Forest land resource protection information management system and method

Abstract

The invention provides a forest land resource protection information management system and method, and the method comprises the steps: determining the core information and replacement information of valuable and rare tree species resource information through obtaining the valuable and rare tree species resource information of a target forest land in the forest land resource protection information management system, and extracting a keyword set for retrieval by a user, determining a plurality of associated fields, matched with the core information, of the keyword set, performing semantic adaptation evaluation of ecological vulnerability on the replacement information and all the associated fields to obtain semantic coverage between the replacement information and each associated field, and determining a risk level of each associated field; and based on the retrieval permission of the user and all the risk levels, determining granularity characteristics when desensitization is performed on each associated field, and performing desensitization replacement on all the associated fields through the granularity characteristics and all the semantic coverage degrees to obtain desensitization information when the user retrieves tree species resources. By adopting the scheme of the invention, the information can be dynamically desensitized and shielded according to the specific requirements of the user under the condition of ensuring the completeness of the residual information.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of information management, more particularly, the present application relates to a forest resource protection information management system and method. BACKGROUND

[0002] Information management refers to a series of technical tools, methods and systems for obtaining, storing, processing, transmitting, analyzing and presenting information, aiming to ensure the accuracy, integrity, security and reliability of information, widely used in enterprises, governments, scientific research and various organizations, involving fields such as data storage, information retrieval, document management, data analysis, etc.

[0003] Forest resource protection information refers to information about the health status of forest and forest resource ecosystem, resource distribution, species diversity, forest coverage, carbon storage, etc.; its main purpose is to effectively monitor, manage and protect forest resources; in the existing forest resource protection information management method, the forest resource information is classified uniformly and normatively (such as forest type, resource amount, protection level, etc.), which is convenient for collaborative management, or through a permission management system to statically shield information, that is, different access permissions are set for different user groups (such as government departments, scientific research institutions, the public, etc.), to ensure that people of different roles can access information as needed, but the static shielding of information makes users unable to access real-time information according to their own needs, resulting in the lack of completeness of the remaining information, such as: the semantics of the remaining information is not coherent, the logic is not smooth, therefore, how to dynamically desensitize shielding information according to the specific needs of users while ensuring the completeness of the remaining information has become a difficult problem in the industry. SUMMARY

[0004] The present application provides a forest resource protection information management system and method, which can dynamically desensitize shielding information according to the specific needs of users while ensuring the completeness of the remaining information.

[0005] In a first aspect, the present application provides a data desensitization method for a forest resource protection information management system, comprising the following steps: Obtain rare tree species resource information of a target forest in a forest resource protection information management system; Determine the core information and replacement information of the rare tree species resource information; When receiving a user tree species resource retrieval request, extract a keyword set for user retrieval, determine a plurality of associated fields in the keyword set that match the core information, perform semantic adaptability evaluation of the replacement information and all associated fields based on ecological vulnerability, and obtain the semantic coverage between the replacement information and each associated field; determining a risk level of each associated field, determining a granularity feature of desensitization of each associated field based on the search permission of the user and all the risk levels; performing desensitization replacement on all the associated fields based on the granularity feature and all the semantic coverage degrees, to obtain desensitization information for the user to search for the rare tree species resource.

[0006] In some embodiments, determining the core information and the replacement information of the rare tree species resource information specifically includes: extracting core information from the rare tree species resource information; determining replacement information according to all the information in the rare tree species resource information except the core information.

[0007] In some embodiments, when receiving a search request of a user tree species resource, extracting a keyword set for the user to search specifically includes: extracting multiple keywords from the search request of the user tree species resource; expanding all the keywords to obtain a keyword set for the user to search.

[0008] In some embodiments, determining multiple associated fields in the keyword set that match the core information specifically includes: selecting a keyword from the keyword set as a selected keyword; matching the keyword with the core information to obtain multiple associated fields of the selected keyword; continuing to determine multiple associated fields of the remaining keywords in the keyword set.

[0009] In some embodiments, performing semantic adaptability evaluation of the replacement information and all the associated fields to obtain semantic coverage degrees between the replacement information and each associated field specifically includes: determining multiple information fidelity degrees of the replacement information based on ecological sensitivity factors; determining multiple theme adaptation degrees between each associated field and the replacement information; determining semantic coverage degrees between the replacement information and each associated field according to all the theme adaptation degrees and all the information fidelity degrees.

[0010] In some embodiments, determining a risk level of each associated field specifically includes: determining a field coverage rate of each associated field; determining a sensitive determination criterion of the core information; determining a risk level of each associated field according to all the field coverage rates and the sensitive determination criterion.

[0011] In some embodiments, the granularity feature for desensitizing each associated field based on the user's search permission and the risk level of all includes: obtaining the search permission of the user; determining a plurality of granularity levels of each associated field according to the risk level of all and the search permission of the user; all granularity levels are taken as the granularity feature for desensitizing the corresponding associated field.

