A design method based on the logical expansion of mind maps

Abstract

The present invention discloses a design method based on the logical expansion of mind maps, belonging to the technical field of design; determining the first keyword for questionnaire analysis to obtain at least one keyword other than the first keyword; constructing a co-occurrence network diagram and a mind map, and determining the Nth keyword, etc.; this method takes exploring the concept generation process of design as the core, regarding designers as the most non-processable part: clearly step-by-step the abstract concept generation process, using relatively concrete language and text keywords as carriers to establish an association between abstract thinking and concrete two-dimensional or three-dimensional images, which becomes the basic condition for sorting out relevant thinking factors and forming design results; this method can effectively broaden the thinking of designers, avoid thinking about the design problem itself narrowly and restrictedly from the perspective of the design entity, and can efficiently gather a large number of keyword elements in a short time to form a design logic, providing logical thinking support for the production design process.

Description

Technical Field

[0001] The invention belongs to the field of design technology, and in particular relates to a design method based on the logical expansion of a mind map. Background Art

[0002] Where does design inspiration come from? How is a design concept generated? This question not only troubles design students, but also designers. Various design methodologies attempt to solve the problems of where ideas come from, how to expand ideas, how to realize concepts, and how to transform ideas into a design result.

[0003] The process of generating ideas is a black box for designers: there are consistent input conditions at the front end of the design, and countless output possibilities at the back end, but the process of producing this design result is difficult to quantify and interpret. The part of generating inspiration is attributed to an unspeakable black box process. Peter Eiseman tried to reduce this irrational and purely perceptual method to a rational step. Through the operation conversion of several steps, the graphic thinking process of architecture is realized, and this unquantifiable process is transformed into a step-by-step and repeatable process. However, the theory of its "Graphic Log" is profound, which makes many designers daunted. Where does the design diagram come from? How is the operation step generated by the diagram decided? How does the designer come up with these operation steps and then let it drive the design? Is there a way to easily transform the illusory ideas and chaotic thoughts in the mind into a visible design process? As a design teacher, is there a way to effectively convey the process of generating inspiration to students so that students can also generate countless ideas, and these ideas are not limited to the teacher's ideas and techniques? These design questions have not been answered based on clear steps in existing design methodologies. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] Out of doubts and research on the above-mentioned problems, the design process adopts the following methods to solve the first complicated process at the top of the pyramid: the button at the very beginning of the black box. When this button is activated, ideas will begin to be generated, becoming the source and raw materials of diversified design results. Only with a constant supply of raw materials can more exquisite design results be produced. Of course, with the production of raw materials, like conventional, classic, and traditional design, a professional training path is required to process, produce and manufacture the raw materials, and finally form design results.

[0006] This method draws on the brainstorming method of "mind mapping" which is based on pure text and associated graphics, and divides the entire design process into four steps: brainstorming - focusing on hotspots - sorting out logic - design process. The first three steps are an output and sorting of ideas from disorder to order, ensuring the production of the raw materials mentioned above. Then, graft and input these produced ideas and raw materials into the traditional design process, and repeat the cycle.

[0007] This is an idea generator. When designers or design students activate their brains, they will involuntarily push the design forward, driving the change of thinking and the iteration of ideas in the entire design team, making the generation of design and ideas a driving force to promote the subsequent professional design production and processing process. Through this method, ideas will no longer dry up, and the connection between the concrete and the abstract becomes within reach.

[0008] (2) Technical solution

[0009] The present invention is realized through the following technical solutions: a design method based on the logical expansion of mind mapping; the method includes the following steps:

[0010] Step 100: Determine the first keyword for questionnaire analysis and obtain at least one keyword other than the first keyword;

[0011] Step 200: Construct a co-occurrence network diagram and a mind map based on the above keywords, and determine the Nth keyword; repeat Step 100 until the number of keywords N reaches the set threshold;

[0012] Step 300: Pair the mind map with the design problem to derive at least one keyword; perform data scraping based on the keyword;

[0013] Step 400: Perform design based on the co-occurrence network diagram, the mind map, and the scraped data.

[0014] As a further description of the above solution, the questionnaire analysis in Step 100 includes the following steps:

[0015] Step 110: Determine the keyword;

[0016] Step 120: Call the question bank to generate at least one keyword question;

[0017] Step 130: Based on the keyword question, call the questionnaire template to generate a questionnaire and distribute and collect it;

[0018] Step 140: Analyze the questionnaire to determine at least one keyword.

