Method and system for constructing and displaying popular science content based on atlas

Abstract

The invention discloses a method and a system for constructing and displaying popular science content based on a graph, relates to the technical field of popular science display, and solves the technical problem that the popular science content display analysis is not performed according to the own characteristics of a user, and the display strategy analysis is not performed, so that the display deviation is further caused. The science popularization knowledge structure model is constructed by adopting the three-dimensional force map and the map technology, complex science popularization knowledge can be presented in a clearer and more organized mode, a user can more conveniently understand the association and hierarchical structure between the knowledge, the learning efficiency is improved, then the use record of the user is analyzed according to the classification of the user, and the user experience is improved. Different display modes are analyzed, the most suitable display mode is selected according to different classified users, multiple factors are comprehensively considered to optimize the popular science content and the display mode, the popular science content is made to better meet the requirements and preferences of the users, the display mode is made to better meet the learning habits of the users, and therefore the popular science effect is improved.

Description

Technical Field

[0001] The present invention relates to the field of science popularization display technology, and in particular to a method and system for displaying science popularization content based on graph construction. Background Art

[0002] With the development of information technology, the ways of disseminating popular science content are becoming increasingly diversified, but how to organize and display popular science content in a more scientific and efficient way to meet the needs of different user groups has become an urgent problem to be solved.

[0003] According to the publication number CN118747207A, a method and system for displaying popular science content based on graph construction is disclosed, which adopts a three-dimensional force-directed graph as a display carrier of popular science content, and constructs a popular science knowledge structure model through graph technology, wherein the popular science knowledge structure model includes multiple nodes, each node is a popular science knowledge point, and the nodes are connected by lines to represent the association between knowledge points; the popular science knowledge structure model is three-dimensionally rendered using three-dimensional technology to generate a popular science content interface with an intuitive and vivid display effect; after the user clicks on any node on the popular science content interface, the popular science article or article list corresponding to the clicked node is called out for the user to consult.

[0004] The above patent is a method for displaying popular science content based on graph construction. Through knowledge structure visualization, three-dimensional rendering and interactive experience, as well as precise content push, it effectively solves the shortcomings of existing popular science methods in knowledge presentation, user interaction and content relevance.

[0005] However, when some existing display methods are used, there is a problem that there is no corresponding popular science content display recommendation analysis based on different categories of users. Different users have different preferences and adaptability for the display methods of popular science content, and there is no good analysis of display strategies, resulting in deviations in the display of popular science content. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for displaying popular science content based on graph construction, which solves the problem of not performing popular science content display analysis based on the user's own characteristics and not performing display strategy analysis, which further causes display deviation.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for displaying popular science content based on graph construction, the method specifically comprising the following steps: Step 1: Use three-dimensional force-directed graphs as a display carrier for popular science content and construct a popular science knowledge structure model through graph technology; Step 2: Obtain corresponding usage records according to the constructed popular science knowledge structure model, and classify users based on the usage records to generate user classification information; Step 3: Analyze the usage records of users of different categories according to the user classification information, and classify the popular science contents into the same type according to the usage records to obtain the popular science contents of the same type, and calculate the like value of the popular science contents of the same type, and then sort them from large to small according to the like value to generate sorting information; Step 4: Perform display analysis on the popular science content of the same type based on the obtained ranking information, select the corresponding display method based on different users, and generate display information at the same time.

[0008] As a further solution of the present invention: the specific method of generating user classification information in step 2 is: Obtain the usage records of the popular science knowledge structure model, and obtain the user information in the usage records. At the same time, classify the user information based on age stages to obtain children, teenagers, young people, middle-aged and elderly users, and generate user classification information.

[0009] As a further solution of the present invention: the specific method of obtaining the same type of popular science content in step 3 is: Obtain user classification information, obtain usage records corresponding to different user classification information, and obtain the corresponding popular science content in the usage records, then classify the popular science content according to the popular science type to obtain the same type of popular science content, and record it as i, and i=1, 2, ..., j, where j represents the type of popular science content.

