Method for optimizing heritage explanation system based on multivariate subject cognitive model

Abstract

The invention discloses a heritage explanation system optimization method based on a multivariate subject cognitive model. The method comprises the following steps: delimiting official, tourist and resident subjects; official texts are mined, and a policy-value two-dimensional analysis framework is constructed for heritage value research; digital footprints are extracted, semantic network information and geographic space information are coupled for classification, and tourism image principal axis coding is comprehensively carried out; carrying out demand attribute division on the recognized heritage cognitive content by interviewing in the ground and introducing a model KANO to quantitatively carry out demand attribute division on the recognized heritage cognitive content; a heritage explanation system optimization method based on an official-tourist-resident trinity cognitive model is constructed by integrating three perspectives, and public and social transformation of heritage protection is guided. Therefore, a heritage explanation system optimization method based on an official-tourist-resident trinity cognitive model is constructed.

Description

Technical Field

[0001] The present invention relates to the field of urban cultural heritage protection and utilization, and specifically to an optimization method for a heritage interpretation system based on a multi-agent cognitive model. Background Art

[0002] Heritage is both an existence and a cognition. Without cognition, there is no heritage in the modern sense. As a system of speech and practice in a specific historical context, heritage and its cognition are a kind of discourse construction facing the past at present. Thus, heritage interpretation has become a means of information transmission based on value understanding, reflecting the cognition of different agents on the value of heritage. Driven by UNESCO, modern heritage has rapidly grown into an important global cultural affair; and cultural heritage on the world stage has become an important marker for expressing the cultural uniqueness of a country. Against this background, the protection instruments formulated by international heritage organizations are usually implemented within the operation framework of "international - sovereign state - heritage community". Under such a framework, the heritage language initiated at the international level and dominated by national forces is forming a special authoritative discourse system, directly or indirectly affecting the changes in local traditions, cultural practices and daily life.

[0003] Among them, the World Heritage Organization stipulates the cognition of heritage and related terms from a global perspective; sovereign states express the cognition of heritage from a national perspective; while those who create, use and inherit cultural heritage form the core value due to their local expressions of heritage interpretation. The dynamic mechanism of maintaining balance among different landscape cognition methods and constituting a comprehensive interpretation system. Specifically, landscape cognition includes both the "external landscape" shaped by external forces such as authoritative institutions with decision-making power at the macro level in the process of globalization, and the "internal landscape" created by internal forces such as users and local residents based on daily practices at the micro level in the process of localization. Therefore, the "officials" with a global and national perspective, the "tourists" with an external landscape perspective, and the "residents" with an internal landscape perspective constitute a multi-agent heritage cognitive model.

[0004] Although there is a strong consensus among the above three roles in heritage protection; due to the differences in the projection dimensions of perspectives, there will still be overlapping, polysemous, intersecting, or even exclusive situations in their heritage cognition. The "officials" shape heritage cognition from top to bottom, and the "tourists" and "residents" respectively influence heritage cognition from the external and internal perspectives from bottom to top. For the existing system, the speech and expression of each unit are limited, and only the structural expression from a comprehensive perspective is relatively complete. Therefore, how to comprehensively balance the interpretation of heritage by each agent has become one of the key issues in the field of heritage interpretation.

[0005] Based on this, there is an urgent need for an optimization method for the heritage interpretation system. By systematically analyzing the dimensions and aspects of heritage cognition from the three perspectives of "official - tourist - resident", a method for optimizing the heritage interpretation system based on the "official - tourist - resident" trinity cognitive model is constructed to understand the various cognitive aspects presented when different roles view the heritage from specific positions, and the value tendencies of different dimensions demonstrated by different cognitive methods. Summary of the Invention

[0006] Aiming at the limitations of the existing isolated heritage interpretation, to optimize the existing heritage interpretation framework and create a cultural heritage interpretation system that can connect multiple subjects, the present invention constructs a method for optimizing the heritage interpretation system based on the "official - tourist - resident" trinity cognitive model. Through systematic analysis and quantitative calculation of the dimensions and aspects of heritage cognition from the three perspectives, it is possible to understand the various cognitive aspects presented when different roles view the heritage from specific positions, and the value tendencies of different dimensions demonstrated by different cognitive methods. Thus, a method for optimizing the heritage interpretation system based on a multi - subject cognitive model with cultural heritage as the analysis object is constructed, and then the "top - down" authoritative discourse system and the "bottom - up" popular discourse system are connected to move towards the shaping of a more comprehensive and diverse heritage discourse system.