[0012] In some embodiments, the desensitization information for the user to search for the resource by desensitizing and replacing all associated fields through the granularity feature and the semantic coverage of all includes: selecting an associated field as a selected associated field; determining a candidate field of the selected associated field according to the semantic coverage of all; desensitizing and replacing the selected associated field based on the granularity feature and the candidate field to obtain a desensitization-replaced associated field; continuing to desensitize and replace the remaining associated fields; determining the desensitization information for the user to search for the resource according to all desensitization-replaced associated fields.

[0013] In some embodiments, the rare tree species resource information of the target forest land in the forest land resource protection information management system is collected by unmanned aerial vehicle remote sensing for on-site measurement of the target forest land.

[0014] In a second aspect, the application provides a forest land resource protection information management system, which comprises a data desensitization unit, and the data desensitization unit comprises: a collection module for collecting rare tree species resource information of a target forest land in a forest land resource protection information management system; a processing module for determining core information and replacement information of the rare tree species resource information; When receiving a search request for tree species resources of a user, the processing module extracts a keyword set for searching by the user, determines a plurality of associated fields matched with the core information in the keyword set, and performs semantic adaptability evaluation of ecological vulnerability on the replacement information and all associated fields to obtain semantic coverage between the replacement information and each associated field. The processing module determines the risk level of each associated field and determines the granularity feature for desensitizing each associated field based on the search permission of the user and the risk level of all. An execution module desensitizes and replaces all associated fields through the granularity feature and the semantic coverage of all to obtain desensitization information for the user to search for the resource.

[0015] The technical scheme provided by the embodiments disclosed in the application has the following beneficial effects: In the forest land resource protection information management system and method provided by the application, first, rare tree species resource information of a target forest land in the forest land resource protection information management system is acquired, core information and replacement information of the rare tree species resource information are determined, when a user's tree species resource search request is received, a keyword set for the user's search is extracted, a plurality of associated fields in the keyword set that match the core information are determined, semantic adaptability evaluation of the replacement information and all associated fields in terms of ecological vulnerability is performed, and semantic coverage degrees between the replacement information and each associated field are obtained; risk levels of each associated field are determined, granularity features for desensitization of each associated field are determined based on the user's search permission and all risk levels, all associated fields are desensitized and replaced through the granularity features and all semantic coverage degrees, and desensitized information for the user's search of tree species resources is obtained.

[0016] Therefore, first, rare tree species resource information of a target forest land in the forest land resource protection information management system is acquired, core information and replacement information of the rare tree species resource information are determined, wherein the core information refers to key information in the rare tree species resource information that needs to be protected, the replacement information is information for desensitization and replacement of the core information, and the core information and the replacement information are used to distinguish the functions of each field in the rare tree species resource information, facilitating subsequent matching of the user's search request; second, when a user's tree species resource search request is received, a keyword set for the user's search is extracted, a plurality of associated fields in the keyword set that match the core information are determined, semantic adaptability evaluation of the replacement information and all associated fields in terms of ecological vulnerability is performed, and semantic coverage degrees between the replacement information and each associated field are obtained; wherein the semantic coverage degree is a parameter value describing the overlapping degree of a field in the replacement information and each field in the core information in terms of information level, used to evaluate the priority of replacement of each field in the replacement information to the core information, facilitating subsequent desensitization protection of information for feedback of the user's tree species resource search request; risk levels of each associated field are determined, granularity features for desensitization of each associated field are determined based on the user's search permission and all risk levels, all associated fields are desensitized and replaced through the granularity features and all semantic coverage degrees, and desensitized information for the user's search of tree species resources is obtained. The above scheme can dynamically desensitize and shield information according to the specific needs of the user while ensuring the integrity of the remaining information. BRIEF DESCRIPTION OF DRAWINGS

[0017] Figure 1 is an exemplary flowchart of a data desensitization method for a forest land resource protection information management system according to some embodiments of the application; Figure 2is a schematic diagram of implementing user tree species resource retrieval according to some embodiments of the present application; Figure 3 is an exemplary flow chart of determining semantic coverage according to some embodiments of the present application; Figure 4 is a structural schematic diagram of a data desensitization unit according to some embodiments of the present application; Figure 5 is a structural schematic diagram of a computer device for implementing a data desensitization method for a forest resource protection information management system according to some embodiments of the present application. DETAILED DESCRIPTION

[0018] In order to better understand the above technical solutions, the above technical solutions will be described in detail below in combination with the drawings in the specification and specific embodiments.

[0019] Reference Figure 1 The figure is an exemplary flow chart of a data desensitization method for a forest resource protection information management system according to some embodiments of the present application, which mainly includes the following steps: In step 101, rare tree species resource information of a target forest in a forest resource protection information management system is obtained.

