Method for identifying associated immovable cultural relic groups and multi-attribute structures

Abstract

A method for identifying associated immovable cultural relic groups and multi-attribute structures, wherein the method comprises: acquiring information about each immovable cultural relic within a target geographical area (101); extracting features of a first attribute from the information about each immovable cultural relic to generate structured data regarding the first attribute (102); constructing a first connection relationship network on the basis of the structured data regarding the first attribute (103); identifying at least one immovable cultural relic group in the first connection relationship network (104); and determining a key cultural relic in the immovable cultural relic group, and generating multi-attribute structures of the immovable cultural relics within the target geographical area (105).

Description

A method for identifying interconnected immovable cultural relic groups and their multi-attribute structures.

[0001] Cross-references to related applications

[0002] This disclosure claims priority to Chinese Patent Application No. 202411571115.6, filed on November 5, 2024, entitled "A Method for Identifying A Group of Related Immovable Cultural Relics and a Multi-Attribute Structure", the entire contents of which are incorporated herein by reference. Technical Field

[0003] This disclosure relates to the fields of historical and cultural heritage protection planning and data technology, and in particular to a method for identifying a group of related immovable cultural relics and a multi-attribute structure. Background Technology

[0004] Immovable cultural relics refer to ancient cultural sites, ancient tombs, ancient buildings, grottoes and stone carvings, murals, important modern historical sites, and representative buildings. In most cases, different immovable cultural relics have spatial, cultural, and functional connections, forming interconnected groups of immovable cultural relics. This interconnectedness is a crucial relationship among immovable cultural relics, and identifying interconnected groups of immovable cultural relics is of great significance for the value discovery and inheritance, overall protection, and display and utilization of immovable cultural relics. Due to large-scale and rapid urban renewal and construction, interconnected groups of immovable cultural relics and their structures are gradually buried in modern urban spaces, making them difficult to identify.

[0005] In historical and cultural heritage protection planning, related groups of immovable cultural relics are an important target of cultural heritage protection and utilization planning. Therefore, the identification of related groups of immovable cultural relics covering a large geographical area and involving a large number of immovable cultural relics is an important aspect and has significant implications for the overall protection and utilization of cultural heritage.

[0006] For the identification of interconnected immovable cultural relic clusters, existing technologies mainly employ manual identification and kernel density estimation methods. Kernel density estimation, based on kernel density calculations to visualize the clustering of immovable cultural relic clusters, cannot quantitatively analyze the relationships between immovable cultural relics, making it difficult to accurately identify the scope and characteristics of immovable cultural relic clusters and their structures, and thus failing to provide detailed information. Consequently, it struggles to accurately reveal the implicit geographical and cultural-historical patterns of immovable cultural relic clusters. Manual identification involves professionals studying historical materials to trace the relationships between immovable cultural relics, thereby identifying interconnected clusters. However, this method is only suitable for a small number of immovable cultural relics within a relatively small geographical area, requires a significant amount of time, and has low efficiency. Furthermore, due to its reliance on manual labor, this method is prone to omissions during the process of tracing interconnected immovable cultural relics, and subjective uncertainties exist, leading to inaccuracies. For the identification of interconnected immovable cultural relic clusters over larger geographical areas, involving a large amount of data, existing technologies are ineffective in terms of accuracy and revealing implicit structures, failing to meet planning requirements. Summary of the Invention

[0007] In view of this, this disclosure proposes a method, device, electronic device, and storage medium for identifying associated immovable cultural relic groups and multi-attribute structures.

[0008] According to one aspect of this disclosure, a method for identifying associated immovable cultural relic groups and multi-attribute structures is provided, the method comprising:

[0009] Obtain information on each immovable cultural relic within the target geographical area; the information on the immovable cultural relic includes one or more of the following: name, geographical location, age, type, ownership, historical and cultural information, natural environment information, and social environment information;

[0010] Extract the first attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the first attribute; the first attribute includes any one of the following: geographical location, age, type, ownership, and historical culture;

[0011] Based on the structured data about the first attribute, a first connection network is constructed; wherein, in the first connection network, each immovable cultural relic is taken as a node, and the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes about the first attribute.

[0012] At least one group of immovable cultural relics was identified in the first connection network;

[0013] Identify the core cultural relics in the at least one group of immovable cultural relics, and based on the core cultural relics in the at least one group of immovable cultural relics, generate a structure of multiple attributes for the immovable cultural relics within the target geographical area.

[0014] In one possible implementation, constructing the first connection network based on the structured data regarding the first attribute includes:

[0015] Based on the structured data regarding the first attribute, the connection relationships regarding the first attribute among the immovable cultural relics within the target geographical area are determined;

[0016] Based on the first attribute characteristics of each immovable cultural relic, calculate the weight value corresponding to the connection relationship between each immovable cultural relic with respect to the first attribute;

[0017] The first connection relationship network is constructed by using each immovable cultural relic as a node and the weight value corresponding to the connection relationship between each immovable cultural relic with respect to the first attribute as the weight value of the edge.

[0018] In one possible implementation, determining the core cultural relics within the at least one group of immovable cultural relics, and generating a structure of multiple attributes for immovable cultural relics within the target geographical area based on the core cultural relics within the at least one group of immovable cultural relics, includes:

[0019] Extract the second attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the second attribute;

[0020] Based on the structured data regarding the second attribute, a second connection network is constructed; wherein, in the second connection network, each immovable cultural relic is taken as a node, and the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes regarding the second attribute;

[0021] Based on the first connection network and / or the second connection network, determine the core cultural relics in the at least one group of immovable cultural relics;

[0022] Based on the core cultural relics in the at least one group of immovable cultural relics, the structure of immovable cultural relics within the target geographical area regarding multiple attributes is obtained; wherein, the multiple attributes include the first attribute and the second attribute.

[0023] In one possible implementation, determining the core artifacts within the at least one group of immovable cultural relics based on the first connection network and / or the second connection network includes:

[0024] For any group of immovable cultural relics, based on the first connection network, the weight values ​​corresponding to each edge in the first connection network, the second connection network, and the weight values ​​corresponding to each edge in the second connection network, the sum of the eigenvector centrality of each immovable cultural relic in the first connection network and the eigenvector centrality of each immovable cultural relic in the second connection network is calculated; the immovable cultural relic with the highest sum is determined as the core cultural relic in the group of immovable cultural relics.

[0025] In one possible implementation, each group of immovable cultural relics contains a core cultural relic;

[0026] The process of obtaining the structure of immovable cultural relics with respect to multiple attributes within the target geographical area based on core cultural relics in at least one group of immovable cultural relics includes:

[0027] Based on the connection relationship between each immovable cultural relic in the at least one immovable cultural relic group regarding the second attribute, establish the connection relationship between the core cultural relics in the at least one immovable cultural relic group;

[0028] The sum of the weight values ​​corresponding to each immovable cultural relic in the at least one immovable cultural relic group shall be used as the weight value corresponding to the connection relationship between the core cultural relics in the at least one immovable cultural relic group.

[0029] Based on the at least one group of immovable cultural relics, the connection relationships between the core cultural relics in the at least one group of immovable cultural relics, and the weight values ​​corresponding to the connection relationships between the core cultural relics in the at least one group of immovable cultural relics, a structure of immovable cultural relics with respect to multiple attributes within the target geographical area is generated.

[0030] In one possible implementation, after calculating the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute, the method further includes:

[0031] Statistical analysis is performed on the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute to determine the critical weight values;

[0032] Among the weight values ​​corresponding to the connection relationship of the first attribute among the immovable cultural relics, weight values ​​that are less than the critical weight value are filtered out.

[0033] The step of constructing the first connection relationship network by using each immovable cultural relic as a node and the weight value corresponding to the connection relationship between each immovable cultural relic with respect to the first attribute as the weight value of the edge includes:

[0034] The first connection relationship network is constructed by using each immovable cultural relic as a node and the weight value corresponding to the connection relationship between the filtered immovable cultural relics with respect to the first attribute as the weight value of the edge.

[0035] In one possible implementation, the method further includes: visualizing the structure of the first connection network, the at least one group of immovable cultural relics, and the multiple attributes.

