An electronic archive single-set management method and system based on panoramic service

Abstract

The application discloses a kind of electronic archive single set system and method based on panoramic service, the method includes: obtaining all historical versions of engineering document, each version of engineering document is divided into multiple sub-documents, and extract certain version and its last version engineering document;The similarity of certain sub-document in the certain version and the same sub-document of the engineering document of the last version is calculated;The operation of the certain version by user is obtained, and the information protection factor of certain sub-document in the certain version is calculated in combination with the similarity, when the information protection factor exceeds preset threshold, certain sub-document in the certain version and the same sub-document of the engineering document of the last version are backed up, to complete engineering document important information management.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of single-set management of engineering documents, and more particularly relates to an electronic archive single-set management method and system based on panoramic services. BACKGROUND

[0002] Panoramic services in the engineering field generally refer to a comprehensive service system based on whole-life-cycle management, all-around data collection and analysis, and whole-dimension optimization decision-making. It aims to cover the whole process, all elements, whole space, and all data of engineering projects, and improve the efficiency, safety, and sustainability of engineering construction and management through digitization and intelligentization.

[0003] Single-set management of engineering documents based on panoramic services can ensure the unity and simplicity of document content and avoid confusion caused by too many versions. However, the disadvantage of single-set documents is that when the document content needs to be modified or updated, there may be a risk of information loss. SUMMARY

[0004] To solve the above technical problems, the present application proposes an electronic archive single-set management method based on panoramic services for single-set management of engineering documents, comprising:

[0005] Obtaining all historical versions of engineering documents, dividing the engineering documents of each version into multiple sub-documents, and extracting the engineering documents of a certain version and its previous version;

[0006] Calculating the similarity of a certain sub-document in the certain version and the same sub-document of the previous version of the engineering documents;

[0007] Obtaining the operation of the user on the certain version, and combining the similarity, calculating the information protection factor of a certain sub-document in the certain version, when the information protection factor exceeds a preset threshold, backing up the certain sub-document in the certain version and the same sub-document of the previous version of the engineering documents to complete the management of important information of engineering documents.

[0008] Further, the information protection factor includes:

[0009]

[0010] Among them, is the information protection factor of the i-th sub-document in the k-th version of engineering documents, and a' is the adjustment factor of the information protection factor, is the influence function of user operation on the i-th sub-document in the k-th version of engineering documents is the i-th sub-document in the k-th version of engineering documents ​With the i-th sub-document in the (k-1)-th version of the project document semantic similarity The dynamic weight adjustment function as a parameter, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The similarity score, where n is the number of sub-documents. For the i-th sub-document in the k-th version of the project document The amount of modification.

[0011] Furthermore, the dynamic weight adjustment function include:

[0012]

[0013] Where γ′ is the first adjustment factor of the dynamic weight adjustment function, and δ′ is the second adjustment factor of the dynamic weight adjustment function.

[0014] Furthermore, the user operation targets the i-th sub-document in the k-th version of the project document. Influence function include:

[0015]

[0016] Where λ1 is the first adjustment factor of the influence function. For users in time window T window The i-th sub-document within the k-th version of the project document The number of edits, λ2 is the second adjustment factor of the influence function. For the user, the i-th sub-document in the k-th version of the project document The number of times the edit was accepted. For the user, the i-th sub-document in the k-th version of the project document The total number of edits, λ3 is the third adjustment factor of the influence function, w insert The weight of the insertion operation. For the user, the i-th sub-document in the k-th version of the project document The number of insertion operations, w delete As the weight of the deletion operation, For the user, the i-th sub-document in the k-th version of the project document The number of times the deletion operation was performed, w replace For the weight of the replacement operation, For the user, the i-th sub-document in the k-th version of the project document The number of replacement operations, λ4 is the fourth adjustment factor of the influence function, v is the fifth adjustment factor of the influence function, is the current modification time of the i-th sub-document in the k-th version of the engineering document is the last modification time of the i-th sub-document in the k-th version of the engineering document

[0017] Further, the similarity of the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document comprises:

[0018]

[0019] wherein α1 is the weight of cosine similarity, is the cosine similarity of the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document α2 is the weight of Jaccard similarity, is the Jaccard similarity of the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document α3 is the weight of KL divergence, is the KL divergence of the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document α4 is the weight of semantic similarity.