[0020] In specific implementation, the rare tree species resource information of the target forest in the forest resource protection information management system is collected by field measurement of the target forest through remote sensing technology (such as unmanned aerial vehicle remote sensing), and the collected rare tree species resource information is saved in a forestry resource database of the forest resource protection information management system. In specific implementation, the rare tree species resource information of the target forest in the forest resource protection information management system is obtained from the forestry resource database, wherein the rare tree species includes a national first-class protected plant tree species and an endangered tree species, and the rare tree species resource information includes tree species name, tree location information, tree species economic value, tree shape information, tree species distribution, static environment for tree growth (such as slope), dynamic time sequence environment for tree growth (such as real-time soil moisture), ecological relationship, and human disturbance situation. The information in the rare tree species resource information except coordinates and numbers is processed by a word segmentation tool (such as jieba) to obtain a plurality of individual fields, all the fields are stored in a database, and all the fields are divided into the following three types according to field content: spatio-temporal type field (such as geographic location, specific time), numerical type field (such as tree height: 125 cm), and classification and description field (such as: Rosaceae species), then all the fields are divided into the following three types according to content description of each field: precise description (such as 66.33°), range description (such as 12 o'clock to 9 o'clock), and fuzzy description (such as medium density level); in other embodiments, other ways can also be used for implementation, which will not be described here.

[0021] In step 102, the core information and the replacement information of the rare tree species resource information are determined.

[0022] In some embodiments, the core information and the replacement information of the rare tree species resource information can be determined by the following steps: extracting the core information from the rare tree species resource information; determining the replacement information according to all information in the rare tree species resource information except the core information.

[0023] In specific implementation, the core information can be extracted from the rare tree species resource information by the following method, that is, all fields containing tree species name, tree location information, tree shape information and tree species economic value in the rare tree species resource information are taken as the core information, all fields obtained after synonym field and phrase expansion of the fields in the core information by a large language model (such as BERT) are added to the core information, for example, the field of the core information is acacia, and all fields obtained after synonym field expansion of the field of the core information are: ["acacia", "acacia tree", "acacia distribution", "acacia growing environment"], and all fields obtained after expansion are added to the core information; in other embodiments, other ways can also be used to determine, which are not limited here.

[0024] In a specific implementation, the determination of the replacement information according to all information in the rare tree species resource information except the core information can be implemented in the following manner: a field in the core information is selected as a selected field, a field in all information in the rare tree species resource information except the core information is selected as a comparison field, word vector conversion is performed on the selected field and the comparison field through a word vector conversion model (such as Word2Vec), the word vectors of the selected field and the comparison field are used as operation parameters, and a cosine similarity calculation formula is used to obtain the information correlation between the selected field and the comparison field, wherein the information correlation is a parameter value describing the correlation of the information carried by the selected field and the comparison field, the information correlation between the selected field and the remaining fields in all information in the rare tree species resource information except the core information is continuously determined, the fields corresponding to the information correlations greater than the average of all information correlations are used as replacement fields of the selected field, wherein the replacement field refers to a field that can replace the core information, the replacement fields of the remaining fields in the core information are continuously determined, one replacement field is selected as a selected replacement field, all fields in the core information are simulated to be replaced through data conversion technology (such as OpenRefine) on the selected replacement field, and the replacement accuracy of all fields in the core information after the simulation is verified, so as to obtain the total number of replacement, the total number of replacement, and the reasonable number of replacement of the selected replacement field, the total number of replacement, the total number of replacement, and the reasonable number of replacement of the remaining replacement fields are continuously determined, and a set of replacement fields with a reasonable number of replacement greater than the average of all reasonable numbers of replacement is used as the replacement information; in other embodiments, other manners can also be used for determination, which is not limited here.

[0025] It should be noted that the core information in the present application refers to the key information in the rare tree species resource information that needs to be protected, the replacement information is the information for desensitization and replacement of the core information, the total number of replacement refers to the total number of fields in the core information that need to be correctly replaced by the replacement field, the total number of replacement refers to the total number of fields replaced by the replacement field in the simulation, the reasonable number of replacement refers to the total number of fields in the core information that meet the safety and effectiveness after the simulation replacement of the replacement field on the core information, and the core information and the replacement information are used to distinguish the functions of the fields in the rare tree species resource information, facilitating the matching of the user's subsequent search request.

[0026] In step 103, when receiving the user's search request for tree species resources, the set of keywords for the user's search is extracted, a plurality of associated fields in the keyword set that match the core information are determined, the replacement information is evaluated for semantic adaptability of ecological vulnerability with all associated fields, and the semantic coverage between the replacement information and each associated field is obtained.

[0027] In some embodiments, with reference to Figure 2As shown, the figure is a schematic diagram of implementing user tree species resource retrieval in some embodiments of the present application. In the present embodiment, implementing user tree species resource retrieval includes a user client and a server. When receiving a retrieval request of a user tree species resource, the server extracts a keyword set for the user to perform retrieval by using the following steps: extracting multiple keywords from the retrieval request of the user tree species resource; extending all keywords to obtain a keyword set for the user to perform retrieval request.

