Historical garden value evaluation method based on multi-source data analysis

Abstract

The invention discloses a historical garden value evaluation method based on multi-source data analysis, and belongs to the field of cultural heritage and historical garden protection, and the method comprises the steps: obtaining a historical garden related text; extracting a professional high-frequency word set in the historical garden related text; performing word meaning classification according to the professional high-frequency word set to obtain a historical garden value evaluation index set; determining a mutual influence degree matrix among the indexes according to the historical garden value evaluation index set; obtaining the weight of each index according to the mutual influence degree matrix among the indexes; and obtaining the score of each index of the to-be-evaluated historical garden, and performing weighted summation by using the weight of each index to obtain the value of the to-be-evaluated historical garden. The historical garden value evaluation method solves the problems that a traditional historical garden value evaluation method is few in data sample, high in individual subjectivity and insufficient in data coverage.

Description

Technical Field

[0001] The present invention belongs to the field of cultural heritage and historical garden protection, and particularly relates to a method for evaluating the value of historical gardens based on multi-source data analysis. Background Art

[0002] Under the background of the implementation of the cultural power strategy, the importance of the value of historical gardens has become prominent. The evaluation of the value of historical gardens aims to identify the excellent essence, the inappropriate or development-hindering parts, and the parts without preservation value in the value of historical gardens through the discrimination of the internal and external manifestations of the value of garden heritage, so as to provide a basis for formulating protection and management plans in the later stage. However, so far, the evaluation of the value of historical gardens still relies on traditional data obtained by methods such as literature analysis, on-site investigation, and questionnaire surveys. Scholars summarize evaluation factors based on existing evaluation studies and personal qualities, construct a value evaluation system, and then evaluate the value of historical gardens and propose corresponding protection strategies.

[0003] Traditional methods for evaluating the value of historical gardens have problems such as fewer data samples, strong personal subjectivity, and insufficient data coverage, resulting in an incomplete understanding of the value of historical gardens and the lack of a unified evaluation method. At the same time, due to the insufficient depth of the current historical garden value evaluation system, the protection research of historical gardens still mainly focuses on the analysis of protection cases and the proposal of protection strategies for single-type or single-case gardens, and a complete hierarchical protection mechanism has not been constructed yet. Summary of the Invention

[0004] In view of the above deficiencies in the prior art, the method for evaluating the value of historical gardens based on multi-source data analysis provided by the present invention solves the problems of fewer data samples, strong personal subjectivity, and insufficient data coverage existing in the traditional method for evaluating the value of historical gardens.

[0005] To achieve the above-mentioned invention purpose, the technical solution adopted by the present invention is: A method for evaluating the value of historical gardens based on multi-source data analysis, comprising:

[0006] Obtaining historical garden-related texts; extracting a set of professional high-frequency words from the historical garden-related texts; classifying the meanings of words according to the set of professional high-frequency words to obtain a set of historical garden value evaluation indicators; determining a mutual influence degree matrix between the indicators according to the set of historical garden value evaluation indicators; obtaining the weights of the indicators according to the mutual influence degree matrix between the indicators;

[0007] Obtaining the scores of each indicator of the historical garden to be evaluated, and performing weighted summation using the weights of the indicators to obtain the value of the historical garden to be evaluated.

[0008] Further, the expression of the mutual influence degree matrix between the indicators is:

[0009]

[0010] Among them, O is the mutual influence degree matrix; a 21 is the direct influence degree of index C 2 on index C 1 ; a 12 is the direct influence degree of index C 1 on index C 2 ; a n1 is the direct influence degree of index C n on index C 1 ; a 1n is the direct influence degree of index C 1 on index C n ; a n2 is the direct influence degree of index C n on index C 2 ; a 2n is the direct influence degree of index C 2 on index C n ; C n is the nth index; n is the total number of indexes.

[0011] Furthermore, obtaining the weights of each index according to the mutual influence degree matrix between each index is specifically as follows:

[0012] Performing a normalization process on the mutual influence degree matrix between each index to obtain a normalized direct influence matrix;

[0013] Multiplying the normalized direct influence matrix by itself to obtain a comprehensive influence matrix;

[0014] Performing a separate normalization process on each column of the comprehensive influence matrix to obtain a weighted matrix of historical garden evaluation indexes;

[0015] Multiplying the weighted matrix of historical garden evaluation indexes by itself multiple times until the multiplication result converges to obtain a limit weighted supermatrix;

[0016] Taking the values in the limit weighted supermatrix as the weights of the corresponding evaluation indexes.

[0017] Furthermore, the expression of the normalized direct influence matrix is:

[0018]

[0019] Among them, P is the normalized direct influence matrix; a ij is the direct influence degree of index C i on index C j ; O is the mutual influence degree matrix; n is the total number of indexes; i and j are both index numbers.