[0036] According to another aspect of this disclosure, a device for identifying associated immovable cultural relic groups and multi-attribute structures is provided, the device comprising:

[0037] The acquisition module is used to acquire information on each immovable cultural relic within the target geographical area; the information on the immovable cultural relic includes one or more of the following: name, geographical location, age, type, ownership, historical and cultural information, natural environment information, and social environment information;

[0038] An extraction module is used to extract the first attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the first attribute; the first attribute includes any one of the following: geographical location, age, type, ownership, and historical culture;

[0039] A connection relationship construction module is used to construct a first connection relationship network based on the structured data about the first attribute; wherein, in the first connection relationship network, each immovable cultural relic is used as a node, and the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes about the first attribute.

[0040] The identification module is used to identify at least one group of immovable cultural relics in the first connection network;

[0041] A multi-attribute structure construction module is used to identify the core cultural relics in the at least one group of immovable cultural relics, and based on the core cultural relics in the at least one group of immovable cultural relics, generate a structure of immovable cultural relics with respect to multiple attributes within the target geographical area.

[0042] According to another aspect of this disclosure, an electronic device is provided, comprising: a processor; a memory for storing processor-executable instructions; wherein the processor is configured to implement the above-described method when executing instructions stored in the memory.

[0043] According to another aspect of this disclosure, a non-volatile computer-readable storage medium is provided that stores computer program instructions thereon, wherein the computer program instructions, when executed by a processor, implement the above-described method.

[0044] According to another aspect of this disclosure, a computer program product is provided, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the above-described method.

[0045] Information on immovable cultural relics within a target geographical area is obtained through various aspects of this disclosure. This information includes one or more of the following: name, geographical location, age, type, ownership, historical and cultural information, natural environment information, and social environment information. A first attribute feature is extracted from the information of each immovable cultural relic, generating structured data about the first attribute. The first attribute includes any one of the following: geographical location, age, type, ownership, and historical and cultural information. Based on the structured data about the first attribute, a first connection network is constructed. In this first connection network, each immovable cultural relic is a node, and the weight value of the edge connecting two nodes is determined by the strength of the correlation between the two nodes regarding the first attribute. At least one group of immovable cultural relics is identified in the first connection network. In this way, by representing immovable cultural relics from multiple dimensions through key attribute extraction, structured data on key attributes of immovable cultural relics is generated, thereby ensuring the accuracy and comprehensiveness of the constructed first connection relationship network. Furthermore, it is possible to achieve quantitative, efficient, accurate, and automatic identification of related immovable cultural relic groups based on the correlation between various immovable cultural relics under the same key attribute, and to fuse the generated immovable cultural relic groups with multiple attributes based on core cultural relics to obtain the structure of multiple attributes. Thus, it reveals the implicit structure of immovable cultural relics in the target area in terms of geospatial, cultural, and historical aspects.

[0046] The above description is merely an overview of the technical solution disclosed herein. In order to better understand the technical means of this disclosure and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this disclosure more apparent and understandable, specific embodiments of this disclosure are described below. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments or related technologies of this disclosure, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0048] Figure 1 schematically illustrates a flowchart of a method for identifying an associated group of immovable cultural relics and a multi-attribute structure according to an embodiment of the present disclosure; and

[0049] Figure 2 schematically illustrates an undirected weighted graph G representing the connection relationships of a target geographical area according to an embodiment of the present disclosure. j A schematic diagram; and

[0050] Figure 3 schematically illustrates a visualization of a connection network covering a target geographical area according to an embodiment of the present disclosure; and

[0051] Figure 4 schematically illustrates the identification results of a group of associated immovable cultural relics within a target geographical area according to an embodiment of this disclosure; and

[0052] Figure 5 schematically illustrates the mapping of the identification results of the associated immovable cultural relic group within a target geographical area according to an embodiment of the present disclosure in geospatial space; and

[0053] Figure 6 schematically illustrates a flowchart of a method for identifying an associated group of immovable cultural relics and a multi-attribute structure according to an embodiment of this disclosure; and

[0054] Figure 7 schematically illustrates a diagram of an immovable cultural relic structure within a target geographical area according to an embodiment of the present disclosure; and

[0055] Figure 8 schematically illustrates a flowchart of a method for identifying an associated group of immovable cultural relics and a multi-attribute structure according to an embodiment of this disclosure; and

[0056] Figure 9 schematically illustrates a flowchart of a method for identifying an associated group of immovable cultural relics and a multi-attribute structure according to an embodiment of this disclosure; and

[0057] Figure 10 schematically illustrates a diagram of the multi-attribute structure of immovable cultural relics within a target geographical area according to an embodiment of the present disclosure; and

[0058] Figure 11 schematically illustrates the structure of an associated immovable cultural relic group and a multi-attribute structure identification device according to an embodiment of the present disclosure; and

[0059] Figure 12 schematically illustrates a block diagram of an electronic device 1900 according to an embodiment of the present disclosure; and

[0060] Figure 13 schematically illustrates a block diagram of a computational processing apparatus for performing a method for identifying an associated immovable cultural relic complex and a multi-attribute structure according to the present disclosure; and

[0061] Figure 14 schematically illustrates a storage unit for holding or carrying program code that implements a method for identifying an associated immovable cultural relic group and a multi-attribute structure according to the present disclosure. Specific Implementation

[0062] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, and not all embodiments. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0063] Figure 1 shows a flowchart of a method for identifying an associated group of immovable cultural relics and a multi-attribute structure according to an embodiment of the present disclosure. Exemplarily, this method can be executed by a device with data processing capabilities, such as a processor, server, terminal, etc. As shown in Figure 1, the method may include the following steps:

[0064] Step 101: Obtain information on each immovable cultural relic within the target area; the information on the immovable cultural relic includes one or more of the following: name, geographical location, age, type, ownership, historical and cultural information, natural environment information, and social environment information.

[0065] The target area can be set according to needs. For example, the target area can be determined based on the planning area selected by the user. There are no restrictions on the size of the target area or the number of immovable cultural relics included within the target area. For example, the target area can be one district (county). It should be noted that the target area must contain at least one immovable cultural relic.

[0066] Immovable cultural relics refer to cultural relics that are geographically fixed and cannot or should not be moved; for example, ancient cultural sites, ancient tombs, ancient buildings, grottoes and stone carvings, murals, important modern historical sites, and representative buildings are all immovable cultural relics.

[0067] As an example, for any immovable cultural relic, its information includes: the name of the immovable cultural relic, its geographical location (including address and geographic coordinates), its age, type, ownership, historical and cultural information, natural environmental information, and social environmental information. The historical and cultural information may include: the relic's physical style, related historical figures and stories, and the historical and cultural connotations it represents. The natural environmental information may include: the natural geographical conditions and climate type of the relic's location. The social environmental information may include: the type of space, community name, and transportation conditions of the relic's location. For example, the name, address, age, type, and ownership of the immovable cultural relic can be obtained from publicly available information or from cultural relic departments based on the administrative regions included in the target area. Geographic coordinates can be obtained by searching for the address on a map and using a coordinate picking tool. Alternatively, information such as a brief introduction to the immovable cultural relic can be obtained through the internet, books, databases, or by applying to cultural relic departments.

[0068] For example, the information of immovable cultural relics can be in different forms such as text, images, videos, and audio, without limitation.

[0069] In one possible implementation, all immovable cultural relics within the target geographical area can be included in the immovable cultural relics dataset H = [h i [(i = 1, 2, ..., M); where M represents the number of immovable cultural relics within the target area, i represents the index of the immovable cultural relic, h... i This represents the i-th immovable cultural relic within the target area.

[0070] Step 102: Extract the first attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the first attribute; the first attribute includes any one of the following: geographical location, age, type, ownership, and historical culture.

[0071] Among them, attributes refer to the inherent properties of things, which are their basic characteristics. Attributes with high importance are called key attributes, and can be selected from multiple preset attributes (including but not limited to geographical location, era, type, ownership, and historical culture) as needed. As an example, an attribute dataset P = [p j (j = 1, 2, ..., N), where N represents the number of preset key attributes, j represents the key attribute index, and p j This represents the j-th key attribute; any key attribute can be selected from the attribute dataset P as the first attribute.

[0072] Among them, the structured data of attribute features are called attribute values. For example, for any immovable cultural relic, the geographical location attribute feature indicates the longitude and latitude of the immovable cultural relic; the historical and cultural attribute feature indicates the historical and cultural connotation that the immovable cultural relic can express, such as cultural themes (such as red culture), historical events, historical figures, etc.; the chronological attribute feature indicates the construction date of the immovable cultural relic; the type attribute feature indicates which type of immovable cultural relic it belongs to, such as ancient cultural sites, ancient tombs, ancient buildings, grottoes and stone carvings, murals, important modern historical sites, representative buildings, etc.; and the ownership attribute feature indicates the entity to which the immovable cultural relic belongs.