[0019] As a further description of the above solution, the keyword question in Step 120 is a text question.

[0020] As a further illustration of the above solution, the method for determining at least one keyword in step 140 includes the following steps:

[0021] Step 141: Use the keywords used in step 120 as candidate keywords for the algorithm;

[0022] Step 142: Segment and extract the text based on the Chinese text keyword extraction algorithm to generate several keywords.

[0023] As a further illustration of the above solution, step 200 specifically includes the following steps:

[0024] Step 210: Construct a keyword co-occurrence network diagram based on N keywords;

[0025] Step 220: Extract 3 to N keywords from the keyword co-occurrence network diagram to construct a mind map.

[0026] As a further illustration of the above solution, step 300 specifically includes the following steps:

[0027] Step 310: Decompose the preset design problem into three modules;

[0028] Step 320: Manually classify the extracted keywords based on the three modules;

[0029] Step 330: Screen the keywords classified by the three modules, and export at least one keyword for each module;

[0030] Step 340: Based on at least one keyword exported for each module, use big data to perform data scraping.

[0031] As a further illustration of the above solution, the three modules in step 310 are: independent module, interchangeable module, and general module.

[0032] As a further illustration of the above solution, the data scraping in step 340 includes image data.

[0033] As a further illustration of the above solution, the co-occurrence network diagram, mind map, and scraped data in step 400 are stored in a database, and a classification package is created with the name of the design problem. The designer calls the data in the classification package for design.

[0034] As a further illustration of the above solution, when a new design problem appears during the design process in step 400, repeat steps 100 to 400, and create a sub-classification package for storage based on the original classification package.

[0035] (III) Beneficial effects

[0036] The present invention has the following beneficial effects compared with the prior art:

[0037] This method takes the exploration of the conceptual generation process of design as the core, regarding the designer as the most non-procedural part: the abstract concept generation process is clearly step-by-step, with relatively concrete language keywords as the carrier, establishing a connection between abstract thinking and concrete two-dimensional or three-dimensional images, becoming the basic condition for sorting out relevant thinking factors and forming design results. This method can effectively broaden the thinking of designers, avoid thinking about design problems narrowly and restrictedly from the perspective of the design itself, and through interaction and questioning, it can broaden and stimulate thinking, and can efficiently gather a large number of keyword elements in a short time to form a design logic, providing logical thinking support for the production design process. Specific implementation mode

[0038] Example 1

[0039] In this embodiment, keywords of design problems are extracted based on the sketches of designers; it should be further noted that the "sketches" mentioned here, that is, "diagrams", are not just hand-drawn sketches, but may include models, digital tools, and various ways to express abstract thinking in a concrete form. First, the first step is to determine the first keyword. For the convenience of explaining the embodiment, the key problem of this embodiment is expressed in words: "The application of the 'national trend' style in graphic design". Based on this design problem, the keyword "national trend" is extracted. After determining the keyword, enter the process of the method of this embodiment:

[0040] Step 100: Determine the first keyword and conduct a questionnaire analysis to obtain at least one keyword other than the first keyword;

[0041] Step 110: Determine the keyword "national trend";

[0042] Step 120: Call the question library to generate at least one keyword question;

[0043] It should be further noted that for the convenience of explaining the principle and steps of the method of this embodiment, this embodiment takes three questions as examples, and the questions are as follows:

[0044] 1. "How to define the style of 'national trend'?"

[0045] 2. "What are the color elements of the 'national trend' style?"

[0046] 3. "What should the 'national trend' style be in your mind?"

[0047] The three keyword questions are all automatically generated using the keyword question template. After the generation is completed, the process proceeds to the next step. It should be further noted that the keyword questions in step 120 are text questions. Since design itself is a form of expression discipline, if the multiple-choice question mode is adopted, it will greatly limit the thinking mode of the respondents, making it impossible for this method to complete the subsequent steps and making this method the same as the design mode under the traditional Internet model, thus covering up the innovation points of this method.

[0048] Step 130: Based on the keyword questions, call the questionnaire template to generate a questionnaire and distribute and collect it.