[0007] The present invention specifically adopts the following technical solutions to solve the above - mentioned technical problems: A method for optimizing the heritage interpretation system based on a multi - subject cognitive model, comprising the steps of: Step 1: Define the three parties of official - tourist - resident; Step 2: Mine official texts and construct a two - dimensional analysis framework of "policy - value" for heritage value research; Step 3: Extract digital footprints, couple semantic network information and geospatial information for classification and comprehensively conduct tourism image main axis coding; Step 4: Conduct on - site interviews and introduce the KANO model for quantitative division of the demand attributes of the identified heritage cognition content; Step 5: Comprehensively construct a method for optimizing the heritage interpretation system based on the "official - tourist - resident" trinity cognitive model from the three perspectives to guide the public and social transformation of heritage protection.

[0008] Furthermore, Step 1 specifically includes analyzing multiple audiences and different perspectives of the heritage to define the three parties of official - tourist - resident.

[0009] Furthermore, Step 2 specifically includes conducting information mining and numerical calculation on government public documents from the official perspective. By referring to the heritage value type analysis framework, a two - dimensional analysis model of "policy - value" for authoritative heritage discourse analysis is constructed using the word - frequency weight statistics method: 1) Select government public documents from official websites as text data sources, put government public documents into ROST-CM6 software for word frequency statistics, and extract corresponding high-frequency words; 2) The process of constructing the index system of heritage value is divided into three stages: heritage characteristics analysis, value type interpretation, and evaluation index determination, and the construction of a heritage value research framework; 3) Analyze the characteristics of heritage from the perspectives of form, relationship and practice, interpret the value types from an official perspective, and establish an evaluation system; 4) A two-dimensional analysis framework is constructed with policy perspective and value assessment as the x-axis and y-axis respectively to visualize the heritage value types from the official perspective.

[0010] Furthermore, in step 1): the information of the super-level perspective comes from the international official website, and the relevant documents issued by the evaluation organization are extracted; the textual data of the high-level perspective comes from the domestic official website.

[0011] Furthermore, in step 2): first, analyze the characteristics of heritage from the three aspects of form, relationship and practice, and summarize them as "heritage composition", "spiritual spectrum" and "symbiotic practice". On this basis, combine the characteristics of heritage objects to make characteristic supplements, so as to interpret the value type from an official perspective and establish an evaluation system; secondly, for the interpretation of value type, find out the registration standards established by the World Heritage Convention that the heritage objects meet from a super-level perspective, and summarize their value characteristics; interpret the value type from a high-level perspective according to the three classification standards of historical value, artistic value and scientific value defined in the Cultural Relics Protection Law of the People's Republic of China; finally, dig out the number and weight of high-frequency words in official texts to determine the evaluation indicators, and calculate the indicator weights for quantitative value classification.

[0012] Furthermore, step three specifically includes dividing cultural heritage into three types: core, transitional, and marginal, based on the spatial distribution of tourists' digital footprints and recreational popularity from the perspective of tourists, coupling semantic network information with geographic space information, and applying the main axis coding technique to the qualitative interpretation of tourists' cognition according to the grounded theory: 1) Use crawler software to batch mine tourist review information posted by tourists on tourism websites and build a digital footprint corpus; 2) In ROST CM6 software, we established a dedicated vocabulary and defined a filtering vocabulary to conduct word frequency analysis and high-frequency word mining; we used social network analysis software Ucinet 6 to calculate the flow information between the heritages, and built a flow matrix with the name of the scenic spot as the basic unit. We compared the structural characteristics of the recreation network through multiple experiments, and selected appropriate breakpoint values ​​to binarize the assignment matrix; in order to characterize the importance of each scenic spot in the recreation network, we used social network analysis software Ucinet 6 to calculate the core degree, and selected the classification basis suitable for individual objects to determine the type of cultural heritage as marginal, transitional or core; 3) Using grounded theory to conduct hierarchical analysis of the digital footprint corpus, open coding, principal axis coding, and selective coding were performed simultaneously for multiple types of scenic spots in the text qualitative analysis software NVivo11, and on this basis, semantic network analysis was completed using Ucinet6. In the semantic network analysis software Ucinet 6, the Netdraw function was used to draw a semantic network analysis diagram; 4) Use proportional area graphs to intuitively display the data size of various cognitive attributes and each coding node through graphic area.