[0073] The information on immovable cultural relics obtained above is unstructured data containing multiple elements such as geography, history, and culture; however, the data structure of this unstructured data is irregular or incomplete, making it inconvenient to represent using a two-dimensional logical table in a database. Therefore, in this step, for any immovable cultural relic within the target geographical area, the first attribute feature of the immovable cultural relic is extracted from its information. Then, based on each immovable cultural relic within the target geographical area and its first attribute feature, structured data about the first attribute is constructed. Structured data refers to information stored in a fixed format or pattern, which can usually be quickly retrieved and processed. Structured data can also be called databases, row data, etc. In this way, the unstructured data of immovable cultural relic information is converted into structured data containing the first attribute, enabling more rapid and efficient subsequent processing.

[0074] For example, existing methods can be used to extract attribute features. For instance, for information on immovable cultural relics in text form, language fragments or keywords describing the first attribute can be automatically identified and extracted from the text, thereby extracting the features of the first attribute.

[0075] As an example, we can select the key attribute p from the attribute dataset P. j As the first attribute; for any immovable cultural relic h in the immovable cultural relic dataset H. i That is, any immovable cultural relic within the target area, from that immovable cultural relic h i Extracting immovable cultural relics from information h i Regarding the key attribute p j The key attribute features; correspondingly, it is possible to traverse all key attributes in the attribute dataset P and all immovable cultural relics in the immovable cultural relics dataset H, thereby extracting the features of all immovable cultural relics in the immovable cultural relics dataset H related to each key attribute in the attribute dataset P, and storing them in the attribute feature dataset X = [x ij(i = 1, 2, ..., M; j = 1, 2, ..., N), where i and j represent the indices of immovable cultural relics and key attributes, respectively, and x ij Let X represent the j-th key attribute feature of the i-th immovable cultural relic, M represent the number of immovable cultural relics within the target area, and N represent the number of preset key attributes; the attribute feature dataset X contains structured data about each key attribute.

[0076] Step 103: Based on the structured data about the first attribute, construct a first connection network; wherein, in the first connection network, each immovable cultural relic is a node, and the weight value of the edge connecting two nodes is determined by the strength of the correlation between the two nodes about the first attribute.

[0077] As an example, the first connection network can be a weighted undirected graph, which includes nodes, edges connecting nodes, and weight values ​​corresponding to the edges. Each immovable cultural relic within the target geographical area is a node in the weighted undirected graph. The line connecting the nodes of two immovable cultural relics that are related with respect to the first attribute is an edge. Each edge represents the connection relationship between immovable cultural relics. The weight value corresponding to the edge is used to characterize the strength of the correlation between the nodes at both ends of the edge with respect to the first attribute, that is, the strength of the correlation between the two immovable cultural relics corresponding to the nodes at both ends of the edge.

[0078] In one possible implementation, the step of constructing a first connection network based on the structured data about the first attribute includes: determining the connection relationships between immovable cultural relics within the target geographical area based on the structured data about the first attribute; calculating the weight values ​​corresponding to the connection relationships between the immovable cultural relics about the first attribute based on the first attribute features of each immovable cultural relic; and constructing the first connection network by using each immovable cultural relic as a node and the weight values ​​corresponding to the connection relationships between the immovable cultural relics about the first attribute as edge weight values.

[0079] Here, the connection relationship represents the correlation between different immovable cultural relics under a certain attribute. For example, determining the connection relationship between immovable cultural relics within the target area regarding the first attribute, based on the structured data about the first attribute, may include: pre-defining the connection relationship of the first attribute; then, based on the definition of the connection relationship of the first attribute and the first attribute characteristics of each immovable cultural relic in the structured data of the first attribute, selecting immovable cultural relics that conform to the definition; and establishing a connection relationship between any two selected immovable cultural relics regarding the first attribute, thereby quantitatively constructing the connection relationship between immovable cultural relics within the target area under the same attribute. For example, if the first attribute is geographical location, it can be predefined that any two immovable cultural relics are related. The structured data on geographical location attributes contains the geographical attribute characteristics of each immovable cultural relic, and a connection relationship based on geographical attributes can be established for any two immovable cultural relics. As another example, if the first attribute is chronology, it can be predefined that immovable cultural relics belonging to the same era are related. The structured data on chronology attributes contains the chronology attribute characteristics of each immovable cultural relic, and a connection relationship based on chronology can be established for any two immovable cultural relics within the same era.

[0080] The calculation of the weight value corresponding to the connection relationship between any two immovable cultural relics regarding the first attribute satisfies the following condition: the stronger the correlation between the two immovable cultural relics in the first attribute, the larger the weight value; conversely, the weaker the correlation, the smaller the weight value, and the weight value ≥ 0. For example, calculating the weight value corresponding to the connection relationship between the immovable cultural relics regarding the first attribute based on the first attribute characteristics of each immovable cultural relic may include: calculating the weight value corresponding to the connection relationship between the immovable cultural relics regarding the first attribute according to the definition of the weight value of the first attribute, based on the first attribute characteristics of each immovable cultural relic. For example, taking the geographical location attribute as the first attribute, the weight value of the geographical location attribute is defined as follows: the reciprocal of the geographical distance D between two immovable cultural relics is taken as the weight value w corresponding to the connection relationship between the two immovable cultural relics with respect to the geographical location attribute, that is, w = 1 / D. For example, based on the longitude and latitude data of the two immovable cultural relics, and combined with the ellipsoidal geodetic distance optimization algorithm, the geographical distance D between the two immovable cultural relics and the weight value 1 / D corresponding to the connection relationship between the two immovable cultural relics with respect to the geographical location attribute can be calculated. According to the definition of this weight value, the larger the weight value, the closer the geographical distance between the two immovable cultural relics is, and the stronger the connection relationship between the two immovable cultural relics with respect to the geographical location attribute, and vice versa. Taking the first attribute as historical and cultural attribute as an example, the weight value of the historical and cultural attribute is defined as follows: the similarity score between two immovable cultural relics in terms of historical and cultural attributes is used as the weight value corresponding to the connection relationship between the two immovable cultural relics in terms of cultural theme, historical event, and historical figure. For example, based on the cultural theme, historical event, and historical figure of two immovable cultural relics, the similarity score between the two immovable cultural relics in terms of cultural theme, historical event, and historical figure can be calculated by using a similarity algorithm, and the similarity score is used as the weight value corresponding to the connection relationship between the two immovable cultural relics in terms of cultural theme, historical event, and historical figure. According to the definition of this weight value, the smaller the weight value, the lower the similarity between the two immovable cultural relics in terms of cultural theme, historical event, and historical figure, and vice versa.

[0081] For example, after calculating the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute, the method may further include: performing statistical analysis on the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute to determine a critical weight value; filtering out weight values ​​smaller than the critical weight value from the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute; and constructing the first connection relationship network using the immovable cultural relics as nodes and the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute as edge weight values, which may further include: constructing the first connection relationship network using the immovable cultural relics as nodes and the filtered weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute as edge weight values. The selection of the critical weight value can be determined based on the mathematical statistical analysis of the connection relationship data of the first attribute among the immovable cultural relics within the target geographical area. The criteria are: when the weight value is greater than the critical weight value, the correlation between the two immovable cultural relics regarding the first attribute is strong; when the weight value is not greater than the critical weight value, the correlation between the two immovable cultural relics regarding the first attribute is weak. Therefore, connection relationship data corresponding to weight values ​​not greater than the critical weight value are deleted. For example, taking geographical location as the first attribute, mathematical statistical analysis can be performed on the weight values ​​corresponding to the connection relationships of each immovable cultural relic regarding geographical location attributes to select a critical weight value w. c =1 / D c , where D cTaking the critical geographical distance as an example, with the first attribute being historical and cultural, statistical analysis methods such as the natural discontinuity method can be used to group the weight values ​​corresponding to the connection relationships of cultural relics attributes among various immovable cultural relics, determine the critical weight value, and thus delete low weight values. Among them, the natural discontinuity method is a statistical method for grading and classifying according to the statistical distribution law of numerical data. Its core idea is to maximize the similarity within each group and maximize the dissimilarity between groups. This method divides the research objects into groups with similar properties by finding natural turning points and characteristic points of the data. The natural discontinuity method not only focuses on the similarity within the group, but also takes into account that the range and quantity of elements between groups should be as similar as possible. In this way, noise reduction processing is performed on the connection relationships of immovable cultural relics with respect to the first attribute within the target area based on the critical weight value. This filters out strong connections of immovable cultural relics with respect to the first attribute and removes weak connections. This reduces or eliminates noise in the connection relationship data of immovable cultural relics with respect to the first attribute, improving the quality and reliability of the connection relationship data for subsequent processing. At the same time, for situations where the target area is large and the amount of connection relationship data of immovable cultural relics with respect to the first attribute is too large, noise reduction processing can effectively reduce the amount of data, thereby improving the efficiency of subsequent data processing and thus improving the accuracy of identifying groups of immovable cultural relics, making each identified group of immovable cultural relics clearer.