[0049] It should be further noted that the mode of distributing and collecting the questionnaire is an existing technology. It can be transmitted online, printed out and transmitted offline, or based on questions for offline interviews, etc. There is no need to elaborate here.

[0050] Step 140: Analyze the questionnaire to determine at least one keyword. The method of determining at least one keyword in step 140 includes the following steps:

[0051] Step 141: Use the keywords used in step 120 as candidate keywords for the algorithm.

[0052] Step 142: Segment and extract the text based on the Chinese text keyword extraction algorithm to generate several keywords.

[0053] It should be further noted that in this embodiment, the TF-IDF text keyword extraction method is used to implement this step. The specific principle is as follows:

[0054] TF = (the number of times a certain keyword appears in the document) / (the total number of times in the document)

[0055] IDF = log((the total number of documents in the corpus) / (the number of documents containing a certain keyword + 1))

[0056] TF-IDF = TF * IDF

[0057] In the above three formulas, TF represents the term frequency, IDF represents the inverse document frequency, and TF-IDF is used to weight all candidate keywords in the text, and the keywords are sorted according to the weights.

[0058] It should be further noted that there are various algorithms for implementing this step, such as the text keyword extraction method based on TextRank and the text keyword extraction method based on Word2Vec word clustering. In order to facilitate the explanation of the principle and process of this method in this embodiment, a relatively simple algorithm is selected for explanation, which is not a further limitation of the claims. At the same time, the TF-IDF text keyword extraction method is a prior art, and only the principle of the TF-IDF text keyword extraction method is elaborated here without further elaboration.

[0059] Step 200: Construct a co-occurrence network diagram and a mind map based on the above keywords, and determine the Nth keyword; repeat Step 100 until the number of keywords N reaches the set threshold.

[0060] Step 210: Construct a keyword co-occurrence network diagram based on the N keywords.

[0061] Step 220: Extract 3 to N keywords from the keyword co-occurrence network diagram to construct a mind map.

[0062] It should be further noted that the purpose of this step is to generate ideas based on the mind map using "language keywords". Use language keywords to describe the main properties and interrelationships of the design. In this step, it often requires multiple people to collaborate and adopt a way of asking and inspiring each other to answer the language keywords proposed by members of the same group, guiding each other to lead out more language keywords. For the language keywords generated in the previous step, select the language keywords that conform to the design theme as the core vocabulary of the second-round mind map and conduct divergent associations. In the second-round focus hotspots, the keywords generated in the first round can still be used as the branch levels in the focus hotspots.

[0063] Step 300: Pair the mind map with the design problem to derive at least one keyword; perform data scraping based on the keyword.

[0064] Step 310: Decompose the preset design problem into three modules: an independent module, an interchangeable module, and a general module. The purpose of this step is to deconstruct the design problem with abstract attributes into a quantifiable index and a matching entity form. In this embodiment, the design problem is "the application of the 'national trend' style in graphic design", so it can be structured into three modules:

[0065] Independent module: National trend style.

[0066] Interchangeable module: Graphic design.

[0067] General module: Practical application.

[0068] Most of the design problems can be decomposed into the above three modules. The independent module represents the unique characteristics of a certain design problem and is the central idea of the design problem. The interchangeable module represents the standardized structures, dimensions, etc. that can be common to the design problem in different fields; the general module represents the versatility of the design problem in horizontal and vertical product parts;

[0069] Step 320: Manually classify the extracted keywords based on the three modules;

[0070] Step 330: Screen the keywords classified based on the three modules, and export at least one keyword for each module;

[0071] Step 340: Based on at least one keyword exported for each module, use big data to perform data scraping; the scraping includes image data.

[0072] From the perspective of data quantification, this step transforms the problem with abstract attributes into a quantifiable problem from the structure to classification to data scraping of big data, and logically matches the abstract attributes generated by focusing on hot keywords with the problem attributes that need to be solved in the design, which becomes the logical basis for the fourth-step design. These logical chains can be re-dispersed and then re-connected and re-processed to form a brand-new logical chain.

[0073] Step 400: Perform design based on the co-occurrence network diagram, mind map, and scraped data. The co-occurrence network diagram, mind map, and scraped data are stored in the database. A classification package is established with the name of the design problem, and the designer calls the data in the classification package for design. The purpose of this step is to integrate the results generated in the previous three steps, establish a classification package, and thus facilitate the designer to carry out the design. When new design problems occur during the design process of Step 400, repeat Steps 100 to 400, and establish a sub-classification package for storage based on the original classification package. During the design process, continuously transform the abstract design problem into a quantifiable entity form, and use computer processing to realize the idea of divergent thinking - extracting logical lines - re-divergent thinking - re-extracting logical lines.