[0020] Furthermore, the expression of the comprehensive influence matrix is as follows:

[0021]

[0022] Where T is the comprehensive influence matrix; n is the total number of indicators; i is the indicator number; and P is the normalized direct influence matrix.

[0023] The beneficial effects of the present invention are as follows: The present invention expands the data support scope for obtaining the original garden value evaluation indicators, weakens the personal influence factors brought by the traditional evaluation system construction and indicator allocation based on the subjective judgment of researchers, and constructs a more objective, comprehensive and scientific historical garden value evaluation system through the combined use of traditional data and big data. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] Figure 1 It is a model diagram of the historical garden value index selection mechanism of the present invention.

[0025] Figure 2 It is a model diagram of the historical garden value evaluation model in the embodiment of the present invention.

[0026] Figure 3 It is a structural diagram of the graded protection strategy system of historical gardens in Chengdu in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] The following describes the specific embodiments of the present invention to facilitate those skilled in the art to understand the present invention. However, it should be clear that the present invention is not limited to the scope of the specific embodiments. For those of ordinary skill in the art, as long as various changes are within the spirit and scope of the present invention defined and determined by the appended claims, these changes are obvious, and all inventions and creations using the concept of the present invention are within the scope of protection.

[0028] As Figure 1 and Figure 2 shown, in an embodiment of the present invention, a method for evaluating the value of historical gardens based on multi-source data analysis includes:

[0029] Obtain historical garden-related texts; extract a set of professional high-frequency words from the historical garden-related texts; classify the meanings according to the set of professional high-frequency words to obtain a set of historical garden value evaluation indicators; determine the mutual influence degree matrix between the indicators according to the set of historical garden value evaluation indicators; and obtain the weights of the indicators according to the mutual influence degree matrix between the indicators.

[0030] Obtain the scores of each indicator of the historical garden to be evaluated, and perform weighted summation using the weights of the indicators to obtain the value of the historical garden to be evaluated.

[0031] In this embodiment, the acquisition of historical garden-related texts includes: using the name of the historical garden as a keyword to obtain relevant paper texts and online review texts in journal paper databases, travel websites, and social media platforms.

[0032] In this embodiment, with the help of the text mining tool ROST CM6 software, text mining technology is used to clean and extract the two types of texts. By constructing a custom word list for the historical garden, professional high-frequency words that can reflect the internal and external value representations of the historical garden are extracted. Through manual screening, the professional high-frequency words are merged and classified according to their meanings, the concerns about the content of the historical garden reflected in the two types of texts are extracted, and the value composition of the historical gardens in Chengdu is refined according to the classified concern content.

[0033] Refine the historical garden value evaluation indicators according to the professional high-frequency word set, including the target layer, first-level indicators, and second-level indicators. The specific implementation process is as follows:

[0034] According to the extracted professional high-frequency words and in combination with relevant domestic and foreign documents on the value evaluation of historical gardens, determine the value indicators of the historical gardens in Chengdu, including the target layer, 8 first-level indicators, and 33 second-level indicators. See Table 1 for details.

[0035] Table 1 Historical Garden Value Evaluation Indicators in Chengdu

[0036]

[0037]

[0038] The expression of the mutual influence degree matrix between the indicators is:

[0039]

[0040] Among them, O is the mutual influence degree matrix; a 21 is the direct influence degree of indicator C 2 on indicator C 1 ; a 12 is the direct influence degree of indicator C 1 on indicator C 2 ; a n1 is the direct influence degree of indicator C n on indicator C 1 ; a 1n is the direct influence degree of indicator C 1 on indicator C n ; a n2 is the direct influence degree of indicator C n on indicator C 2 ; a 2n is the direct influence degree of indicator C 2 on indicator C nThe direct influence degree; C n is the nth index; n is the total number of indices.

[0041] In this embodiment, 15 experts in the field of historical garden and cultural heritage protection are selected, and the "1-4" scale method is adopted, that is, index C i for C j Absolutely no influence is 0 points, weak influence is 1 point, moderate influence is 2 points, strong influence is 3 points, and extremely strong influence is 4 points, to determine the mutual influence relationship between each index. Or, use the multivariate correlation analysis method to solve the influence relationship between each index.

[0042] The weights of each index are obtained according to the mutual influence degree matrix between each index, specifically:

[0043] Perform a normalization process on the mutual influence degree matrix between each index to obtain a normalized direct influence matrix;

[0044] Multiply the normalized direct influence matrix by itself to obtain a comprehensive influence matrix;

[0045] Perform a separate normalization process on each column of the comprehensive influence matrix to obtain a weighted matrix of historical garden evaluation indices;

[0046] Multiply the weighted matrix of historical garden evaluation indices by itself multiple times until the multiplication result converges to obtain a limit weighted supermatrix;

[0047] Take the values in the limit weighted supermatrix as the weights of the corresponding evaluation indices.