[0082] As an example, consider a key attribute p in the attribute dataset P. j It can be based on information about the key attribute p j Definition, and attribute features of each immovable cultural relic in dataset X regarding the key attribute p j The characteristics are used to determine the relationship between any two immovable cultural relics within the target geographical area that meet the definition regarding the key attribute p. j This establishes the connection relationships between all immovable cultural relics within the target area, thereby constructing pairwise relationships regarding the key attribute p. j The connection relationship is incorporated into the key attribute p. j Connection relationship dataset R j =[r q (q = 1, 2, ..., Z), where Z represents the number of joins, and j and q represent the indices of the key attribute and the join, respectively; r q Represented as in the key attribute p j The following are related immovable cultural relic data pairs, namely R j =[r q ] = [h q1 ,h q2 ], where h q1 with h q2These represent the key attribute p within the target geographical area. j The q1th immovable cultural relic is related to the q2th immovable cultural relic within the target area, and q1 and q2 are both positive integers in the interval [1, M]. Then, for the key attribute p... j Data, based on the attribute feature dataset X, for each immovable cultural relic regarding the key attribute p. j Features, calculate the connection relationships in dataset R j The connection relationships r in the middle q The corresponding weight value is then stored in the connection relationship dataset. Chinese w q In order to establish a dataset of connections between immovable cultural relics containing weighted data. Among them, w q Indicates immovable cultural relics h q1 and immovable cultural relics q2 Between the key attribute p j The weight values ​​corresponding to the connection relationships; and then, based on the immovable cultural relic connection relationship dataset. Based on the characteristics, a critical weight value w is selected. c Filter out values ​​smaller than the critical weight value w c weight value w q The corresponding connection relationship data r q Among them, the critical weight value w c The value satisfies the condition when the weight value w q Greater than the critical weight value w c At that time, the correlation between two immovable cultural relics was relatively strong. After this noise reduction process, a filtered dataset of connections between immovable cultural relics was obtained. Finally, based on the immovable cultural relic dataset H and its connection relationship dataset... Constructing immovable cultural relics in the target region based on key attributes p j The following is a network of connections, which is represented as an undirected weighted graph. The immovable cultural relics dataset H contains all immovable cultural relics within the target geographical area, which are used as the undirected weighted graph G. j The nodes in the dataset, and the connection relationships after noise reduction. This includes the undirected weighted graph G. j The connection relationships between two nodes and the corresponding weight values ​​are shown in Figure 2. Figure 2 illustrates an undirected weighted graph G representing the connection relationships within a target geographical area according to an embodiment of this disclosure. j A schematic diagram; as shown in Figure 2, the immovable cultural relics dataset H includes 5 immovable cultural relics (i.e., h1, h2, h3, h4, h5), and the connection relationship datasets are shown. This includes information about the key attribute p among these five immovable cultural relics. j The connection relationships are assigned weight values ​​(i.e., w1, w2, w3, w4, w5, w6), where a weight value of 0 indicates that there is no connection between the two immovable cultural relics or that they are filtered out due to weak connection or a weight value less than the critical weight value. Using h1, h2, h3, h4, h5 as nodes, the connections between h1, h2, h3, h4, h5 as edges, and w1, w2, w3, w4, w5, w6 as the weight values ​​corresponding to the edges, the key attribute p of each immovable cultural relic within the target region is generated. j The undirected weighted graph G below j .

[0083] In one possible implementation, after constructing the first connection network, the first connection network can be visualized; thereby realizing the construction of the connection network of each immovable cultural relic within the target geographical area regarding the first attribute and realizing the visualization of the connection network.

[0084] For example, the visualization of the first connection network can be achieved using existing network visualization software, such as Gephi, NodeXL, Pajek, etc.

[0085] As an example, let's take the above undirected weighted graph G using Gephi. j For example, in network visualization, you can load the "Node Data Table" (i.e., the immovable cultural relic dataset H) and the "Edge Data Table" (i.e., the connection relationship dataset) into Gephi's "Data Sources" respectively. The visualization can be performed via the "Overview" or "Preview" tabs. Figure 3 shows a schematic diagram of the visualization of a connection network of a target geographical area according to an embodiment of the present disclosure. As shown in Figure 3, the undirected weighted graph G of the target geographical area... j Visualization: Each circle in the graph represents an undirected weighted graph G. j A node in the graph represents an immovable cultural relic within the target area; the line connecting any two nodes forms an undirected weighted graph G. j A single edge represents the relationship between two immovable cultural relics within the target geographical area regarding the key attribute p. j The connection relationship.

[0086] Step 104: Identify at least one group of immovable cultural relics in the first connection network.

[0087] In one possible implementation, the at least one group of immovable cultural relics can be visualized. The possible implementation methods for visualization can refer to the foregoing description of visualizing the first connection network.

[0088] One possible implementation involves analyzing the connection network of immovable cultural relics based on a community discovery model. This identifies related groups of immovable cultural relics within the first connection network. Immovable cultural relics within the same group exhibit strong correlations regarding their primary attribute, thus revealing the implicit structure of immovable cultural relics within the target geographical area in terms of geospatial and cultural history. It should be noted that other methods of cultural relic network structure analysis can also be used to identify related groups of immovable cultural relics; there are no limitations on this approach.

[0089] For example, an existing community detection model can be used to analyze the first connection network constructed above, and a modularity iterative optimization algorithm (e.g., Louvain algorithm, Label Propagation Algorithm algorithm) matching the community detection model can be used to identify the associated immovable cultural relic groups in the first connection network. Modularity is an important indicator of the quality of graph partitioning, reflecting the degree to which nodes in the graph are correctly assigned to various modules (or communities). High modularity means that the internal connections of modules in the partitioning result are tight, while the connections between modules are relatively sparse. It should be noted that for any immovable cultural relic, it can only belong to one associated immovable cultural relic group, and the modularity of the first connection network is maximized.

[0090] As an example, we will use the Gephi community recognition plugin and the Louvain algorithm to identify the undirected weighted graph G in Figure 3 above. j Taking a group of related immovable cultural relics as an example, Figure 4 shows a schematic diagram of the identification results of related immovable cultural relics groups within a target geographical area according to an embodiment of the present disclosure. As shown in Figure 4, dots of the same color represent immovable cultural relics belonging to the same related immovable cultural relics group; immovable cultural relics groups containing dots of different colors are the identified different immovable cultural relics groups. Figure 5 shows a schematic diagram of the mapping of the identification results of related immovable cultural relics groups within a target geographical area in geographic space according to an embodiment of the present disclosure; as shown in Figure 5, dots represent immovable cultural relics within the target geographical area, and all immovable cultural relics within the target geographical area are divided into multiple related immovable cultural relics groups.

[0091] Step 105: Determine the core cultural relics in the at least one group of immovable cultural relics, and based on the core cultural relics in the at least one group of immovable cultural relics, generate the structure of the immovable cultural relics in the target area regarding multiple attributes.

[0092] In one possible implementation, the structure with multiple attributes can be visualized. The possible implementation methods for visualization can refer to the aforementioned description of visualizing the first connection network.

[0093] Among them, the core cultural relic refers to the immovable cultural relic that best represents the correlation between the immovable cultural relic groups in terms of the second attribute in the first connection network.

[0094] For example, each group of immovable cultural relics contains a core cultural relic.

[0095] The multiple attributes can include a first attribute and at least one other attribute. For example, the structure of the multiple attributes can be a weighted undirected graph.

[0096] Thus, through steps 101-105 above, the automatic identification of the associative groups of immovable cultural relics with respect to the first attribute within the target geographical area and the structure of immovable cultural relics with respect to multiple attributes within the target geographical area is achieved. Users can select different target geographical areas as needed, thereby obtaining groups of immovable cultural relics with respect to the first attribute in different geographical areas. They can also select different attributes as the first attribute for the same target geographical area, thereby constructing a network of connections between immovable cultural relics with diverse key attributes and identifying groups of immovable cultural relics with respect to different attributes within the target geographical area. Furthermore, the core cultural relics in the group of immovable cultural relics can be identified, and based on the core cultural relics, the structure of immovable cultural relics with respect to multiple attributes within the target geographical area can be generated.