[0074] Embodiment 2

[0075] The difference between this embodiment and Embodiment 1 is that big data scraping is first performed using keywords to determine the picture data closest to the theme, a keyword problem is established through the pictures, and then a questionnaire is generated; the remaining steps are the same as those in Embodiment 1.

[0076] The foregoing has shown and described the basic principles, main features and advantages of the present invention. For a person skilled in the art, it is obvious that the present invention is not limited to the details of the above-mentioned exemplary embodiments, and without departing from the spirit or basic features of the present invention, the present invention can be implemented in other specific forms. Therefore, from any point of view, the embodiments should be regarded as exemplary and non-limiting. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, it is intended to embrace all changes that fall within the meaning and scope of the equivalent elements of the claims in the present invention.

[0077] In addition, it should be understood that although this specification is described in terms of embodiments, not every embodiment only contains an independent technical solution. This narrative manner of the specification is only for clarity. Those skilled in the art should regard the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A design method based on the logical expansion of mind maps; characterized in that: The method includes the following steps: Step 100: Determine the first keyword for questionnaire analysis to obtain at least one keyword other than the first keyword; the questionnaire analysis in step 100 includes the following steps: Step 110: Determine the keyword. Step 120: Call the question bank to automatically generate at least one keyword question based on the keyword question template; the keyword question is a text question. Step 130: Based on the keyword question, call the questionnaire template to generate a questionnaire and distribute and collect it. Step 140: Analyze the questionnaire to determine at least one keyword; the method for determining at least one keyword in step 140 includes the following steps: Step 141: Use the keyword used in step 120 as the candidate keyword for the algorithm. Step 142: Segment and extract the text based on the Chinese text keyword extraction algorithm to generate several keywords. Step 200: Construct a co-occurrence network diagram and a mind map based on the above keywords to determine the Nth keyword. Repeat step 100 until the number of keywords N reaches the set threshold. Step 300: Pair the mind map with the design problem to export at least one keyword; perform data scraping based on the keyword. The specific steps of step 300 include the following steps: Step 310: Decompose the preset design problem into three modules: an independent module, an interchange module, and a general module; the independent module represents the unique characteristics of the design problem and is the central idea of the design problem. The interchange module represents the standardized structure and dimensions that the design problem can be common in different fields. The general module represents the versatility of the design problem in horizontal and vertical product parts. The purpose of this step is to deconstruct the design problem with abstract attributes into a structure of quantifiable indicators and matching entity forms. Step 320: Manually classify the extracted keywords based on the three modules. Step 330: Screen the keywords classified by the three modules, and export at least one keyword for each module. Step 340: Based on at least one keyword exported for each module, use big data for data scraping. In step 340, the data scraping includes image data. This step, from structure to classification to big data scraping, starting from the perspective of data quantification, transforms the problem with abstract attributes into a quantifiable problem, logically matches the abstract attributes generated by focusing on hot keywords with the problem attributes that need to be solved in the design, and becomes the logical basis for the design in step 400. Step 400: Perform design based on the co-occurrence network diagram, mind map, and the scraped data; the specific steps of step 200 include the following steps: Step 210: Construct a keyword co-occurrence network diagram based on the N keywords. Step 220: Extract 3 to N keywords from the keyword co-occurrence network diagram to construct a mind map. Based on the mind map method, use "language keywords" to generate ideas; use language keywords to describe the main properties and interrelationships of the design. In this step, multiple people need to collaborate and use the method of asking and inspiring each other to answer the language keywords proposed by members of the same group, and guide each other to lead out more language keywords. For the language keywords generated in the previous step, select the language keywords that conform to the design theme as the core vocabulary of the second-round mind map, and conduct divergent associations; specifically, the co-occurrence network diagram, mind map, and captured data in step 400 are stored in the database, and a classification package is established with the design problem as the name. The designer calls the data in the classification package for design; when new design problems arise during the design process of step 400, repeat steps 100 to 400, and establish a sub-classification package for storage based on the original classification package.