[0013] Furthermore, step 4 specifically includes first determining the communities covered by the 15-minute living circle of each heritage attraction in the three types of heritage through traffic accessibility from the perspective of residents, and conducting semi-structured interviews and text semantic analysis. Then, the user demand analysis model KANO is used to quantitatively divide the demand attributes of the identified heritage cognitive content: 1) Using ArcGIS, we defined and constructed a 15-minute living circle within the service area of ​​each cultural heritage site through the traffic accessibility function, and counted the number and names of various communities within the scope; 2) Through the method of step-by-step and point-by-point mining, the situational semi-structured interview was conducted. The survey was divided into two parts: interview and questionnaire. The interview part guided the residents to express their views, and adopted the reverse analysis process opposite to the main axis coding of tourists' heritage cognition to improve the cognitive system framework. The questionnaire part introduced the Kano model, and the questionnaire design combined with the coding results in step 3 to score the degree of the questions set at each node, and conducted a preliminary survey to supplement the questionnaire questions based on the actual situation. 3) Distribute survey questionnaires, translate interview recordings, and perform text semantic analysis using a large language model; collect survey questionnaire information, conduct two-way reliability and validity tests on the questionnaire results using SPSS, and, based on the good structural validity of the questionnaire, perform quantitative statistics on the survey results corresponding to the necessary attributes M, desired attributes O, attractive attributes A, indifference attributes I, and reverse attributes R according to the Kano model attribute table, and substitute them into the Kano model for analysis; 4) Calculate by the Better-Worse coefficient method. The Better coefficient = (A + O) / (A + O + M + I), and the Worse coefficient = -(O + M) / (A + O + M + I); calculate the distance from each node to the origin of coordinates to obtain the sensitivity value of each node, and draw a four-quadrant scatter plot of the calculation results. The four quadrants represent expected requirements, basic requirements, indifferent requirements, and attractive requirements respectively. 5) Present the above analysis results quantitatively in a three-dimensional four-quadrant space scatter plot in a centralized manner.

[0014] Further, step five specifically includes comprehensively comparing the data results of the three-party research, constructing a "government-visitor-resident" trinity framework for heritage interpretation and a method for systematically optimizing this interpretation system, and guiding the public and social transformation of heritage protection. Beneficial effects

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) From the perspective of the content of heritage interpretation, the present invention expands the main framework and discourse order of cultural heritage protection, and also improves the three-dimensional image of world cultural heritage, which has important significance and contemporary value for the public and social transformation of heritage protection.

[0016] (2) From the perspective of the way of heritage cognition, the present invention explores a more democratic and more local characteristic method for representing the social value of heritage, which helps to incorporate more diverse voices into the heritage discourse system and realize the public and social transformation of heritage protection.

[0017] (3) From the perspective of heritage management, the present invention points out that experts need to determine the heritage value from the perspective of managers and formulate corresponding protection and development strategies based on these values.

[0018] (4) From the perspective of heritage protection methods, the present invention guides the exploration from the public perspective of how local emotions and community memories construct the contemporary social value of heritage, thus moving towards the shaping of a more comprehensive and diverse heritage discourse system. Brief description of the drawings

[0019] Figure 1 : Flowchart of the method of the embodiment of the present invention.

[0020] Figure 2 . Heritage value evaluation system from the official perspective of the embodiment of the present invention.

[0021] Figure 3 . Two-dimensional analysis framework for heritage value evaluation from the official perspective of the embodiment of the present invention.

[0022] Figure 4. Semantic network analysis of three types of cultural heritage from the perspective of tourists in the embodiments of the present invention.

[0023] Figure 5 . Proportional area chart representing the cognitive differences of three types of cultural heritage at the overall level in the embodiments of the present invention.

[0024] Figure 6 . Spatial scope of the 15-minute living circle of the heritage community in the embodiments of the present invention.

[0025] Figure 7 . Semi-structured interview framework with scenario immersion in the embodiments of the present invention.

[0026] Figure 8 . Kano model impact index and demand type evaluation system in the embodiments of the present invention.

[0027] Figure 9 . Spatial ranking of the impact indicators of residents' heritage cognition in the embodiments of the present invention.