[0048] The expression of the normalized direct influence matrix is:

[0049]

[0050] where P is the normalized direct influence matrix; a ij is the index C i on the index C j The direct influence degree; O is the mutual influence degree matrix; n is the total number of indices; i and j are both index numbers.

[0051] The expression of the comprehensive influence matrix is:

[0052]

[0053] where T is the comprehensive influence matrix; n is the total number of indices; i is the index number; P is the normalized direct influence matrix.

[0054] Further use the formula Multiply the normalized matrix by itself to make all the values in the P matrix tend to 0, and obtain the comprehensive influence matrix T. As shown in Table 2 and Table 3.

[0055] Table 2 Comprehensive Influence Matrix among the First-Level Indicators of the Value Evaluation of Chengdu's Historical Gardens

[0056] <![CDATA[S 1 > <![CDATA[S 2 > <![CDATA[S 3 > <![CDATA[S 4 > <![CDATA[S 5 > <![CDATA[S 6 > <![CDATA[S 7 > <![CDATA[S 8 > <![CDATA[S 9 > <![CDATA[S 1 > 0.493 0.724 0.588 0.672 0.702 0.565 0.725 0.738 0.563 <![CDATA[S 2 > 0.591 0.563 0.57 0.649 0.685 0.55 0.708 0.701 0.545 <![CDATA[S 3 > 0.519 0.623 0.432 0.615 0.612 0.488 0.665 0.65 0.484 <![CDATA[S 4 > 0.519 0.644 0.546 0.495 0.64 0.492 0.681 0.662 0.517 <![CDATA[S 5 > 0.484 0.579 0.467 0.527 0.483 0.496 0.636 0.574 0.451 <![CDATA[S 6 > 0.374 0.443 0.373 0.412 0.489 0.31 0.496 0.471 0.38 <![CDATA[S 7 > 0.453 0.511 0.449 0.49 0.559 0.453 0.471 0.541 0.438 <![CDATA[S 8 > 0.567 0.668 0.548 0.617 0.657 0.519 0.693 0.557 0.531 <![CDATA[S 9 > 0.330 0.38 0.319 0.358 0.391 0.322 0.415 0.394 0.259

[0057] Table 3 Comprehensive Influence Matrix among the Second-Level Indicators of the Value Evaluation of Chengdu's Historical Gardens

[0058]

[0059]

[0060] According to the comprehensive influence matrix, using the formula f i represents the degree of being influenced, that is, the sum of the values in each column of the matrix P; e i represents the comprehensive influence degree of each column element on other elements, and then calculates the influence degree, the degree of being influenced, the centrality, and the reason degree of each index of Chengdu's historical gardens, and constructs the network structure of the value evaluation of Chengdu's historical gardens.

[0061] Perform separate normalization processing on each column of the comprehensive influence matrix to obtain the weighted matrix of the evaluation indexes of Chengdu's historical gardens. Multiply the weighted matrix by itself multiple times to make the product values in the matrix tend to be unique, so as to obtain the limit weighted supermatrix, and finally obtain the corresponding weights of each evaluation index of the value evaluation of Chengdu's historical gardens. As shown in Table 4.

[0062] Table 4 Weights of the Value Evaluation Indexes of Chengdu's Historical Gardens

[0063]

[0064]

[0065] This embodiment provides a hierarchical protection system for historical gardens based on value evaluation, which specifically includes the following steps:

[0066] S1. Establish a hierarchical evaluation standard system for Chengdu's historical gardens. According to the index weights, determine the evaluation scores of each index in a hundred-mark system to form a hierarchical evaluation standard system for historical gardens.

[0067] S2. Conduct the value evaluation of historical gardens. According to the evaluation criteria, divide the answers to each value evaluation question into five levels: very agree, relatively agree, medium, relatively disagree, and very disagree through a questionnaire survey, corresponding to the scores 1, 0.75, 0.5, 0.25, and 0 respectively. Statistically analyze the questionnaire survey data, calculate the average of the total data of each value evaluation index and then multiply it by the weight of each index, and finally add them up to obtain the value scores and total scores of different categories of each garden. As shown in Table 5.

[0068] Table 5 Results of Value Scoring for Each Historical Garden in Chengdu

[0069]

[0070] S3. Determine the garden levels and formulate protection strategies for each level. After determining the value scores of historical gardens, determine the levels of each historical garden according to the grading criteria, and then determine the protection strategies for historical gardens at each level.