[0010] As a further solution of the present invention: the specific method of calculating the like value of the same type of popular science content in step 3 is: Take any type of popular science content of the same type as the analysis object, obtain the total popular science content of the analysis object within time t, record it as n, and n=1, 2, ..., m, where m represents the number of popular science content, and obtain the total number of views corresponding to popular science content n, record it as Cn, obtain the number of promotions corresponding to popular science content n, record it as Gn, and obtain the number of non-recommendations corresponding to popular science content n, record it as Fn, and then substitute the obtained parameters into the formula The preference index Sn corresponding to the popular science content n is calculated, where Cmax, Gmax and Fmax are the maximum total number of views, the maximum number of promotions and the maximum number of non-recommendations in the popular science content n, respectively. , and They are weight coefficients, respectively, and the specific values ​​are set by the operator; Similarly, the like indexes corresponding to all popular science contents n in the analysis object are analyzed, and the mean of all like indexes Sn is calculated and recorded as the like value; The calculation method of the object's likeness value is similarly analyzed, and the likeness values ​​corresponding to all popular science content i of the same type are calculated.

[0011] As a further solution of the present invention: the specific method of displaying and analyzing the same type of popular science content in step 4 is: Obtain the sorting information of the same type of popular science content, then obtain historical data, and analyze any one of the same type of popular science content as the target object, combine the historical data to obtain the display method corresponding to the target object, and label it as o, where o=1, 2, ..., p, where p represents the number of display methods, then obtain the user corresponding to the display method o, and label it as a, where a=1, 2, ..., b, where b represents different types of users.

[0012] As a further solution of the present invention: the specific method of generating the display information in step 4 is: Get the number of times used by different users and record it as Kao, and get the learning time corresponding to different users and record it as Tao. Then get the total number of users corresponding to different users and record it as Rao. Substitute the obtained parameters into the formula The comprehensive index Eao of display mode o is calculated, and , and is the weight coefficient, the specific value is set by the operator, and , while in the formula , and They are the total number of times the display method is used, the total learning time of the display method, and the total number of people using the display method; Similarly, the above calculation method is used to calculate the comprehensive index of different types of users corresponding to different display modes o, and the average of all comprehensive indexes is calculated as the display value; Then, the corresponding user is obtained, and the corresponding display method is selected based on the calculated comprehensive index, and the display method corresponding to the maximum comprehensive index is selected as the standard display method.

[0013] A system for displaying popular science content based on graph construction, including an information collection module, a model building module, a display analysis module and an information output module; An information collection module, which is used to acquire popular science content and transmit the acquired popular science content to a model building module; The model building module is used to build a popular science knowledge structure model based on the acquired popular science content, obtain usage records based on the popular science knowledge structure model, and transmit the acquired usage records to the display analysis module.

[0014] A display analysis module is used to classify and analyze the acquired usage records to obtain user classification information, analyze the usage records of users of different classifications according to the user classification information, and classify the popular science contents into the same type according to the usage records to obtain the same type of popular science contents, and calculate the likeness values ​​of the same type of popular science contents, and then sort them from large to small according to the likeness values ​​to generate sorting information, display and analyze the same type of popular science contents according to the obtained sorting information, and select the corresponding display method based on different users, and generate display information at the same time, and then transmit the display information to the information output module.

[0015] The information output module is used to display the acquired display information to the corresponding operator.