[0028] Figure 10 . Heritage interpretation system of the multi-agent cognitive model in the embodiments of the present invention Detailed implementation manners

[0029] The following further elaborates the operation method for the comprehensive optimization of the heritage interpretation system in the practical application of the present invention in combination with the accompanying drawings and specific implementation manners. Among them, the extraction of word frequencies from the official perspective is mainly based on the semantic network analysis software ROST CM6, the cognitive analysis from the tourist perspective is mainly based on the semantic network analysis software Ucinet 6 and the qualitative analysis software NVivo11, and the cognitive interpretation from the resident perspective is mainly based on the Kano model of user demand analysis. It should be noted that these implementation manners are not limitations to the present invention, and any equivalent transformation or substitution in terms of functions, methods, or structures made by those of ordinary skill in the art based on these implementation manners shall fall within the protection scope of the present invention.

[0030] Taking a certain cultural heritage as a specific case, it is elaborated as follows, and the method flow is as Figure 1 shown, and the present invention includes the following steps: Step 1: Combining the existing framework and theoretical basis, delimit the three parties, specifically: 1.1. Determine the limitations and problems of the existing framework for the instance.

[0031] 1.2. Divide the three parties, and determine their respective database sources and analysis methods.

[0032] Step 2: Mine the official text, construct a "policy - value" two-dimensional analysis framework for heritage value research, as Figure 2 、 Figure 3 shown, specifically: 2.1. The official perspective is divided into two regional dimensions: the world and the country. Among them, the text information from the world perspective comes from international official websites such as the World Heritage Centre and the Asia-Pacific World Heritage Network, and the text information from the country perspective comes from domestic official websites such as the website of the Central People's Government of the People's Republic of China, the National Cultural Heritage Administration, and the Chinese Academy of Cultural Heritage. Multiple official texts and policy documents are extracted. Considering the feasibility of increasing comparative analysis, both use the specific names of cultural heritage as keywords for in-site searches. After removing duplicate content and text mainly consisting of pictures, introductory and definitional articles are selected as the original analysis texts. Finally, the official text materials are respectively placed into the ROST-CM6 software for word frequency statistics, and the corresponding high-frequency words are extracted.

[0033] 2.2. Draw on the heritage value analysis framework based on the overall perspective to conduct heritage value analysis on cultural heritage from the official perspective. Count the word frequencies of the high-frequency words extracted in the previous step according to the framework classification and calculate the weights.

[0034] Specifically, the calculation of the weight of this method follows the following formula: Weight ω = frequency of words in a certain category / total word frequency Among them, the frequency of words in a certain category represents the sum of the occurrences of all high-frequency words belonging to this category, and the total word frequency is the total number of occurrences of high-frequency words in all categories. This weight value reflects the relative importance of a certain category in the overall corpus. The higher the weight, the more important the status of this category in the cultural heritage value analysis, indicating that it may receive more attention or have a higher priority from the official perspective.

[0035] 2.3. Summarize the heritage characteristics of cultural heritage from three aspects: form, relationship, and practice, and summarize them into three aspects: "heritage composition", "spiritual genealogy", and "symbiotic practice". For the interpretation of value types, from the world perspective, according to the inscription criteria established by the World Heritage Convention, and from the country perspective, according to the three classification criteria of historical value, artistic value, and scientific value defined by the Law of the People's Republic of China on the Protection of Cultural Relics, conduct value type interpretation. Determine the evaluation indicators by mining the high-frequency words in the official text, and calculate the indicator weights for quantitative value classification.

[0036] 2.4. Use the policy perspective as the X-axis and value assessment as the Y-axis to draw a two-dimensional analysis chart. Classify the high-frequency words statistically above according to value types and allocate areas according to weights.

[0037] Step 3: Extract digital footprints, couple semantic network information and geospatial information for classification, and comprehensively conduct tourism image main axis coding, as Figure 4 、 Figure 5 shown, specifically as follows: 3.1. Incorporate the scenic spots within the specific scope covered by Ctrip into the analysis scope. Using the names of each cultural heritage as keywords, search for review information of a specific year within the website. Conduct quantitative research on the correlation information between cultural heritages and other scenic spots by constructing a digital footprint corpus.