[0028] In a specific implementation, extracting multiple keywords from the retrieval request of the user tree species resource can be implemented by using the following method, that is, when receiving a retrieval request of a user tree species resource, removing punctuation marks (such as commas, periods, and quotation marks, etc.) and special characters (such as mol / L) in the content of the retrieval request of the user tree species resource, using a word segmentation tool (such as jieba) to perform word segmentation processing on the content of the retrieval request of the tree species resource after removing the punctuation marks and special characters, obtaining multiple fields and phrases, and removing all stop words (such as “of”) from all fields and phrases, thereby obtaining multiple keywords, wherein the keywords refer to core words or phrases in the retrieval request of the user tree species resource that can reflect the user's retrieval intention and describe the retrieval theme; extending all keywords to obtain a keyword set for the user to perform retrieval request can be implemented by using the following method, that is, all keywords are extended by a large language model (such as BERT) to obtain synonym fields, and then all keywords combined with all synonym fields obtained by extension are de-duplicated by a de-duplication algorithm (such as SimHash), and the set composed of all keywords and fields after de-duplication is used as a keyword set for the user to perform retrieval request; in other embodiments, other methods can also be used to determine, which is not limited here.

[0029] It should be noted that the keyword set in the present application refers to a keyword set of the content of the retrieval request of the user tree species resource, which includes extended fields and phrases of keywords, and is used to analyze the content of the retrieval request of the user tree species resource, facilitating subsequent information matching, wherein the retrieval request of the user tree species resource is input in the form of natural language.

[0030] In some embodiments, determining multiple associated fields of the keywords in the keyword set that match the core information can be implemented by using the following steps: selecting a keyword from the keyword set as a selected keyword; matching the keyword with the core information to obtain multiple associated fields of the selected keyword; continuing to determine multiple associated fields of the remaining keywords in the keyword set.

[0031] In a specific implementation, the matching of the keywords with the core information to obtain the multiple associated fields of the selected keyword can be implemented in the following manner: first, a field in the core information is selected as a selected field, and the selected keyword is judged. If the selected keyword is multiple exact words (such as "Yangtze River Basin"), the following judgment is directly performed: if the selected field contains the selected keyword, the selected field is taken as the associated field of the selected keyword. For example, the selected keyword is ["Robinia pseudoacacia"], and the selected field is ["Robinia pseudoacacia distribution in the Yellow River Basin"], and it is determined that the selected field contains the selected keyword. If the selected keyword is a fuzzy description (such as "coverage condition"), the selected keyword is matched with all the fields in the core information by using full-text indexing (i.e., all the fields related to "coverage"), so that all the fields in the core information containing the full-text indexing are taken as the associated fields of the selected keyword. If the selected keyword is greater than or equal to two, the selected keyword is matched with all the fields in the core information by using combination indexing. For example, the selected keyword is ["Robinia pseudoacacia in the flood season of the Yellow River"], and the combination indexing is ["Yellow River", "flood season", "Robinia pseudoacacia"], and then all the fields in the core information containing the combination indexing are taken as the associated fields of the selected keyword. The judgment and matching of all the synonym fields and phrases extended from the selected keyword are also performed in the specific implementation, and all the associated fields of the selected keyword obtained are de-duplicated to obtain the multiple associated fields of the selected keyword. In other embodiments, other manners can also be used for determination, which is not limited here.

[0032] It should be noted that the associated field in the present application refers to a field in the core information that can effectively connect the keyword with the field in the core information, and is used for quickly positioning and extracting the core information content related to the keyword, so as to facilitate the subsequent adaptation degree evaluation between the fields.

[0033] In some embodiments, as shown in Figure 3 The figure is a flow diagram for determining semantic coverage in some embodiments of the present application. In the present embodiment, ecological vulnerability can be represented by ecological sensitivity factors. The semantic adaptation evaluation of the replacement information and all the associated fields for ecological vulnerability can be implemented in the following steps: First, in step 1031, multiple information fidelity degrees of the replacement information are determined based on ecological sensitivity factors. Second, in step 1032, multiple theme adaptation degrees between each associated field and the replacement information are determined. Finally, in step 1033, the semantic coverage between the replacement information and each associated field is determined according to all the theme adaptation degrees and all the information fidelity degrees.

[0034] In a specific implementation, the multiple information fidelities of the replacement information determined based on the ecological sensitivity factor can be implemented in the following manner: a field in the replacement information is selected as a selected field, and the selected field is judged. If the selected field is a space-time type field (such as geographic coordinates, collection time), if the ecological sensitivity factor is, for example, the distribution of an ecologically sensitive area (such as a nature reserve, a habitat of rare tree species), the selected field and all space-time type fields in the core information are calculated by the Hausdorff distance formula to obtain the similarity of the spatial distribution between the selected field and each space-time type field in the core information, and the weight of the similarity is adjusted according to the ecological sensitivity of the space-time area. All adjusted spatial distribution similarities are used as the information fidelities between the selected field and each space-time type field in the core information. If the selected field is a numerical field, and the numerical value is related to an ecological index (such as the ecological function score of a tree species, the ecological service value of a forest land), a field in the core information is selected as a comparison field, the minimum of the selected field and the comparison field is taken as an integral object, and a preliminary information fidelity is calculated by combining the overlap coefficient formula. Then, the preliminary information fidelity is corrected according to the influence of the ecological sensitivity on the numerical value, and the corrected information fidelities between the remaining numerical fields in the core information and the selected field are determined. If the numerical value is not related to the ecological index, the information fidelity between the selected field and the comparison field is calculated in a conventional manner, that is, a field in the core information is selected as a comparison field, the minimum of the selected field and the comparison field is taken as an integral object, and the information fidelity between the selected field and the comparison field is calculated by combining the overlap coefficient formula. The information fidelities between the remaining numerical fields in the core information and the selected field are determined. If the selected field does not belong to the above-mentioned numerical field or the above-mentioned space-time field, the rationality of the replacement is audited based on the requirement of the ecological sensitivity, the number of reasonable replacements corresponding to the selected field is divided by the total number of replacements corresponding to the selected field to obtain a first value, the number of reasonable replacements corresponding to the selected field is divided by the total number of fields in the core information excluding the numerical fields and the space-time fields to obtain a second value, the product of the first value and the second value is divided by the sum of the first value and the second value, and then the divided value is multiplied by 2. Finally, the multiplied value is taken as the information fidelity of the selected field, wherein the information fidelity is a parameter value describing the similarity of the overall information after the selected field in the replacement information is replaced by the corresponding field in the core information. The multiple information fidelities of the remaining fields in the replacement information combined with the ecological sensitivity factor are determined. In other embodiments, the ecological sensitivity factor can also be determined in other manners, which are not limited here.