[0016] Beneficial Effects The present invention provides a method and system for displaying popular science content based on graphs. Compared with the prior art, it has the following beneficial effects: The present invention constructs a popular science knowledge structure model by adopting three-dimensional force-directed mapping and graph technology, which can present complex popular science knowledge in a clearer and more organized manner. Users can more conveniently understand the relationship and hierarchical structure between knowledge and improve learning efficiency. Then, the usage records are analyzed according to user classification, and different display methods are analyzed. The most suitable display method is selected according to different classified users. The popular science content and display method are optimized by comprehensively considering various factors, so that the popular science content is more in line with the needs and preferences of users, and the display method is more suitable for the learning habits of users, thereby improving the popular science effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a step method diagram of the present invention; Figure 2 This is a block diagram of the system principle of the present invention. DETAILED DESCRIPTION

[0018] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0019] For example, see Figure 1 The present application provides a method for displaying popular science content based on a graph, which specifically includes the following steps: Step one, use a three-dimensional force-directed map as a display carrier for popular science content, and construct a popular science knowledge structure model through graph technology. The construction of the popular science knowledge structure model here is an existing technology. For details, please refer to the construction method with publication number CN118747207A, and no further details will be given here.

[0020] Step 2: Obtain corresponding usage records based on the constructed popular science knowledge structure model, and classify users based on the usage records to generate user classification information.

[0021] The usage records of the popular science knowledge structure model are obtained, and the usage records indicate which personnel have used the popular science knowledge structure model, and the user information in the usage records is obtained, and the user information here includes age, gender and education level. At the same time, the user information is classified based on age to obtain children, teenagers, young people, middle-aged and elderly users, and user classification information is generated at the same time.

[0022] The specific age stage of children is 1-12 years old, the age stage of teenagers is 13-19 years old, the age stage of young people is 20-39 years old, the age stage of middle-aged people is 40-59 years old, and the age stage of the elderly is over 60 years old.

[0023] Step three, analyzing the usage records of users of different categories according to the user classification information, and classifying the popular science contents into the same type according to the usage records to obtain the same type of popular science contents, and calculating the like value of the same type of popular science contents, and then sorting them from large to small according to the like value to generate sorting information.

[0024] Obtain user classification information, obtain usage records corresponding to different user classification information, and obtain corresponding popular science content in the usage records. Then classify the popular science content according to the popular science type to obtain popular science content of the same type, and record it as i, and i=1, 2, ..., j, where j represents the type of popular science content. Then obtain the number of views Ci corresponding to the popular science content of the same type i, and the number of views here represents the total number of views of a single type of popular science content corresponding to the same age stage, for example, the number of views of popular science content of the type of scientific knowledge by young users, and calculate the like value of the popular science content of the same type i based on the number of views Ci, and the specific calculation method is as follows: Take any type of popular science content of the same type as the analysis object, obtain the total popular science content of the analysis object within time t, record it as n, and n=1, 2, ..., m, where m represents the number of popular science content, and at the same time obtain the total number of views corresponding to popular science content n, record it as Cn, and obtain the number of promotions corresponding to popular science content n, record it as Gn, and the number of promotions here represents the number of times the popular science content is sent to other users for viewing by users performing operations such as conversion and sharing, and at the same time obtain the number of non-recommendations corresponding to popular science content n, record it as Fn, and the number of non-recommendations here represents the number of times users do not recommend the content, then substitute the obtained parameters into the formula The preference index Sn corresponding to the popular science content n is calculated, where Cmax, Gmax and Fmax are the maximum total number of views, the maximum number of promotions and the maximum number of non-recommendations in the popular science content n, respectively. , and are weight coefficients respectively, and the specific values ​​are set by the operator. Similarly, the like indexes corresponding to all popular science contents n in the analysis object are analyzed, and the mean of all like indexes Sn is calculated and recorded as the like value; Similarly, the calculation method of the object's like value is used to calculate the like value corresponding to all popular science content i of the same type; The popular science contents i of the same type are sorted from large to small according to the calculated preference values, and the sorting information is generated.

[0025] Step 4: Perform display analysis on the popular science content of the same type based on the obtained ranking information, select the corresponding display method based on different users, and generate display information at the same time.