[0038] 3.2. Through repeated experiments, select the break point value with the most obvious structural characteristics of the recreation network. When the traffic between scenic spots is greater than or equal to the selected break point value, assign the value 1 to the original matrix unit, otherwise 0. Use the social network analysis software Ucinet 6 to calculate the centrality. In data analysis, the numerical distribution probability shows a regular trend within the interval of the mean ± k times σ (standard deviation). The 3σ criterion is commonly used as the standard for evaluating data distribution and detecting data anomalies under the normal distribution. Using the mean ± k times σ as the classification basis for continuous data, classify the heritage with a mean higher than the mean + 2σ as the core type, the heritage with a mean lower than the mean + σ as the marginal type, and the ones in between as the transitional type.

[0039] 3.3. The axial coding aims to conduct cluster analysis on the structured heritage cognitive information. Through secondary structure organization, sequentially classify the primary nodes of each type of cultural heritage into the axial categories constructed by multiple secondary nodes. The selection of coding is mainly based on lexical attributes, and conduct the third - level structural organization on the above - mentioned secondary nodes. The present invention classifies the above - mentioned secondary nodes into three third - level nodes: heritage characteristics, tourism image, and recreation experience according to the heritage interpretation theme. In the semantic network analysis software Ucinet 6, use the Netdraw function to draw a semantic network analysis diagram that can represent the influence of each attribute in the cognitive network of various cultural heritages.

[0040] 3.4. To more intuitively compare the differential representations of various cultural heritages in heritage cognition at the overall level, draw a proportional area chart for the above - mentioned axial coding results, and use the graphic areas of different colors to show the tourist cognitive attributes of the core - transitional - marginal three types of cultural heritages and the data sizes of each coding node.

[0041] Step Four: Conduct on - site interviews and introduce the KANO model to quantitatively divide the demand attributes of the identified heritage cognitive content, as Figure 6 , Figure 7 , Figure 8 , Figure 9 shown, specifically as: 4.1. The present invention centers around various cultural heritages and constructs a 15-minute living circle within the service scope of each heritage through traffic accessibility analysis in ArcGIS. Determine the number of communities included in the 15-minute living circle, count the respective numbers of old communities built before 2000 and new communities built after 2000, and calculate the sample quantity ratio of old communities to new communities. To avoid result deviation caused by a single type of surveyed community, the present invention sets the interview quantity for each type of community according to the quantity ratio of the two types of communities, and based on this, conducts scenario-based semi-structured interviews and questionnaire collection for residents of the two types of communities respectively.

[0042] The calculation formula for the interview quantity of each type is as follows: The interview quantity for a certain type of community = the total planned interviews × the quantity of the corresponding type of community / the total quantity of all communities.

[0043] 4.2. "Scenario substitution" mainly aims to understand the overall perception of residents towards cultural heritages from a macro level; "core interviews" analyze three tertiary nodes, namely heritage characteristics, tourism image, and recreation experience from the perspective of residents, based on the tertiary nodes obtained from the tourist perception coding in the previous part; "in-depth description" deeply explores according to the secondary nodes mentioned by residents in the open-ended answers to understand the impact of specific attributes on the overall perception. Based on the secondary nodes extracted from the tourist perception coding in this part, "recreation frequency" is added through preliminary research to enrich the indicators for the study of residents' heritage perception.

[0044] 4.3. To further quantitatively analyze residents' heritage perception of the three types of cultural heritages, the present invention introduces the Kano model proposed by Japanese scholar Noriaki Kano for questionnaire design and analysis. The Kano model is an analysis model for classifying and ranking the importance of user demand indicators. Based on this model, the questionnaire is designed in two parts: The first part is demographic characteristics, including information such as gender, age, length of residence, and type of residential community, etc.; the second part is Kano items, which establish an index system from the tertiary nodes and secondary nodes respectively, and set question options from both positive and negative aspects. Among them, the positive and negative question options can be classified into 5 types of attributes: Must-be Quality (M), One-dimensional Quality (O), Attractive Quality (A), Indifferent Quality (I), Reverse Quality (R). 60 questionnaires are distributed respectively in the communities served by the three types of cultural heritages, and finally a total of 180 pieces of research information including interview recordings and questionnaires are obtained, and the survey results are substituted into the Kano model to analyze the heritage perception of residents.

[0045] 4.4. The Kano model classifies and evaluates the influence of satisfaction by calculating coefficients for attribute values. The present invention calculates using the Better-Worse coefficient method proposed by Berger et al.