[0035] In specific implementation, determining the multiple topic fit degrees between each associated field and the replacement information can be achieved in the following way: select an associated field as the selected associated field, select a field from the replacement information as the selected field, and obtain the topic fit degree between the selected field and the selected associated field through topic modeling technology (such as LDA). The topic fit degree refers to the degree of fit of the main content between the selected field and the selected associated field. Continue to determine the topic fit degree between the remaining fields in the replacement information and the selected associated field, and continue to determine the multiple topic fit degrees of the remaining associated fields. Other methods can also be used in other embodiments, which are not limited here.

[0036] In specific implementation, determining the semantic coverage between the replacement information and each associated field based on all topic adaptability and all information fidelity can be achieved in the following way: First, all The associated fields are sorted in ascending order (from left to right) according to the average value of the topic fit corresponding to each associated field, resulting in an associated field sequence. All fields in the replacement information are sorted in ascending order (from left to right) according to the average value of the information fidelity of each field, resulting in a replacement field sequence. One associated field is selected as the selected associated field. From all fields in the replacement information corresponding to the selected associated field, one field is selected as the selected replacement field. The average value of all information fidelities corresponding to the selected replacement field is multiplied by the position of the selected replacement field in the replacement field sequence to obtain the first value. Then, the position of the selected associated field in the associated field sequence is multiplied by the average value of all topic fit corresponding to the selected associated field. The result of this multiplication is added to the first value. The result of this addition is then logarithmically calculated to base 2. The result of this logarithmic calculation is used as the semantic coverage between the selected associated field and the selected replacement field. The semantic coverage between the selected associated field and the remaining fields in the replacement information corresponding to the selected associated field is then determined. Multiple semantic coverages between the remaining associated fields and the replacement information are then determined. In other embodiments, other methods can also be used to determine this, which are not limited here.

[0037] It should be noted that the semantic coverage in this application is a dynamic parameter value that describes the comprehensive overlap between the fields in the replacement information and the corresponding fields in the core information in terms of semantic matching degree and ecological adaptability. It is used to evaluate the priority of each field in the replacement information in replacing the core information, so as to facilitate the de-identification protection of the information fed back to the user's tree species resource retrieval request.

[0038] In step 104, the risk level of each associated field is determined, and the granularity features for desensitizing each associated field are determined based on the user's search permissions and all risk levels.

[0039] In some embodiments, determining the risk level of each associated field can be achieved by the following steps: determining the field coverage of each associated field; determining the sensitive determination criterion of the core information; determining the risk level of each associated field according to all the field coverage and the sensitive determination criterion.

[0040] In specific implementation, determining the field coverage of each associated field can be achieved by the following way, i.e. selecting an associated field as a selected associated field, counting the number of times of the selected associated field appearing in all the fields of the rare tree species resource information by text query (such as SQL statement query), dividing the number of times of the selected associated field appearing in all the fields of the rare tree species resource information by the total number of fields of the rare tree species resource information, and then taking the value obtained by the division as the field coverage of the selected associated field, wherein the field coverage is a parameter value describing the coverage degree of the selected associated field in the rare tree species resource information, and the field coverage of the remaining associated fields is determined successively; determining the sensitive determination criterion of the core information can be achieved by the following way, i.e. taking the legal or policy restriction information (such as the tree species information protected by laws and regulations), the ecological sensitive restriction information (such as the endangered and threatened tree species), the economic value of the tree species (such as the information of high-value tree species) and the geographical distribution of the tree species (such as the tree species involving the national nature reserve) as the sensitive determination criterion of the core information, wherein the sensitive determination criterion is a criterion for judging the sensitivity of each field in the core information; in other embodiments, other ways can also be used for determination, which is not limited here.