[0026] Get the ranking information of the same type of popular science content, then get the historical data, and analyze any one of the same type of popular science content as the target object, combine the historical data to get the display method corresponding to the target object, and mark it as o, and o=1, 2, ..., p, where p represents the number of display methods, then get the user corresponding to display method o, and mark it as a, and a=1, 2, ..., b, where b represents different types of users, and the users here represent users of different age groups, and get the number of times of use corresponding to different users, record it as Kao, and get the learning time corresponding to different users, record it as Tao, and the learning time here is the learning time corresponding to display method o, then get the total number of users corresponding to different users, record it as Rao, and substitute the obtained parameters into the formula The comprehensive index Eao of display mode o is calculated, and , and is the weight coefficient, the specific value is set by the operator, and , while in the formula , and They are the total number of times the display method is used, the total learning time of the display method, and the total number of people using the display method; Similarly, the above calculation method is used to calculate the comprehensive index of different types of users corresponding to different display modes o, and the average of all comprehensive indexes is calculated as the display value; Then, the corresponding user is obtained, and the corresponding display method is selected based on the calculated comprehensive index, and the display method corresponding to the largest comprehensive index is selected as the standard display method. Specifically, for example, the current user is classified as a teenager, and further calculations show that when the teenager is learning popular science content, the corresponding display methods include image display, text display, and video display, and the order obtained after sorting according to the corresponding comprehensive index is video display, image display, and text display. The display method with the largest comprehensive index is further selected as the standard display method.

[0027] For example 2, please refer to Figure 2 The present application provides a system for displaying popular science content based on graphs, the system includes: an information collection module, a model building module, a display analysis module and an information output module, and at the same time, in combination with the attached Figure 2 It can be known that all the above functional modules are electrically connected in one direction.

[0028] The information collection module is used to acquire popular science content and transmit the acquired popular science content to the model building module.

[0029] The model building module is used to build a popular science knowledge structure model based on the acquired popular science content, obtain usage records based on the popular science knowledge structure model, and transmit the acquired usage records to the display analysis module.

[0030] A display analysis module is used to classify and analyze the acquired usage records to obtain user classification information, analyze the usage records of users of different classifications according to the user classification information, and classify the popular science contents into the same type according to the usage records to obtain the popular science contents of the same type, and calculate the preference values ​​of the popular science contents of the same type, and then generate sorting information by sorting them from large to small according to the preference values. The processing method here is the same as the analysis process of step three in embodiment one. The popular science contents of the same type are displayed and analyzed according to the obtained sorting information, and the corresponding display method is selected based on different users, and the display information is generated at the same time. The display information is then transmitted to the information output module, and the processing method here is the same as the analysis process of step four in embodiment one.

[0031] The information output module is used to display the acquired display information to the corresponding operator.

[0032] Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0033] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for displaying popular science content based on graph construction, characterized in that: The method specifically comprises the following steps: Step 1: Use three-dimensional force-directed graphs as a display carrier for popular science content and construct a popular science knowledge structure model through graph technology; Step 2: Obtain corresponding usage records according to the constructed popular science knowledge structure model, and classify users based on the usage records to generate user classification information; Step 3: Analyze the usage records of users of different categories according to the user classification information, and classify the popular science contents into the same type according to the usage records to obtain the popular science contents of the same type, and calculate the like value of the popular science contents of the same type, and then sort them from large to small according to the like value to generate sorting information; Step 4: Perform display analysis on the popular science content of the same type based on the obtained ranking information, select the corresponding display method based on different users, and generate display information at the same time.

2. A method for displaying popular science content based on graph construction according to claim 1, characterized in that: The specific method of generating user classification information in step 2 is: Obtain the usage records of the popular science knowledge structure model, and obtain the user information in the usage records. At the same time, classify the user information based on age stages to obtain children, teenagers, young people, middle-aged and elderly users, and generate user classification information.