[0097] In this embodiment of the disclosure, information on each immovable cultural relic within a target geographical area is obtained; the information on the immovable cultural relic includes one or more of the following: name, geographical location, age, type, ownership, historical and cultural information, natural environment information, and social environment information; a first attribute feature of each immovable cultural relic is extracted from the information of each immovable cultural relic to generate structured data about the first attribute; the first attribute includes any one of the following: geographical location, age, type, ownership, and historical culture; based on the structured data about the first attribute, a first connection relationship network is constructed; wherein, in the first connection relationship network, each immovable cultural relic is used as a node, and the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes with respect to the first attribute; at least one group of immovable cultural relics is identified in the first connection relationship network. In this way, by characterizing immovable cultural relics from multiple dimensions through key attribute extraction, structured data on key attributes of immovable cultural relics is generated, thereby ensuring the accuracy and comprehensiveness of the constructed first connection network. Furthermore, it enables the quantitative, efficient, accurate, and automatic identification of related immovable cultural relic groups based on the correlation between immovable cultural relics under the same key attribute. Based on the core cultural relic, the generated groups of immovable cultural relics with multiple attributes are fused to obtain a structure regarding multiple attributes, thus revealing the implicit structure of immovable cultural relics within the target geographical area in terms of geospatial and cultural history. Simultaneously, this embodiment can accurately identify related groups of immovable cultural relics with the same key attribute based on different key attributes, revealing the implicit structure of immovable cultural relics in terms of geospatial and cultural history. Since this method for identifying related groups of immovable cultural relics and multi-attribute structures is based on a quantitative analysis method of structured data, the identification of immovable cultural relic groups is not affected by the subjective judgment of researchers, significantly improving the speed, stability, and accuracy of identifying related groups of immovable cultural relics. Furthermore, in the existing technology, identifying a wider geographical area (such as a province or country) means a significant increase in the number of immovable cultural relics involved, which leads to a significant increase in the time and material costs of their correlation research. The method in the embodiments of this disclosure is not limited by the size of the target geographical area or the number of immovable cultural relics within the target geographical area, thereby better supporting the construction of the connection network of immovable cultural relics in a wider geographical area and the rapid identification of related immovable cultural relic groups.

[0098] Figure 6 shows a flowchart of a method for identifying an associated group of immovable cultural relics and a multi-attribute structure according to an embodiment of the present disclosure. As shown in Figure 6, one possible implementation of step 105 in Figure 1 above may include:

[0099] Step 601: Extract the second attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the second attribute.

[0100] The second attribute includes any one of the following: geographical location, age, type, ownership, and historical culture, and the second attribute is different from the first attribute.

[0101] The specific process of generating structured data about the second attribute in this step can be referred to the relevant description of generating structured data about the first attribute in step 102 above, and will not be repeated here.

[0102] Step 602: Based on the structured data about the second attribute, construct a second connection network; wherein, in the second connection network, each immovable cultural relic is a node, and the weight value of the edge connecting two nodes is determined by the strength of the correlation between the two nodes about the second attribute.

[0103] The second connection network has the same number of nodes as the first connection network, meaning both contain all immovable cultural relics within the target geographical area. As an example, the second connection network is a weighted undirected graph.

[0104] For example, after the second connection network is constructed, the second connection network can also be visualized.

[0105] The specific process of generating and visualizing the second connection network in this step can be referred to the relevant description of building the first connection network in step 103 above, and will not be repeated here.

[0106] Step 603: Based on the first connection network and / or the second connection network, determine the core cultural relics in the at least one group of immovable cultural relics.

[0107] The role of the core cultural relic is to identify a "core representative" among the cultural relic groups identified in the first connection network, thereby enabling the superposition and construction of the first and second connection networks, making the structure of immovable cultural relics within the target area clearer. In this step, the core cultural relic can be determined based on the first connection network; or, based on the second connection network; or, by comprehensively considering both the first and second connection networks.

[0108] In one possible implementation, determining the core artifacts in the at least one group of immovable cultural relics based on the first connection network and / or the second connection network includes: for any group of immovable cultural relics, calculating the sum of the eigenvector centrality of each immovable artifact in the first connection network and the eigenvector centrality in the second connection network, based on the first connection network, the weight values ​​corresponding to each edge in the first connection network, the second connection network, and the weight values ​​corresponding to each edge in the second connection network; and determining the immovable artifact with the highest sum as the core artifact in the group of immovable cultural relics. Thus, core artifacts in each group of immovable cultural relics can be determined using diverse methods; other evaluation systems can also be used to determine the core artifacts, and this is not limited.

[0109] In the calculation of eigenvector centrality, the importance of a node depends on both the number of its neighboring nodes and the importance of those neighboring nodes. Compared to other types of centrality measurements, eigenvector centrality considers not only the influence of a single node on other nodes but also the influence of the neighboring nodes it affects. Therefore, it incorporates the ability of a node to spread its influence, which aligns with the principle of influence diffusion in the protection and utilization of immovable cultural relics. For example, for any group of immovable cultural relics in the first connection network identified above, the sum of the eigenvector centralities of each immovable cultural relic in the first and second connection networks can be calculated using network analysis software such as Gephi and UCINET, based on the weight values ​​of each edge in the first and second connection networks (i.e., the weight values ​​corresponding to the connection relationships between immovable cultural relics regarding the first attribute and the second attribute). The immovable cultural relic with the highest sum of eigenvector centralities can then be identified as the core relic in the group. It should be noted that other existing methods can also be used to determine the core relic; this is not limited.

[0110] Step 604: Based on the core cultural relics in the at least one group of immovable cultural relics, obtain the structure of the immovable cultural relics within the target geographical area regarding multiple attributes; wherein, the multiple attributes include the first attribute and the second attribute.

[0111] In one possible implementation, obtaining the structure of immovable cultural relics with respect to multiple attributes within the target geographical area based on the core cultural relics in the at least one group of immovable cultural relics may include: establishing connection relationships between core cultural relics in the at least one group of immovable cultural relics based on the connection relationships between each immovable cultural relic in the at least one group of immovable cultural relics with respect to the second attribute; using the sum of the corresponding weight values ​​between each immovable cultural relic in the at least one group of immovable cultural relics as the weight value corresponding to the connection relationship between the core cultural relics in the at least one group of immovable cultural relics; and generating the structure of immovable cultural relics with respect to multiple attributes within the target geographical area based on the at least one group of immovable cultural relics, the connection relationships between the core cultural relics in the at least one group of immovable cultural relics, and the weight values ​​corresponding to the connection relationships between the core cultural relics in the at least one group of immovable cultural relics.

[0112] Wherein, the connection relationship between the core cultural relics in the at least one group of immovable cultural relics represents the connection relationship between the at least one group of immovable cultural relics; for example, based on the connection relationship between each immovable cultural relic in the at least one group of immovable cultural relics regarding the second attribute, establishing the connection relationship between the core cultural relics in the at least one group of immovable cultural relics may include: for all the core cultural relics in the second connection relationship network determined above, determining the connection relationship between each immovable cultural relic in the immovable cultural relic group where any two core cultural relics are located regarding the second attribute as the connection relationship between the two core cultural relics.

[0113] The weight value corresponding to the connection relationship between the core cultural relics in the at least one immovable cultural relic group represents the weight value corresponding to the connection relationship between the at least one immovable cultural relic group. For example, for any two core cultural relics in any two immovable cultural relic groups, the weight value corresponding to the connection relationship between these two core cultural relics can be determined by the weight value corresponding to the connection relationship between each immovable cultural relic in these two immovable cultural relic groups regarding the second attribute. For example, the sum of the weight values ​​corresponding to the connection relationship between each immovable cultural relic in these two immovable cultural relic groups regarding the second attribute can be used as the weight value corresponding to the connection relationship between these two core cultural relics, thereby realizing the conversion of the sum of the weight values ​​corresponding to the connection relationship between each immovable cultural relic in the second connection relationship network regarding the second attribute into the weight value corresponding to the connection relationship between the core cultural relics of each immovable cultural group in the first connection relationship network regarding the second attribute.