[0020] Further, all weights and adjustment factors are fitted by gradient descent method or ant colony algorithm.

[0021] Further, the semantic similarity of the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document is calculated by Word2Vec or BERT model

[0022] Further, the sub-document comprises: title, paragraph, table containing engineering parameters, and conclusion of the engineering document.

[0023] The application further provides an electronic archive single-set management system based on panoramic service, which is used for single-set management of engineering documents and comprises:

[0024] ​​​The document segmentation module is used to obtain all historical versions of the project document, divide each version of the project document into multiple sub-documents, and extract the project document of a certain version and its previous version.

[0025] The similarity calculation module is used to calculate the similarity between a sub-document in a certain version and the same sub-document in the previous version of the project document;

[0026] The backup module is used to obtain the user's operation information for a certain version, and calculate the information protection factor of a certain sub-document in the certain version based on the similarity. When the information protection factor exceeds a preset threshold, the module backs up the sub-document in the certain version and the same sub-document in the previous version of the project document to complete the management of important information in the project document.

[0027] Furthermore, information protection factors include:

[0028]

[0029] in, Let α be the information protection factor for the i-th sub-document in the k-th version of the project document, and let α′ be the adjustment factor for the information protection factor. For user operations on the i-th sub-document in the k-th version of the project document Influence function The i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document semantic similarity The dynamic weight adjustment function as a parameter, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The similarity score, where n is the number of sub-documents. For the i-th sub-document in the k-th version of the project document The amount of modification.

[0030] In summary, the technical solutions conceived by this invention have the following beneficial effects compared with the prior art:

[0031] This invention, by setting an information protection factor, can back up important content when engineering documents are updated, thereby solving the risk of information loss when single-set documents need to be modified or updated. Attached Figure Description

[0032] Figure 1 This is a flowchart of the method in Embodiment 1 of the present invention;

[0033] Figure 2 Figure 1 is a system structure diagram of an embodiment 2 of the present application. DETAILED DESCRIPTION

[0034] In order to better understand the above technical solutions, the above technical solutions will be described in detail below in combination with the drawings of the specification and specific embodiments.

[0035] The method provided by the present application can be implemented in a terminal environment, which can include one or more of the following components: a processor, a storage medium and a display screen. The storage medium stores at least one instruction, which is loaded and executed by the processor to implement the method described in the following embodiments.

[0036] The processor can include one or more processing cores. The processor connects various parts in the entire terminal through various interfaces and lines, executes various functions of the terminal and processes data by running or executing instructions, programs, code sets or instruction sets stored in the storage medium, and calling data stored in the storage medium.

[0037] The storage medium can include random access memory (RAM) and read-only memory (ROM). The storage medium can be used to store instructions, programs, codes, code sets or instructions.

[0038] The display screen is used to display the user interface of each application program.

[0039] In addition, those skilled in the art can understand that the structure of the above terminal does not constitute a limitation on the terminal, and the terminal can include more or fewer components, or combine certain components, or different component arrangements. For example, the terminal also includes radio frequency circuit, input unit, sensor, audio circuit, power supply and other components, which are not described here.

[0040] Embodiment 1

[0041] As Figure 1 The present embodiment proposes an electronic file single set management method based on panoramic service, which is used for single set management of engineering documents, and includes the following steps.

[0042] In step 101, all historical versions of engineering documents are obtained, each version of engineering documents is divided into multiple sub-documents, and engineering documents of a certain version and its previous version are extracted.

[0043] Specifically, the sub-documents include: title, paragraph, table containing engineering parameters and conclusion of the engineering documents.