[0046] Better coefficient = (A + O) / (A + O + M + I) Worse coefficient = -(O + M) / (A + O + M + I) Among them, A, O, M, and I respectively refer to the attractive attributes, expected attributes, must-have attributes, and indifferent attributes in the above positive and negative question options.

[0047] Calculate the Better coefficient and Worse coefficient of the three types of cultural heritage respectively, and draw a four-quadrant scatter plot of the calculation results of the three types of cultural heritage. The nodes in the first quadrant point to expected demands, indicating the indicators that residents expect to have; the nodes in the second quadrant point to basic demands, indicating the indicators that residents think should be met; the nodes in the third quadrant point to indifferent demands, indicating the indicators with little impact on the heritage interpretation of residents; the nodes in the fourth quadrant point to attractive demands, indicating the indicators that exceed residents' expectations.

[0048] Step Five: Construct a "trinity" framework for heritage interpretation from the perspectives of the three parties to guide the public and social transformation of heritage protection, as Figure 10 shown, specifically as follows: 5.1. Compare and analyze the research results of the three main bodies of "official - tourist - resident" in Step Two, Step Three, and Step Four.

[0049] 5.2. Combining the "trinity" framework, and analyzing the three main bodies of "official - tourist - resident" with different value positions in Steps Two, Three, and Four, construct an optimization method for the heritage interpretation system based on the "official - tourist - resident" trinity cognitive model, and reach a consensus on heritage protection and generate an internal structural connection.

[0050] Inspired by the ideal embodiments of the present invention described above, through the above description, relevant staff can completely make various changes and modifications without departing from the technical idea of this invention. The technical scope of this invention is not limited to the content in the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. An optimization method for the heritage interpretation system based on the multi-agent cognitive model, characterized in that, Including the steps: Step 1: Define the three parties of the official, tourists, and residents; Step 2: Mine official texts and construct a two-dimensional analysis framework of "policy - value" for heritage value research; Step 3: Extract digital footprints, couple semantic network information and geospatial information for classification and comprehensively conduct the main axis coding of the tourism image; Step 4: Conduct on-site interviews and introduce the KANO model for quantitative division of the demand attributes of the identified heritage cognitive content; Step 5: Comprehensively construct an optimization method for the heritage interpretation system based on the "official - tourist - resident" trinity cognitive model from the perspectives of the three parties, guiding the public and social transformation of heritage protection.

2. The optimization method of the heritage interpretation system based on the multi-agent cognitive model according to claim 1, characterized in that Specifically, Step 1 includes analyzing multiple audiences and different perspectives of the heritage and defining the three parties of the official, tourists, and residents.

3. The method for optimizing the heritage interpretation system based on the multi-agent cognitive model according to claim 1, characterized in that Specifically, Step 2 includes mining information and performing numerical calculations on government public documents from the official perspective. By referring to the analysis framework of heritage value types, a two-dimensional analysis model of "policy - value" for authoritative heritage discourse analysis is constructed using the word frequency weight statistics method: 1) Select government public documents on official websites as the source of text materials, place the government public documents into the ROST-CM6 software for word frequency statistics, and extract the corresponding high-frequency words; 2) Divide the construction process of the indicator system of heritage value into three stages: heritage feature analysis, value type interpretation, and evaluation indicator determination, and construct a heritage value research framework; 3) Analyze heritage features from three aspects of form, relationship, and practice, conduct value type interpretation from the official perspective, and establish an evaluation system; 4) Construct a two-dimensional analysis framework with the policy perspective and value assessment as the x-axis and y-axis respectively to visually present the heritage value types from the official perspective.

4. The method for optimizing the heritage interpretation system based on the multi-agent cognitive model according to claim 3, characterized in that, In Step 1): The information from the superordinate perspective comes from international official websites, and relevant documents issued by evaluation organizations are extracted; the text materials from the high-level perspective come from domestic official websites.

5. The optimization method of the heritage interpretation system based on the multi-agent cognitive model according to claim 4, wherein, In Step 2): First, analyze heritage features from three aspects of form, relationship, and practice, and summarize them as three aspects of "heritage composition", "spiritual genealogy", and "symbiotic practice". On this basis, make characteristic supplements in combination with the characteristics of the heritage object, so as to conduct value type interpretation from the official perspective and establish an evaluation system; second, for value type interpretation, search from the superordinate perspective for the registration criteria established by the World Heritage Convention that the heritage object conforms to, and summarize its value characteristics; Conduct value type interpretation from the high-level perspective according to the three classification criteria of historical value, artistic value, and scientific value defined by the Law of the People's Republic of China on the Protection of Cultural Relics; finally, determine the evaluation indicators by mining the quantity and weight of high-frequency words in official texts, and calculate the indicator weights for quantitative value classification.