[0071] In step S3, the specific steps include:

[0072] S301. On the basis of referring to other relevant literature materials, regulatory documents and expert opinions on the hierarchical protection of cultural heritage, and integrating the characteristics of historical gardens in Chengdu and people's cognitive habits, determine the grading criteria for historical gardens and complete the grading of historical gardens in Chengdu. As shown in Tables 6 and 7.

[0073] Table 6 Grading Criteria and Grading Characteristics of Historical Gardens

[0074]

[0075]

[0076]

[0077] Table 7 Grading Results of Historical Gardens in Chengdu

[0078] Garden Name Value Level Qingshan Mountain Taoist Temple Garden Group First Level Du Fu Thatched Cottage First Level Wuhou Memorial Temple First Level Wenshu Monastery Second Level Yanhua Pond Second Level Xindu Osmanthus Lake Second Level Xinfan East Lake Second Level Baoguang Temple Third Level Chengdu People's Park Third Level Wangjiang Tower Garden Third Level Qingyang Palace Third Level Zhaojue Temple Third Level Wangcong Temple Garden Fourth Level Dayi Liu's Manor Fourth Level

[0079] S302. Based on the value judgment of historical gardens, and integrating the advantages and disadvantages of gardens at each level and relevant domestic and international protection documents, construct a hierarchical protection system for historical gardens in Chengdu from two levels: general protection strategies and targeted protection strategies. Among them, the targeted protection strategy system is further developed from four aspects: protection of cultural relics and historic sites, protection of built environment, protection of cultural attributes, and management guarantee. As Figure 3 shown.

[0080] In summary, the advantages of the present invention may include: By using the method for evaluating the value of historical gardens based on multi-source data analysis established in the present invention, the data support scope for obtaining the original garden value evaluation indicators can be expanded, the personal influence factors brought by the traditional evaluation system construction and index allocation based on the subjective judgment of researchers can be weakened, and the value content of historical gardens can be excavated more comprehensively, objectively and deeply; at the same time, a hierarchical protection system for historical gardens is provided supported by this value evaluation method, which can effectively propose corresponding protection intensities and protection methods according to the characteristics of gardens at different levels, and provide methods and basis for formulating historical garden protection policies and proposing protection measures.

Claims

1. A method for evaluating the value of historical gardens based on multi-source data analysis, characterized in that: include: Obtaining historical garden-related texts; extracting a set of professional high-frequency words from historical garden-related texts; According to the professional high-frequency word set, the word meaning is classified to obtain the historical garden value evaluation index set; according to the historical garden value evaluation index set, the mutual influence degree matrix between the indicators is determined; according to the mutual influence degree matrix between the indicators, the weight of each indicator is obtained; The scores of each indicator of the historical garden to be evaluated are obtained, and the weights of each indicator are used for weighted summation to obtain the value of the historical garden to be evaluated.

2. The historical garden value evaluation method based on multi-source data analysis according to claim 1 is characterized in that: The expression of the mutual influence degree matrix between the indicators is: Among them, O is the mutual influence degree matrix; a 21 is the direct impact of indicator C2 on indicator C1; a 12 is the direct impact of indicator C1 on indicator C2; a n1 C n The degree of direct impact on indicator C1; a 1n For index C1 to index C n The degree of direct impact; n2 C n The degree of direct impact on indicator C2; a 2n C2 is the index of C n The degree of direct impact; n is the nth indicator; n is the total number of indicators.

3. The historical garden value evaluation method based on multi-source data analysis according to claim 1 is characterized in that: The weight of each indicator is obtained according to the mutual influence degree matrix between the indicators, which is specifically: The mutual influence degree matrix between each indicator is normalized to obtain the normalized direct influence matrix; Multiply the normalized direct impact matrix by itself to obtain the comprehensive impact matrix; Each column of the comprehensive impact matrix is ​​normalized separately to obtain the weighted matrix of historical garden evaluation indicators; The weighted matrix of historical garden evaluation indexes is multiplied by itself many times until the result of the multiplication converges to obtain the limit weighted supermatrix. The values ​​in the extreme weighted supermatrix are used as the weights of the corresponding evaluation indicators.

4. The historical garden value evaluation method based on multi-source data analysis according to claim 3 is characterized in that: The normalization directly affects the expression of the matrix: Where P is the normalized direct influence matrix; a ij C i For indicator C j is the degree of direct influence; O is the mutual influence matrix; n is the total number of indicators; i and j are the indicator numbers.

5. The historical garden value evaluation method based on multi-source data analysis according to claim 3 is characterized in that: The expression of the comprehensive impact matrix is: Among them, T is the comprehensive impact matrix; n is the total number of indicators; i is the indicator number; and P is the normalized direct impact matrix.

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