[0044] Step 102: Calculate the similarity between a sub-document in a certain version and the same sub-document in the previous version of the project document;

[0045] Specifically, the i-th sub-document in the k-th version of the project document. With the i-th sub-document in the (k-1)-th version of the project document similarity include:

[0046]

[0047] Where α1 is the weight of the cosine similarity, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The cosine similarity is given by α2, where α2 is the weight of the Jaccard similarity. For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The Jaccard similarity, where α3 is the weight of the KL divergence. For the i-th sub-document in the k-th version of the project document With the u-th sub-document in the (k-1)-th version of the project document The KL divergence is given by α4, where α4 is the weight of semantic similarity.

[0048] Step 103: Obtain the user's operation status for a certain version, and calculate the information protection factor of a certain sub-document in the certain version based on the similarity. When the information protection factor exceeds a preset threshold, back up the same sub-document in the certain version and the same sub-document in the previous version of the project document to complete the management of important information in the project document.

[0049] Specifically, information protection factors include:

[0050]

[0051] in, Let α be the information protection factor for the i-th sub-document in the k-th version of the project document, and let α′ be the adjustment factor for the information protection factor. For user operations on the i-th sub-document in the k-th version of the project document Influence function The i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document semantic similarity The dynamic weight adjustment function as a parameter, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The similarity score, where n is the number of sub-documents. For the i-th sub-document in the k-th version of the project document The amount of modification.

[0052] Specifically, dynamic weight adjustment function include:

[0053]

[0054] Where γ′ is the first adjustment factor of the dynamic weight adjustment function, and δ′ is the second adjustment factor of the dynamic weight adjustment function.

[0055] Specifically, the user operation affects the i-th sub-document in the k-th version of the project document. Influence function include:

[0056]

[0057] Where λ1 is the first adjustment factor of the influence function. For users in time window T window The i-th sub-document within the k-th version of the project document The number of edits, λ2 is the second adjustment factor of the influence function. For the user, the i-th sub-document in the k-th version of the project document The number of times the edit was accepted. For the user, the i-th sub-document in the k-th version of the project document The total number of edits, λ3 is the third adjustment factor of the influence function, w insert The weight of the insertion operation. For the user, the i-th sub-document in the k-th version of the project document The number of insertion operations, w delete As the weight of the deletion operation, For the user, the i-th sub-document in the k-th version of the project document The number of times the deletion operation was performed, w replace For the weight of the replacement operation, For the user, the i-th sub-document in the k-th version of the project document The number of replacement operations, λ4 is the fourth adjustment factor of the influence function, and τ is the fifth adjustment factor of the influence function. For the i-th sub-document in the k-th version of the project document Current modification time, the last modification time of the i-th sub-document in the k-th version engineering document.

[0058] Specifically, the weights and adjustment factors are fitted by gradient descent method or ant colony algorithm.

[0059] Specifically, the semantic similarity between the i-th sub-document in the k-th version engineering document and the i-th sub-document in the k-1-th version engineering document is calculated by Word2Vec or BERT model.

[0060] Embodiment 2

[0061] As shown in Figure 2 , the embodiment provides an electronic archive single-set management system based on panoramic service, which is used for single-set management of engineering documents, and includes:

[0062] A document division module is configured to obtain all historical versions of engineering documents, divide the engineering documents of each version into multiple sub-documents, and extract the engineering documents of a certain version and its previous version.

[0063] Specifically, the sub-documents include the title, paragraphs, tables containing engineering parameters, and conclusions of the engineering documents.

[0064] A similarity calculation module is configured to calculate the similarity between a certain sub-document in the certain version and the same sub-document of the previous version of the engineering documents.

[0065] Specifically, the similarity between the i-th sub-document in the k-th version engineering document and the i-th sub-document in the k-1-th version engineering document includes:

[0066]

[0067] wherein, α1 is the weight of cosine similarity, is the cosine similarity between the i-th sub-document in the k-th version engineering document and the i-th sub-document in the k-1-th version engineering document , α2 is the weight of Jaccard similarity, is the Jaccard similarity between the i-th sub-document in the k-th version engineering document and the i-th sub-document in the k-1-th version engineering document , and α3 is the weight of KL divergence, is the KL divergence between the i-th sub-document in the k-th version engineering document​​ With the i-th sub-document in the (k-1)-th version of the project document The KL divergence is given by α4, where α4 is the weight of semantic similarity.