6. The optimization method of the heritage interpretation system based on the multi-agent cognitive model according to claim 1, wherein Specifically, Step 3 includes coupling semantic network information and geospatial information according to the spatial distribution and recreation popularity of tourists' digital footprints from the perspective of tourists, dividing cultural heritage into three types: core, transitional, and marginal, and applying the main axis coding technology to the qualitative interpretation of tourists' cognition following the grounded theory: 1) Use web crawler software to batch mine the tourism review information posted by tourists on tourism websites and construct a digital footprint corpus; 2) In ROST CM6 software, we established a dedicated vocabulary and defined a filtering vocabulary to conduct word frequency analysis and high-frequency word mining; we used social network analysis software Ucinet 6 to calculate the flow information between the heritages, and built a flow matrix with the name of the scenic spot as the basic unit. We compared the structural characteristics of the recreation network through multiple experiments, and selected appropriate breakpoint values ​​to binarize the assignment matrix; in order to characterize the importance of each scenic spot in the recreation network, we used social network analysis software Ucinet 6 to calculate the core degree, and selected the classification basis suitable for individual objects to determine the type of cultural heritage as marginal, transitional or core; 3) Using grounded theory to conduct hierarchical analysis of the digital footprint corpus, open coding, principal axis coding, and selective coding were performed simultaneously for multiple types of scenic spots in the text qualitative analysis software NVivo11, and on this basis, semantic network analysis was completed using Ucinet 6. In the semantic network analysis software Ucinet 6, the Netdraw function was used to draw a semantic network analysis diagram; 4) Use proportional area graphs to intuitively display the data size of various cognitive attributes and each coding node through graphic area.

7. The method for optimizing the heritage interpretation system based on the multi-agent cognitive model according to claim 1, wherein Step 4 specifically includes first determining the communities covered by the 15-minute living circle of each heritage attraction in the three types of heritage through traffic accessibility from the perspective of residents, and conducting semi-structured interviews and text semantic analysis. Then, the user demand analysis model KANO is used to quantitatively divide the demand attributes of the identified heritage cognitive content: 1) Using ArcGIS, we defined and constructed a 15-minute living circle within the service area of ​​each cultural heritage site through the traffic accessibility function, and counted the number and names of various communities within the scope; 2) Through the method of step-by-step and point-by-point mining, the situational semi-structured interview was conducted. The survey was divided into two parts: interview and questionnaire. The interview part guided the residents to express their views, and adopted the reverse analysis process opposite to the main axis coding of tourists' heritage cognition to improve the cognitive system framework. The questionnaire part introduced the Kano model, and the questionnaire design combined with the coding results in step 3 to score the degree of the questions set at each node, and conducted a preliminary survey to supplement the questionnaire questions based on the actual situation. 3) Distribute survey questionnaires, translate interview recordings, and perform text semantic analysis using a large language model; collect survey questionnaire information, conduct two-way reliability and validity tests on the questionnaire results using SPSS, and, based on the good structural validity of the questionnaire, perform quantitative statistics on the survey results corresponding to the necessary attributes M, desired attributes O, attractive attributes A, indifference attributes I, and reverse attributes R according to the Kano model attribute table, and substitute them into the Kano model for analysis; 4) Calculate using the Better-Worse coefficient method, where Better coefficient = (A+O) / (A+O+M+I), Worse coefficient = −(O+M) / (A+O+M+I); Calculate the distance from each node to the origin of the coordinate system to obtain the sensitivity value of each node, and draw a four-quadrant scatter plot of the calculation results. The four quadrants represent expected demand, basic demand, undifferentiated demand, and attractive demand respectively; 5) Quantitatively present the above analysis results centrally in a three-dimensional four-quadrant scatter plot.

8. The method for optimizing the heritage interpretation system based on the multi-agent cognitive model according to claim 1, wherein Step 5 specifically includes comprehensively comparing the data results of the three-party research, constructing a "government-visitor-resident" trinity framework for heritage interpretation and a method for systematically optimizing such an interpretation system, and guiding the public and social transformation of heritage protection.

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