[0041] In a specific implementation, the risk level of each associated field can be determined according to all field coverage and the sensitive determination criterion in the following manner: an associated field is selected as a selected associated field, and the sensitivity of the selected associated field is determined according to the sensitive determination criterion; if the selected associated field is tree species basic information, the selected associated field is marked as a non-sensitive field, and the sensitive level of the non-sensitive field is set to 3, wherein the tree species basic information includes tree species name and tree shape information; if the selected associated field is ecological sensitive restriction information, the selected associated field is marked as a medium-sensitive field, and the sensitive level of the medium-sensitive field is set to 5, wherein the ecological sensitive restriction information includes tree location information; if the selected associated field is tree species economic value, the selected associated field is marked as a high-sensitive field, and the sensitive level of the high-sensitive field is set to 8; the sensitive level corresponding to the selected associated field is added to the field coverage of the selected associated field, the sum is divided by the product of the sensitive level corresponding to the selected associated field and the field coverage of the selected associated field, and the value obtained by the division is taken as the risk level of the selected associated field, and the risk level of the remaining associated field is determined continuously; in other embodiments, other manners can also be used for determination, which is not limited here.

[0042] It should be noted that the risk level in the present application is to describe the risk degree when the content information of each associated field is leaked, and is used to evaluate the sensitive situation of each associated field, wherein the risk level can be set according to the specific protection strategy of the target information, and the risk level is convenient for subsequent desensitization of each associated field.

[0043] In some embodiments, the granularity feature when desensitizing each associated field can be implemented in the following steps based on the search permission of the user and all risk levels: obtaining the search permission of the user; determining a plurality of granularity levels of each associated field according to all risk levels and the search permission of the user; all granularity levels are taken as the granularity feature when desensitizing the corresponding associated field.

[0044] In a specific implementation, the search permission of the user can be obtained in the following manner: after the user logs in the forest resource protection information query system successfully, the role (e.g., researcher) and attribute (e.g., forestry protection department) of the user are obtained from an identity management system (e.g., LDAP), and then the search permission corresponding to the user is obtained from a permission management system according to the role and attribute of the user. The attribute of the user is information (e.g., department, position, project team, etc.) describing the characteristics of the user, which is used for access control of the user. The search permission refers to the permission of the user to access or operate the range of data in the rare forest resource protection information query system, which determines the information that can be searched and the fields that can be accessed by the user. The search permission includes: the permission of a general user, which can access non-sensitive fields and can only read and write data; the permission of an administrator, which can access all fields and can add, delete, read and write data; and the permission of a researcher, which can access medium-sensitive fields and can add, delete, read and write data. In other embodiments, other manners can also be used for implementation, which will not be described here.

[0045] In a specific implementation, the granularity level of each associated field can be determined according to all risk levels and the search permission of the user in the following manner: the permission of the user is judged. If the permission of the user is the permission of an administrator, the granularity level of all associated fields is 0, that is, the desensitization replacement of each associated field is not needed. If the permission of the user is the permission of a researcher, one associated field is selected as a selected associated field, the risk level of the selected associated field is divided by the permission level of the user, and the value obtained by the division is taken as the granularity level of the selected associated field under the permission of the researcher. The granularity level of the remaining associated fields under the permission of the researcher is determined. If the permission of the user is the permission of a general user, the granularity level of each associated field is calculated in the same manner as the permission of the researcher. The granularity level is a parameter value describing the degree of detail of the operation of desensitization replacement of each associated field. In other embodiments, other manners can also be used for implementation, which will not be described here.

[0046] It should be noted that the granularity feature in the present application refers to the degree of detail of the desensitization processing of each associated field, which is used to evaluate the degree of detail of the desensitization operation and the amount of information retained by each associated field after desensitization. The higher the granularity feature, the less information retained by the associated field after desensitization. The lower the granularity feature, the more information retained by the associated field after desensitization. The granularity feature facilitates subsequent determination of desensitization information when the user searches for tree species resources.

[0047] In step 105, all associated fields are desensitized and replaced by the granularity feature and all semantic coverage degrees, to obtain desensitization information when the user searches for tree species resources.

[0048] In some embodiments, the desensitization information of the user searching the tree species resource is obtained by desensitizing and replacing all the associated fields according to the granularity feature and all the semantic coverages, which can be achieved by the following steps: selecting an associated field as a selected associated field; determining a candidate field of the selected associated field according to all the semantic coverages; desensitizing and replacing the selected associated field based on the granularity feature and the candidate field to obtain a desensitization-replaced associated field; continuing to desensitize and replace the remaining associated fields; determining the desensitization information of the user searching the tree species resource according to all the desensitization-replaced associated fields.