[0114] For example, based on the at least one group of immovable cultural relics, the connection relationships between core cultural relics in the at least one group of immovable cultural relics, and the weight values ​​corresponding to the connection relationships between core cultural relics in the at least one group of immovable cultural relics, generating a structure of immovable cultural relics with respect to multiple attributes within the target area may include: using each immovable cultural relic within the target area as a node in the structure of multiple attributes, using the connection relationships between each immovable cultural relic within the target area with respect to the first attribute and the connection relationships between core cultural relics in each group of immovable cultural relics with respect to the second attribute as edges, and using the weight values ​​corresponding to each connection relationship as the weight values ​​corresponding to the corresponding edges, thus constructing a structure with respect to multiple attributes.

[0115] As an example, Figure 7 shows a schematic diagram of an immovable cultural relic structure within a target geographical area according to an embodiment of the present disclosure. As shown in Figure 7, the cultural relic structure within the target geographical area is a structure with multiple attributes. In this structure, the dots represent immovable cultural relics within the target geographical area, the green dots represent immovable cultural relics of the red culture, and the red dots represent the identified core cultural relics. The yellow polygons in this structure are the identified groups of immovable cultural relics with geographical attributes. The different thicknesses of the edges in this structure represent different weight values. In the left figure, the edges represent the connection relationship between each immovable cultural relic in each group of immovable cultural relics with geographical attributes and the connection relationship between ...

[0116] In this embodiment of the disclosure, a second connection relationship network is constructed based on the correlation of each immovable cultural relic with respect to the second attribute within the target area, and the core cultural relic of each group of related immovable cultural relics within the first connection relationship network is determined. Then, based on the core cultural relic, the generated groups of immovable cultural relics with respect to multiple attributes are fused to obtain a structure with respect to multiple attributes, namely, the structure of "first attribute - second attribute" of each immovable cultural relic within the target area.

[0117] The following example, using geographical location as the first attribute, illustrates the above-mentioned method for identifying related immovable cultural relics groups and multi-attribute structures.

[0118] Figure 8 shows a flowchart of a method for identifying an associated group of immovable cultural relics and a multi-attribute structure according to an embodiment of the present disclosure. As shown in Figure 8, the method includes the following steps:

[0119] Step 801: Obtain information on each immovable cultural relic within the target area.

[0120] The possible implementation of step 801 can be found in the relevant description in step 101 of Figure 1 above.

[0121] Step 802: Extract the geographical location attributes of each immovable cultural relic from the information of each immovable cultural relic.

[0122] This step transforms unstructured data on immovable cultural relics, including geographical, historical, and cultural elements, into structured data containing geographical location attributes.

[0123] The possible implementation of step 802 can be found in the relevant description in step 102 of Figure 1 above.

[0124] Step 803: Quantitatively construct the connection relationships of each immovable cultural relic under the same geographical location attribute.

[0125] Step 804: Calculate the weight values ​​corresponding to the connection relationships between immovable cultural relics based on their geographical location attributes.

[0126] Step 805: Based on the weight values ​​corresponding to the connection relationships of immovable cultural relics with respect to geographical location attributes, perform noise reduction processing on the connection relationship data of immovable cultural relics and filter out strong connection relationships between immovable cultural relics.

[0127] Step 806: Construct a network of connections between immovable cultural relics and their geographical location attributes, and visualize this network.

[0128] The possible implementation methods of steps 803-806 above can be referred to the relevant description in step 103 of Figure 1 above.

[0129] Step 807: Analyze the connection network based on the community discovery model to identify the associated groups of immovable cultural relics in the connection network.

[0130] The possible implementation of step 807 can be found in the relevant description in step 104 of Figure 1 above.

[0131] In this embodiment of the disclosure, a strategy of "geographical location attribute extraction - quantitative connection construction - weighted noise reduction processing - cultural relic network construction - immovable cultural relic group identification" is adopted, which can achieve quantitative and accurate identification of related immovable cultural relic groups based on geographic location attributes, thereby revealing the implicit structure of immovable cultural relics in terms of geospatial, cultural and historical aspects within the target area.

[0132] The following example, using the first attribute as geographical location and the second attribute as historical and cultural attribute, illustrates the above-mentioned method for identifying related immovable cultural relics groups and multi-attribute structures.

[0133] Figure 9 shows a flowchart of a method for identifying an associated group of immovable cultural relics and a multi-attribute structure according to an embodiment of the present disclosure. As shown in Figure 9, the method includes the following steps:

[0134] Step 901: Obtain information on each immovable cultural relic within the target area.

[0135] The possible implementation of step 901 can be found in the relevant description in step 101 of Figure 1 above.

[0136] Step 902: Extract the geographical location attributes of immovable cultural relics and construct structured data containing latitude and longitude.

[0137] The possible implementation of step 902 can be found in the relevant description in step 102 of Figure 1 above.

[0138] Step 903: Calculate the geographical distance between immovable cultural relics based on latitude and longitude, and construct a connection relationship between immovable cultural relics with the reciprocal of the geographical distance as the weight value.

[0139] Step 904: Select a weight threshold to perform noise reduction processing on the connection relationship related to geographic location attributes.

[0140] Step 905: Construct a network of connections between immovable cultural relics and their geographical location attributes, and visualize this network.

[0141] The possible implementation methods of steps 904 and 905 can be referred to the relevant description in step 103 of Figure 1 above.

[0142] Step 906: Analyze the connection network of immovable cultural relics with respect to geographical location attributes based on the community discovery model, and identify groups of immovable cultural relics that are closely related geographically.

[0143] The possible implementation of step 906 can be found in the relevant description in step 104 of Figure 1 above.

[0144] Thus, the identification of geographically closely related groups of immovable cultural relics is completed through steps 901-906 above.

[0145] Step 907: Extract the historical and cultural attributes of each immovable cultural relic within the target geographical area and construct structured data containing historical and cultural attributes.

[0146] The possible implementation of step 907 can be found in the relevant description in step 601 of Figure 6 above.

[0147] Step 908: Calculate the historical and cultural similarity score and construct the connection relationship between each immovable cultural relic with the historical and cultural similarity score as the weight value.

[0148] The higher the similarity in cultural themes, historical events, and historical figures, the higher the score. The connection relationship with the historical and cultural similarity score as the weight value is the connection relationship about historical and cultural attributes.

[0149] Step 909: Select a weight threshold to perform noise reduction processing on the connection relationship regarding historical and cultural attributes.

[0150] For example, methods such as the natural point break method can be used to group the weight values ​​corresponding to the connection relationships of each immovable cultural relic with respect to its historical and cultural attributes, and then filter out low-weight recombinants.

[0151] Step 910: Construct a network of connections between the historical and cultural attributes of immovable cultural relics and visualize this network.

[0152] The possible implementation methods of steps 908-910 can be referred to the relevant description in step 602 of Figure 6 above.

[0153] Step 911: Calculate the core cultural relics in a geographically closely related group of immovable cultural relics.

[0154] One possible implementation is to calculate the sum of the feature vector centrality of each immovable cultural relic in the geographical connectivity network and the feature vector centrality in the historical and cultural connectivity network. The immovable cultural relic with the highest sum of feature vector centrality in each group of immovable cultural relic with respect to geographical location attributes is the core cultural relic.

[0155] The possible implementation of step 911 can be found in the relevant description in step 603 of Figure 6 above.

[0156] Step 912: Transform the historical and cultural attributes of immovable cultural relics into the connection between core cultural relics in a geographically closely related group of immovable cultural relics, and obtain the "geographical-historical-cultural" structure of cultural relics in the destination area.

[0157] For example, a geographically closely related group of immovable cultural relics can be regarded as a new node, and the sum of the weight values ​​corresponding to the connection relationships of historical and cultural attributes among the immovable cultural relics can be converted into the weight values ​​corresponding to the connection relationships of historical and cultural attributes among the various groups of immovable cultural relics.

[0158] The "Geography-History and Culture" structure is based on geographical location attributes and historical and cultural attributes.

[0159] The possible implementation of step 912 can be found in the relevant description in step 604 of Figure 6 above.

[0160] By implementing the connection relationships based on geographical location attributes through steps 907-912 above, the connection relationships related to historical and cultural attributes are extracted, and a multi-attribute-associated immovable cultural relic structure is constructed.

