction step, namely extracting keyword information from the text information of each experimental circuit and filtering the keyword information;
s3, a step of digital processing, namely, carrying out digital processing on the filtered keyword information to obtain a feature vector for describing a circuit problem;
s4, a problem clustering step, namely clustering problems according to the characteristic vectors and controlling the scale of the problems;
wherein, the problem clustering step comprises:
a preset value substep, setting and storing circuit types and problem scale parameters, and giving association rules of different levels of problems in a case mode as initial values;
a sub-step of dividing the key words surrounding a circuit in a plurality of sampling sample information into the same region;
a calculating substep, calculating the minimum distance between any two regions to obtain two regions with the minimum distance between the regions;
a region merging sub-step of merging two regions having the smallest distance between the regions into a new region;
the calculating substep and the region merging substep are alternately executed until the number of the remaining regions is a preset value;
and S5, generating a problem venation map with multiple layers surrounding the basic circuit according to the problem clustering result.
2. The method as claimed in claim 1, wherein the step of collecting the text information comprises:
a traversal substep, extracting text information in the abnormal data analysis summary of all the student historical experiment reports;
the association substep is used for extracting the name of the experiment basic circuit and the experiment abnormal information;
a description substep, which is to combine and describe the name of the basic circuit of the experiment and the text information and the abnormal information of the experiment in the abnormal data analysis summary;
the keyword information extraction step comprises the following steps:
a word extraction substep, which is used for resolving as many key words as possible from the experimental abnormal information;
and a comparison substep, comparing the correlation among the keywords to form mutually independent keywords.
3. The method as claimed in claim 1, wherein the step of digitizing comprises:
a word frequency calculating substep, calculating the word frequency of each keyword in the total number of samples, wherein the word frequency represents the frequency of the keywords in the text information;
the method comprises the following steps of (1) calculating a reverse question frequency of each keyword, wherein the reverse question frequency represents the importance degree of the keyword;
a product calculation substep, calculating the product of the word frequency and the inverse problem frequency of each keyword;
and a vector generation substep, which is used for creating a characteristic vector representing the importance degree of the keywords according to the product of the word frequency and the reverse question frequency of each keyword.
4. The method as claimed in claim 1, wherein the generating step comprises:
classifying, namely, classifying the keyword area information into different types of experimental circuits;
a layering substep of categorizing the keyword regions into different layers surrounding each type of experimental circuit;
and a drawing substep, drawing the tree structure of the keywords and the experimental circuit according to the classification and layering results.
5. The method as claimed in claim 1, wherein the circuit type is a preset experimental circuit type based on the principle of minimum components and unique topology.
6. The method as claimed in claim 1, wherein the problem context map is a hierarchical connection between the basic circuit structure and the textual description information, the problem sets, and the problems.
7. The method as claimed in claim 1, wherein the problem context map is generated after a complete data acquisition, and the structure of the map is dynamically changed.
8. An apparatus for generating a context map of an experimental circuit problem, the apparatus comprising:
the acquisition module is used for acquiring text information which respectively describes different experimental basic circuits;
the extraction module is used for extracting keyword information from the text information of each experimental circuit and filtering the keyword information;
the processing module is used for carrying out digital processing on the filtered keyword information to obtain a characteristic vector for describing a circuit problem;
the clustering module is used for clustering the problems according to the characteristic vectors and controlling the scale of the problems;
the generating module is used for generating a multi-level problem venation map surrounding the basic circuit according to the result of the problem clustering;
wherein, the clustering module comprises:
the preset value submodule is used for setting and storing the circuit type and the problem scale parameters, and giving association rules of problems in different levels in a case mode to serve as initial values;
the sub-module of the subregion, is used for classifying every key word around a certain circuit in a plurality of sample information of sampling as the identity district;
the calculation submodule is used for calculating the minimum distance between any two regions to obtain two regions with the minimum distance between the regions;
a region merging submodule for merging two regions having the smallest distance between the regions into a new region;
and the calculation submodule and the area merging submodule are alternately executed until the number of the remaining areas is a preset value.
9. The apparatus for generating an experimental circuit problem context map as claimed in claim 8, wherein said acquisition module comprises:
the traversal submodule is used for extracting text information in the abnormal data analysis summary of all the student historical experiment reports;
the correlation submodule is used for extracting the name of the experiment basic circuit and the experiment abnormal information;
the description submodule is used for carrying out combined description on the name of the experiment basic circuit and text information and experiment abnormal information in the abnormal data analysis summary;
the extraction module comprises:
the word extraction submodule is used for decomposing as many key words as possible from the experimental abnormal information;
the comparison sub-module is used for comparing the correlation among the keywords to form mutually independent keywords;
the processing module comprises:
the word frequency calculation submodule is used for calculating the word frequency of each keyword in the total number of the samples;
the inverse frequency calculation submodule is used for calculating the inverse problem frequency of each keyword;
a product calculating submodule for calculating the product of the word frequency and the inverse problem frequency of each keyword;
the vector generation submodule is used for creating a characteristic vector representing the importance degree of the keywords according to the product of the word frequency and the reverse question frequency of each keyword;
the generation module comprises:
the classification submodule is used for classifying the keyword area information into different types of experimental circuits;
the hierarchical submodule is used for arranging the keyword areas to different levels surrounding each type of experimental circuit;
and the drawing submodule is used for drawing the keywords and the experimental circuit into a tree structure according to the classification and layering results.
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| CN104537063A (en) * | 2014-12-29 | 2015-04-22 | 北京理工大学 | Knowledge venation map construction system and method based on thesis citation network |
| CN104915446A (en) * | 2015-06-29 | 2015-09-16 | 华南理工大学 | Automatic extracting method and system of event evolving relationship based on news |
| CN106557558A (en) * | 2016-11-09 | 2017-04-05 | 中国工商银行股份有限公司 | A kind of data analysing method and device |
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| CN104537063A (en) * | 2014-12-29 | 2015-04-22 | 北京理工大学 | Knowledge venation map construction system and method based on thesis citation network |
| CN104915446A (en) * | 2015-06-29 | 2015-09-16 | 华南理工大学 | Automatic extracting method and system of event evolving relationship based on news |
| CN106557558A (en) * | 2016-11-09 | 2017-04-05 | 中国工商银行股份有限公司 | A kind of data analysing method and device |
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