[0049] In specific implementation, the candidate field of the selected associated field according to all the semantic coverages can be determined by the following way, that is, the field in the replacement information corresponding to the maximum semantic coverage in all the semantic coverages between the selected associated field and the replacement information is taken as the candidate field of the selected associated field, wherein the candidate field refers to the field for replacing the selected associated field, and the candidate field of the remaining associated fields is continuously determined; the desensitization-replaced associated field can be obtained by desensitizing and replacing the selected associated field based on the granularity feature and the candidate field, which can be achieved by the following way, that is, if the user permission is the administrator permission, the selected associated field does not need to be desensitized and replaced, if the user permission is the researcher permission, a replacement field model is initialized, the granularity feature of the selected associated field under the researcher permission is taken as the constraint parameter of the replacement field, and the candidate field of the selected associated field is taken as the initialization parameter of the replacement field, and then the replacement field of the selected associated field is obtained through the replacement field model, it should be noted that the replacement field model is a model for establishing the replacement field using a machine learning algorithm (such as a regression algorithm, a neural network), for example, the replacement field of the selected associated field = A * the candidate field of the selected associated field (i.e., the initialization parameter) + B * the granularity feature of the selected associated field under the researcher permission (i.e., the constraint parameter), wherein A and B are weight coefficients, A and B can be determined by data fitting on a historical data set of the training replacement field according to a multivariate linear regression method (such as the least square method), the obtained replacement field of the selected associated field is used to replace the selected associated field, if the user permission is the ordinary user permission, the replacement field of the selected associated field under the ordinary user permission is determined in the same way as under the researcher permission, and the obtained replacement field of the selected associated field under the ordinary user permission is used to replace the selected associated field to obtain the desensitization-replaced associated field; in other embodiments, other methods can also be used for determination, which is not limited here.

[0050] In a specific implementation, the desensitization information of the user searching for the tree species resource can be determined in the following manner: the desensitized associated fields are connected and corrected (e.g., adjusting passive voice, removing redundant phrases) by a language model (e.g., an NLP language model) to obtain the desensitization information of the user searching for the tree species resource; in other embodiments, other methods can also be used to determine the desensitization information, which is not limited here.

[0051] It should be noted that the desensitization information in the present application refers to the information obtained by desensitizing the fields obtained by searching the user's information search request content, which is used to dynamically desensitize and replace the information fed back to the user according to the user's access rights, so that the original rare tree species resource information cannot be directly identified, and the dynamic desensitization protection of the rare tree species resource information in information search is facilitated.

[0052] In addition, another aspect of the present application, in some embodiments, the present application provides a forest resource protection information management system, which comprises a data desensitization unit, which is described with reference to Figure 4 The figure is a structural schematic diagram of a data desensitization unit according to some embodiments of the present application. The data desensitization unit 400 comprises a collection module 401, a processing module 402 and an execution module 403, which are described as follows: The collection module 401 is mainly used to obtain the rare tree species resource information of the target forest land in the forest resource protection information management system in the present application. The processing module 402 is used to determine the core information and the replacement information of the rare tree species resource information in the present application. It should be noted that the processing module 402 is also used to extract the keyword set of the user searching when receiving the user's search request for the tree species resource, determine a plurality of associated fields in the keyword set matching the core information, and perform semantic adaptability evaluation on the replacement information and all associated fields to obtain the semantic coverage between the replacement information and each associated field. In addition, it should be noted that the processing module 402 is also used to determine the risk level of each associated field, and determine the granularity feature of desensitizing each associated field based on the user's search authority and all risk levels. The execution module 403 is mainly used to desensitize and replace all associated fields by the granularity feature and all semantic coverages to obtain the desensitization information of the user searching for the tree species resource in the present application.

[0053] In addition, the present application further provides a computer device, comprising a memory and a processor, the memory stores a code, and the processor is configured to acquire the code and execute the data desensitization method for the forest resource protection information management system.

[0054] In some embodiments, with reference to Figure 5 The figure is a structural schematic diagram of a computer device for implementing the data desensitization method for the forest resource protection information management system according to some embodiments of the present application. The data desensitization method for the forest resource protection information management system in the above embodiments can be implemented by the computer device shown in the figure, which comprises at least one processor 501, a communication bus 502, a memory 503 and at least one communication interface 504. Figure 5 The processor 501 can be a general central processing unit (CPU) or an application specific integrated circuit (ASIC).

[0055] The processor 501 can be a general central processing unit (CPU) or an application specific integrated circuit (ASIC).

[0056] The communication bus 502 can be used to transmit information between the above components.

[0057] The memory 503 can be a read-only memory (ROM) or other types of static storage devices that can store static information and instructions, a random access memory (RAM) or other types of dynamic storage devices that can store information and instructions, an electrically erasable programmable read-only memory (EEPROM), a compact disc read-only memory (CDROM) or other optical disk storage, an optical disk storage (including a compact disk, a laser disk, an optical disk, a digital versatile disk, a blue-ray disk, etc.), a magnetic disk or other magnetic storage device, or any other medium capable of carrying or storing desired program codes in the form of instructions or data structures and capable of being accessed by a computer, but not limited to this. The memory 503 can exist independently and be connected to the processor 501 through the communication bus 502. The memory 503 can also be integrated with the processor 501.

[0058] The memory 503 is configured to store a program code for implementing the scheme of the present application, and the processor 501 is configured to execute the program code stored in the memory 503. The program code can include one or more software modules. The method used in the above-described embodiments can be implemented by the processor 501 and one or more software modules in the program code in the memory 503.

[0059] The communication interface 504 is configured to communicate with other devices or communication networks, such as an Ethernet, a radio access network (RAN), a wireless local area network (WLAN), etc., using any transceiver-like device.

[0060] In a specific implementation, as an example, the computer device can include a plurality of processors, each of which can be a single CPU processor or a multi-CPU processor. The processor herein can refer to one or more devices, circuits, and / or processing cores for processing data (e.g., computer program instructions).