[0161] Figure 10 illustrates a schematic diagram of the multi-attribute structure of immovable cultural relics within a target geographical area according to an embodiment of the present disclosure. As shown in Figure 10, the largest outer rectangle represents the target geographical area. Each node (square and pentagon) within this rectangle represents an immovable cultural relic within the target geographical area. The square represents the core cultural relic, and the pentagon represents other immovable cultural relics (general cultural relics) in the group of immovable cultural relics excluding the core cultural relic. Each gray polygon within the rectangle represents a geographically closely related group of immovable cultural relics, and each dashed polygon represents a historically and culturally closely related group of immovable cultural relics. The edges within each gray polygon connect a core cultural relic and a general cultural relic, representing the geographical connection between the two corresponding immovable cultural relics. The square within each gray polygon represents the core cultural relic in the corresponding group of immovable cultural relics. The edges connecting the squares in different gray polygons represent the historical and cultural connection between the two corresponding groups of immovable cultural relics. The thickness of the edges represents the strength of the association between the two corresponding immovable cultural relics, i.e., the edge weight.

[0162] In this embodiment, the connection relationship between immovable cultural relics regarding historical and cultural attributes is transformed into the historical and cultural connection relationship between core cultural relics in an immovable cultural relic group regarding geographical location attributes. This results in a "geographical-historical-cultural" structure of immovable cultural relics within a destination area. This multi-attribute structure of "geographical-historical-cultural" attributes can provide technical support for the planning of regional cultural heritage protection structures.

[0163] Based on the same inventive concept in the above method embodiments, the present disclosure also provides a device for identifying associated immovable cultural relics groups and multi-attribute structures, which can be used to execute the technical solutions described in the above method embodiments.

[0164] Figure 11 shows a structural diagram of a group of associated immovable cultural relics and a multi-attribute structure identification device according to an embodiment of the present disclosure. As shown in Figure 11, the device may include: an acquisition module 1101, used to acquire information of each immovable cultural relic within a target geographical area; the information of the immovable cultural relic includes one or more of the following: name, geographical location, age, type, ownership, historical and cultural information, natural environment information, and social environment information; and an extraction module 1102, used to extract the first attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the first attribute; the first attribute includes any one of the following: geographical location, age, type, ownership, and historical and cultural information. One component includes: a connection relationship construction module 1103, used to construct a first connection relationship network based on the structured data about the first attribute; wherein, in the first connection relationship network, each immovable cultural relic is a node, and the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes about the first attribute; an identification module 1104, used to identify at least one group of immovable cultural relics in the first connection relationship network; and a multi-attribute structure construction module 1105, used to determine the core cultural relic in the at least one group of immovable cultural relics, and based on the core cultural relic in the at least one group of immovable cultural relics, to generate a structure of immovable cultural relics about multiple attributes within the target geographical area.

[0165] In this embodiment of the disclosure, information on each immovable cultural relic within a target geographical area is obtained; the information on the immovable cultural relic includes one or more of the following: name, geographical location, age, type, ownership, historical and cultural information, natural environment information, and social environment information; a first attribute feature of each immovable cultural relic is extracted from the information of each immovable cultural relic to generate structured data about the first attribute; the first attribute includes any one of the following: geographical location, age, type, ownership, and historical culture; based on the structured data about the first attribute, a first connection relationship network is constructed; wherein, in the first connection relationship network, each immovable cultural relic is used as a node, and the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes with respect to the first attribute; at least one group of immovable cultural relics is identified in the first connection relationship network. In this way, by representing immovable cultural relics from multiple dimensions through key attribute extraction, structured data on the first attribute of immovable cultural relics is generated, thereby ensuring the accuracy and comprehensiveness of the constructed first connection network. Furthermore, it is possible to achieve quantitative, efficient, accurate, and automatic identification of related immovable cultural relic groups based on the correlation between various immovable cultural relics under the same key attribute, and to fuse the generated immovable cultural relic groups with multiple attributes based on core cultural relics to obtain the structure of multiple attributes. Thus, it reveals the implicit structure of immovable cultural relics in the target area in terms of geospatial, cultural, and historical aspects.

[0166] In one possible implementation, the connection construction module 1103 is further configured to: determine the connection relationship between each immovable cultural relic within the target geographical area regarding the first attribute based on the structured data regarding the first attribute; calculate the weight value corresponding to the connection relationship between each immovable cultural relic regarding the first attribute based on the first attribute characteristics of each immovable cultural relic; and construct the first connection relationship network using each immovable cultural relic as a node and the weight value corresponding to the connection relationship between each immovable cultural relic regarding the first attribute as the weight value of the edge.

[0167] In one possible implementation, the multi-attribute structure construction module 1105 is further configured to: extract the second attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the second attribute; construct a second connection relationship network based on the structured data about the second attribute; wherein, in the second connection relationship network, with each immovable cultural relic as a node, the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes about the second attribute; determine the core cultural relic in the at least one group of immovable cultural relic based on the first connection relationship network and / or the second connection relationship network; and obtain the structure of immovable cultural relics with respect to multiple attributes within the target geographical area based on the core cultural relic in the at least one group of immovable cultural relic; wherein, the multiple attributes include the first attribute and the second attribute.

[0168] In one possible implementation, the multi-attribute structure construction module 1105 is further configured to: for any group of immovable cultural relics, based on the first connection relationship network, the weight values ​​corresponding to each edge in the first connection relationship network, the second connection relationship network, and the weight values ​​corresponding to each edge in the second connection relationship network, calculate the sum of the feature vector centrality of each immovable cultural relic in the first connection relationship network and the feature vector centrality in the second connection relationship network; and determine the immovable cultural relic with the highest sum as the core cultural relic in the group of immovable cultural relics.

[0169] In one possible implementation, each group of immovable cultural relics contains a core cultural relic; the multi-attribute structure construction module 1105 is further configured to: establish a connection relationship between the core cultural relics in the at least one group of immovable cultural relics based on the connection relationship between each immovable cultural relic in the at least one group of immovable cultural relics with respect to the second attribute; use the sum of the corresponding weight values ​​between each immovable cultural relic in the at least one group of immovable cultural relics as the weight value corresponding to the connection relationship between the core cultural relics in the at least one group of immovable cultural relics; and generate a structure of immovable cultural relics with respect to multiple attributes within the target geographical area based on the at least one group of immovable cultural relics, the connection relationship between the core cultural relics in the at least one group of immovable cultural relics, and the weight value corresponding to the connection relationship between the core cultural relics in the at least one group of immovable cultural relics.

[0170] In one possible implementation, the connection construction module 1103 is further configured to: perform statistical analysis on the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute, and determine the critical weight value; filter out weight values ​​smaller than the critical weight value from the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute; and construct the first connection relationship network using the immovable cultural relics as nodes and the filtered weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute as edge weight values.

[0171] In one possible implementation, the device further includes a visualization module for visualizing the first connection network, the at least one group of immovable cultural relics, and the structure of the multiple attributes.

[0172] In some embodiments, the functions or modules of the apparatus provided in this disclosure can be used to perform the methods described in the above method embodiments. The specific implementation can be referred to the description of the above method embodiments, and for the sake of brevity, it will not be repeated here.

[0173] This disclosure also proposes a computer-readable storage medium storing computer program instructions that, when executed by a processor, implement the above-described method. The computer-readable storage medium can be volatile or non-volatile.

[0174] This disclosure also proposes an electronic device, including: a processor; and a memory for storing processor-executable instructions; wherein the processor is configured to implement the above method when executing the instructions stored in the memory.

[0175] This disclosure also provides a computer program product, including computer-readable code, or a non-volatile computer-readable storage medium carrying computer-readable code, wherein when the computer-readable code is run in a processor of an electronic device, the processor in the electronic device performs the above-described method.

[0176] Figure 12 shows a block diagram of an electronic device 1900 according to an embodiment of the present disclosure. For example, the electronic device 1900 may be provided as a server or terminal device. Referring to Figure 12, the electronic device 1900 includes a processing component 1922, which further includes one or more processors, and memory resources represented by memory 1932 for storing instructions executable by the processing component 1922, such as application programs. The application programs stored in memory 1932 may include one or more modules, each corresponding to a set of instructions. Furthermore, the processing component 1922 is configured to execute instructions to perform the methods described above.

[0177] Electronic device 1900 may also include a power supply component 1926 configured to perform power management of electronic device 1900, a wired or wireless network interface 1950 configured to connect electronic device 1900 to a network, and an input / output interface 1958 (I / O interface). Electronic device 1900 can operate on an operating system, such as Windows Server, stored in memory 1932. TM Mac OS X TM Unix TM Linux TM FreeBSD TM Or similar.

[0178] In an exemplary embodiment, a non-volatile computer-readable storage medium is also provided, such as a memory 1932 including computer program instructions that can be executed by a processing component 1922 of an electronic device 1900 to perform the above-described method.