3. The method for displaying popular science content based on graph construction according to claim 1, characterized in that: The specific method of obtaining the same type of popular science content in step 3 is: Obtain user classification information, obtain usage records corresponding to different user classification information, and obtain the corresponding popular science content in the usage records, then classify the popular science content according to the popular science type to obtain the same type of popular science content, and record it as i, and i=1, 2, ..., j, where j represents the type of popular science content.

4. The method for displaying popular science content based on graph construction according to claim 1, characterized in that: The specific method for calculating the likeability value of the same type of popular science content in step 3 is: Take any type of popular science content of the same type as the analysis object, obtain the total popular science content of the analysis object within time t, record it as n, and n=1, 2, ..., m, where m represents the number of popular science content, and obtain the total number of views corresponding to popular science content n, record it as Cn, obtain the number of promotions corresponding to popular science content n, record it as Gn, and obtain the number of non-recommendations corresponding to popular science content n, record it as Fn, and then substitute the obtained parameters into the formula The preference index Sn corresponding to the popular science content n is calculated, where Cmax, Gmax and Fmax are the maximum total number of views, the maximum number of promotions and the maximum number of non-recommendations in the popular science content n, respectively. , and They are weight coefficients, and the specific values ​​are set by the operator; Similarly, the like indexes corresponding to all popular science contents n in the analysis object are analyzed, and the mean of all like indexes Sn is calculated and recorded as the like value; The calculation method of the object's likeness value is similarly analyzed, and the likeness values ​​corresponding to all popular science content i of the same type are calculated.

5. The method for displaying popular science content based on graph construction according to claim 1, characterized in that: The specific method for displaying and analyzing the same type of popular science content in step 4 is: Obtain the sorting information of the same type of popular science content, then obtain historical data, and analyze any one of the same type of popular science content as the target object, combine the historical data to obtain the display method corresponding to the target object, and label it as o, where o=1, 2, ..., p, where p represents the number of display methods, then obtain the user corresponding to the display method o, and label it as a, where a=1, 2, ..., b, where b represents different types of users.

6. The method for displaying popular science content based on graph construction according to claim 1, characterized in that: The specific method of generating display information in step 4 is: Get the number of times used by different users and record it as Kao, and get the learning time corresponding to different users and record it as Tao. Then get the total number of users corresponding to different users and record it as Rao. Substitute the obtained parameters into the formula The comprehensive index Eao of display mode o is calculated, and , and is the weight coefficient, the specific value is set by the operator, and , while in the formula , and They are the total number of times the display method is used, the total learning time of the display method, and the total number of people using the display method; Similarly, the above calculation method is used to calculate the comprehensive index of different types of users corresponding to different display modes o, and the average of all comprehensive indexes is calculated as the display value; Then, the corresponding user is obtained, and the corresponding display method is selected based on the calculated comprehensive index, and the display method corresponding to the maximum comprehensive index is selected as the standard display method.

7. A system for displaying popular science content based on graph construction, used to execute the method for displaying popular science content based on graph construction according to any one of claims 1 to 6, characterized in that: It includes information collection module, model building module, display analysis module and information output module.

8. The system for displaying popular science content based on graph construction according to claim 7, characterized in that: The information collection module is used to acquire popular science content and transmit the acquired popular science content to the model building module; A model building module, which is used to build a popular science knowledge structure model based on the acquired popular science content, obtain usage records based on the popular science knowledge structure model, and transmit the acquired usage records to the display analysis module; A display analysis module, which is used to classify and analyze the acquired usage records to obtain user classification information, analyze the usage records of users of different classifications according to the user classification information, and classify the popular science contents into the same type according to the usage records to obtain the same type of popular science contents, and calculate the likeness values ​​of the same type of popular science contents, and then sort them from large to small according to the likeness values ​​to generate sorting information, perform display analysis on the same type of popular science contents according to the obtained sorting information, and select corresponding display methods based on different users, and generate display information at the same time, and then transmit the display information to the information output module; The information output module is used to display the acquired display information to the corresponding operator.

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