[0061] The computer device described above can be a general-purpose computer device or a special-purpose computer device. In a specific implementation, the computer device can be a desktop computer, a laptop computer, a network server, a personal digital assistant (PDA), a mobile phone, a tablet computer, a wireless terminal device, a communication device, or an embedded device. The embodiments of the present application do not limit the type of the computer device.

[0062] In addition, the present application also provides a computer-readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the above-described data desensitization method for a forest resource protection information management system.

[0063] Although the preferred embodiments of the present application have been described, those skilled in the art can make further changes and modifications to the embodiments once they know the basic inventive concept. Therefore, the appended claims are intended to cover all changes and modifications falling within the scope of the present application.

[0064] Obviously, those skilled in the art can make various modifications and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application is also intended to include these modifications and variations.

Claims

1. A data desensitization method for a forest resource protection information management system, characterized by, The method comprises the following steps: obtaining rare tree species resource information of a target forest land in a forest land resource protection information management system; determining core information and replacement information of the rare tree species resource information; when receiving a search request of a user for tree species resources, extracting a keyword set for search of the user, determining a plurality of associated fields in the keyword set that match the core information, performing semantic adaptation evaluation of ecological vulnerability of the replacement information on all associated fields, and obtaining semantic coverage degrees between the replacement information and the associated fields; determining risk levels of the associated fields, and determining granularity features of desensitization of the associated fields based on search permissions of the user and all risk levels; performing desensitization and replacement of all associated fields based on the granularity features and all semantic coverage degrees, and obtaining desensitization information for search of tree species resources by the user.

2. The method of claim 1, wherein, The determination of the core information and the replacement information of the rare tree species resource information specifically comprises: extracting core information from the rare tree species resource information; determining replacement information based on all information in the rare tree species resource information except the core information.

3. The method of claim 1, wherein, The extraction of the keyword set for search of the user when receiving the search request of the user for tree species resources specifically comprises: extracting a plurality of keywords from the search request of the user for tree species resources; expanding all keywords to obtain the keyword set for search request of the user.

4. The method of claim 1, wherein, The determination of the plurality of associated fields in the keyword set that match the core information specifically comprises: selecting a keyword in the keyword set as a selected keyword; matching the keyword with the core information to obtain a plurality of associated fields of the selected keyword; continuing to determine a plurality of associated fields of remaining keywords in the keyword set.

5. The method of claim 1, wherein, The semantic adaptation evaluation of ecological vulnerability of the replacement information on all associated fields to obtain the semantic coverage degrees between the replacement information and the associated fields specifically comprises: determining a plurality of information fidelity degrees of the replacement information based on ecological sensitivity factors; determining a plurality of theme adaptation degrees between the associated fields and the replacement information; determining the semantic coverage degrees between the replacement information and the associated fields based on all theme adaptation degrees and all information fidelity degrees.

6. The method of claim 1, wherein, The determination of the risk levels of the associated fields specifically comprises: determining field coverage rates of the associated fields; determining a sensitive determination criterion of the core information; determining the risk levels of the associated fields based on all field coverage rates and the sensitive determination criterion.

7. The method of claim 1, wherein, The determination of the granularity features of desensitization of the associated fields based on the search permissions of the user and all risk levels specifically comprises: obtaining search permissions of the user; determining a plurality of granularity levels of the associated fields based on all risk levels and the search permissions of the user; taking all granularity levels as the granularity features of desensitization of the corresponding associated fields.

8. The method of claim 1, wherein, The desensitization and replacement of all associated fields based on the granularity features and all semantic coverage degrees to obtain the desensitization information for search of tree species resources by the user specifically comprises: selecting an associated field as a selected associated field; determining a candidate field of the selected associated field based on all semantic coverage degrees; The selected associated field is replaced by desensitization according to the granularity feature and the candidate field, and a desensitized associated field is obtained; The desensitization of the remaining associated fields is continued; The desensitization information of the user when searching for the tree species resource is determined according to all the desensitized associated fields.

9. The method of claim 1, wherein, The rare tree species resource information of the target forest land in the forest resource protection information management system is collected through the field measurement of the target forest land by the unmanned aerial vehicle remote sensing.

10. A forest resource conservation information management system comprising a data de- sensitization unit, characterized by, The data desensitization unit comprises: A collection module acquires the rare tree species resource information of the target forest land in the forest resource protection information management system; A processing module determines the core information and the replacement information of the rare tree species resource information; When receiving a search request of a user tree species resource, the processing module extracts a keyword set for the search of the user, determines a plurality of associated fields matched with the core information in the keyword set, and performs semantic adaptability evaluation of the replacement information and all the associated fields according to the ecological vulnerability, to obtain the semantic coverage between the replacement information and each associated field; The processing module determines the risk level of each associated field, and determines the granularity feature of the desensitization of each associated field based on the search authority of the user and all the risk levels; A performing module performs desensitization replacement on all the associated fields according to the granularity feature and all the semantic coverages, to obtain the desensitization information of the user when searching for the tree species resource.

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