[0179] The various component embodiments of this disclosure can be implemented in hardware, or as software modules running on one or more processors, or a combination thereof. Those skilled in the art will understand that microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components in the computing processing device according to embodiments of this disclosure. This disclosure can also be implemented as a device or apparatus program (e.g., a computer program and computer program product) for performing some or all of the methods described herein. Such an implementation of this disclosure can be stored on a computer-readable medium or can be in the form of one or more signals. Such signals can be downloaded from an Internet website, provided on a carrier signal, or provided in any other form.

[0180] For example, Figure 13 illustrates a computing processing device that can implement a method for identifying associated immovable cultural relic groups and multi-attribute structures according to this disclosure. This computing processing device conventionally includes a processor 1010 and a computer program product or computer-readable medium in the form of a memory 1020. The memory 1020 can be an electronic memory such as flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. The memory 1020 has a storage space 1030 for program code 1031 for performing any of the method steps described above. For example, the storage space 1030 for the program code may include various program codes 1031 for implementing the various steps in the above method. These program codes can be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. Such computer program products are typically portable or fixed storage units as described with reference to Figure 14. This storage unit may have storage segments, storage spaces, etc., arranged similarly to the memory 1020 in the computing processing device of Figure 14. The program code can be compressed, for example, in an appropriate form. Typically, the storage unit includes computer-readable code 1031', that is, code that can be read by a processor such as 1010, which, when run by a computing processing device, causes the computing processing device to perform the various steps in the method for identifying associated immovable cultural relics groups and multi-attribute structures described above.

[0181] This disclosure can be a system, method, and / or computer program product. A computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for causing a processor to implement various aspects of this disclosure.

[0182] Computer-readable storage media can be tangible devices capable of holding and storing instructions for use by an instruction execution device. Computer-readable storage media can be, for example—but not limited to—electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer-readable storage media used herein are not to be construed as transient signals themselves, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., light pulses through fiber optic cables), or electrical signals transmitted through wires.

[0183] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0184] Computer program instructions used to perform the operations of this disclosure may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, Wolfram, etc., and conventional procedural programming languages ​​such as the "C" language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer may be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuitry, such as programmable logic circuitry, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), is personalized by utilizing state information from the computer-readable program instructions to implement various aspects of this disclosure.

[0185] Various aspects of this disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0186] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0187] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0188] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of an instruction containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, may be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0189] The various embodiments of this disclosure have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is chosen to best explain the principles, practical application, or technical improvements to the embodiments in the market, or to enable others skilled in the art to understand the embodiments disclosed herein.

Claims

1. A method for identifying interconnected immovable cultural relic groups and their multi-attribute structures, characterized in that, The method includes: Obtain information on each immovable cultural relic within the target geographical area; the information on the immovable cultural relic includes one or more of the following: name, geographical location, age, type, ownership, historical and cultural information, natural environment information, and social environment information; Extract the first attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the first attribute; the first attribute includes any one of the following: geographical location, age, type, ownership, and historical culture; Based on the structured data about the first attribute, a first connection network is constructed; wherein, in the first connection network, each immovable cultural relic is taken as a node, and the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes about the first attribute. At least one group of immovable cultural relics was identified in the first connection network; Identify the core cultural relics in the at least one group of immovable cultural relics, and based on the core cultural relics in the at least one group of immovable cultural relics, generate a structure of multiple attributes for the immovable cultural relics within the target geographical area.

2. The method according to claim 1, characterized in that, The construction of the first connection network based on the structured data regarding the first attribute includes: Based on the structured data regarding the first attribute, the connection relationships regarding the first attribute among the immovable cultural relics within the target geographical area are determined; Based on the first attribute characteristics of each immovable cultural relic, calculate the weight value corresponding to the connection relationship between each immovable cultural relic with respect to the first attribute; The first connection relationship network is constructed by using each immovable cultural relic as a node and the weight value corresponding to the connection relationship between each immovable cultural relic with respect to the first attribute as the weight value of the edge.

3. The method according to claim 1, characterized in that, The step of identifying the core cultural relics in the at least one group of immovable cultural relics, and generating a structure of multiple attributes for immovable cultural relics within the target geographical area based on the core cultural relics in the at least one group of immovable cultural relics, includes: Extract the second attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the second attribute; Based on the structured data regarding the second attribute, a second connection network is constructed; wherein, in the second connection network, each immovable cultural relic is taken as a node, and the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes regarding the second attribute; Based on the first connection network and / or the second connection network, determine the core cultural relics in the at least one group of immovable cultural relics; Based on the core cultural relics in the at least one group of immovable cultural relics, the structure of immovable cultural relics within the target geographical area regarding multiple attributes is obtained; wherein, the multiple attributes include the first attribute and the second attribute.

4. The method according to claim 3, characterized in that, The determination of core cultural relics in at least one group of immovable cultural relics based on the first connection network and / or the second connection network includes: For any group of immovable cultural relics, based on the first connection network, the weight values ​​corresponding to each edge in the first connection network, the second connection network, and the weight values ​​corresponding to each edge in the second connection network, the sum of the eigenvector centrality of each immovable cultural relic in the first connection network and the eigenvector centrality of each immovable cultural relic in the second connection network is calculated; the immovable cultural relic with the highest sum is determined as the core cultural relic in the group of immovable cultural relics.

5. The method according to claim 3, characterized in that, Each group of immovable cultural relics contains a core cultural relic; The process of obtaining the structure of immovable cultural relics with respect to multiple attributes within the target geographical area based on core cultural relics in at least one group of immovable cultural relics includes: Based on the connection relationship between each immovable cultural relic in the at least one immovable cultural relic group regarding the second attribute, establish the connection relationship between the core cultural relics in the at least one immovable cultural relic group; The sum of the weight values ​​corresponding to each immovable cultural relic in the at least one immovable cultural relic group shall be used as the weight value corresponding to the connection relationship between the core cultural relics in the at least one immovable cultural relic group. Based on the at least one group of immovable cultural relics, the connection relationships between the core cultural relics in the at least one group of immovable cultural relics, and the weight values ​​corresponding to the connection relationships between the core cultural relics in the at least one group of immovable cultural relics, a structure of immovable cultural relics with respect to multiple attributes within the target geographical area is generated.

6. The method according to claim 2, characterized in that, After calculating the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute, the method further includes: Statistical analysis is performed on the weight values ​​corresponding to the connection relationships between the immovable cultural relics with respect to the first attribute to determine the critical weight values; Among the weight values ​​corresponding to the connection relationship of the first attribute among the immovable cultural relics, weight values ​​that are less than the critical weight value are filtered out. The step of constructing the first connection relationship network by using each immovable cultural relic as a node and the weight value corresponding to the connection relationship between each immovable cultural relic with respect to the first attribute as the weight value of the edge includes: The first connection relationship network is constructed by using each immovable cultural relic as a node and the weight value corresponding to the connection relationship between the filtered immovable cultural relics with respect to the first attribute as the weight value of the edge.

7. The method according to any one of claims 1-6, characterized in that, The method further includes: The structure of the first connection network, the at least one group of immovable cultural relics, and the multiple attributes is visualized.

8. A device for identifying interconnected immovable cultural relics groups and multi-attribute structures, characterized in that, The device includes: The acquisition module is used to acquire information on each immovable cultural relic within the target geographical area; the information on the immovable cultural relic includes one or more of the following: name, geographical location, age, type, ownership, historical and cultural information, natural environment information, and social environment information; An extraction module is used to extract the first attribute features of each immovable cultural relic from the information of each immovable cultural relic, and generate structured data about the first attribute; the first attribute includes any one of: geographical location, age, type, ownership, and historical culture; A connection relationship construction module is used to construct a first connection relationship network based on the structured data about the first attribute; wherein, in the first connection relationship network, each immovable cultural relic is used as a node, and the weight value corresponding to the edge connecting two nodes is determined by the strength of the correlation between the two nodes about the first attribute. The identification module is used to identify at least one group of immovable cultural relics in the first connection network; A multi-attribute structure construction module is used to identify the core cultural relics in the at least one group of immovable cultural relics, and based on the core cultural relics in the at least one group of immovable cultural relics, generate a structure of multiple attributes for immovable cultural relics within the target geographical area.

9. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to implement the method of any one of claims 1 to 7 when executing instructions stored in the memory.

10. A non-volatile computer-readable storage medium storing computer program instructions thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 7.

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