[0068] The backup module is used to obtain the user's operation information for a certain version, and calculate the information protection factor of a certain sub-document in the certain version based on the similarity. When the information protection factor exceeds a preset threshold, the module backs up the sub-document in the certain version and the same sub-document in the previous version of the project document to complete the management of important information in the project document.

[0069] Specifically, information protection factors include:

[0070]

[0071] in, Let α be the information protection factor for the i-th sub-document in the k-th version of the project document, and let α′ be the adjustment factor for the information protection factor. For user operations on the i-th sub-document in the k-th version of the project document Influence function The i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document semantic similarity The dynamic weight adjustment function as a parameter, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The similarity score, where n is the number of sub-documents. For the i-th sub-document in the k-th version of the project document The amount of modification.

[0072] Specifically, dynamic weight adjustment function include:

[0073]

[0074] Where γ′ is the first adjustment factor of the dynamic weight adjustment function, and δ′ is the second adjustment factor of the dynamic weight adjustment function.

[0075] Specifically, the user operation affects the i-th sub-document in the k-th version of the project document. Influence function include:

[0076]

[0077] Where λ1 is the first adjustment factor of the influence function. For users in time window T window The i-th sub-document within the k-th version of the project document The number of edits, λ2 is the second adjustment factor of the influence function. For the user, the i-th sub-document in the k-th version of the project document The number of times the edit was accepted. For the user, the i-th sub-document in the k-th version of the project document The total number of edits, λ3 is the third adjustment factor of the influence function, w insert The weight of the insertion operation. For the user, the i-th sub-document in the k-th version of the project document The number of insertion operations, w delete As the weight of the deletion operation, For the user, the i-th sub-document in the k-th version of the project document The number of times the deletion operation was performed, w replace For the weight of the replacement operation, For the user, the i-th sub-document in the k-th version of the project document The number of replacement operations, λ4 is the fourth adjustment factor of the influence function, and τ is the fifth adjustment factor of the influence function. For the u-th sub-document in the k-th version of the project document Current modification time, For the i-th sub-document in the k-th version of the project document The last time it was modified.

[0078] Specifically, all weights and adjustment factors are fitted using gradient descent or ant colony optimization.

[0079] Specifically, the i-th sub-document in the k-th version of the project document is calculated using the Word2Vec or BERT model. With the i-th sub-document in the (k-1)-th version of the project document semantic similarity

[0080] Example 3

[0081] This invention also proposes a storage medium storing multiple instructions, which are used to implement the aforementioned method for managing electronic archives in a single set based on panoramic services.

[0082] Optionally, in this embodiment, the storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0083] Optionally, in the embodiment, the storage medium is configured to store program code for performing the following steps: step 101, obtaining all historical versions of the engineering document, dividing each version of the engineering document into a plurality of sub-documents, and extracting the engineering document of a certain version and the previous version thereof;

[0084] Specifically, the sub-documents include: title, paragraph, table containing engineering parameters, and conclusion of the engineering document.

[0085] Step 102, calculating the similarity between a certain sub-document in the certain version and the same sub-document of the engineering document of the previous version;

[0086] Specifically, the similarity between the i-th sub-document in the k-th version of the engineering document and the u-th sub-document in the k-1-th version of the engineering document is calculated as

[0087]

[0088] wherein, α1 is the weight of the cosine similarity, is the cosine similarity between the u-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document , α2 is the weight of the Jaccard similarity, is the Jaccard similarity between the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document , α3 is the weight of the KL divergence, is the KL divergence between the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document , and α4 is the weight of the semantic similarity.

[0089] Step 103, obtaining the operation of the user on the certain version, and combining the similarity, calculating the information protection factor of a certain sub-document in the certain version, when the information protection factor exceeds a preset threshold, backing up the certain sub-document in the certain version and the same sub-document of the engineering document of the previous version, to complete the management of important information of the engineering document.

[0090] Specifically, the information protection factor includes:

[0091]

[0092] wherein, ​Let α be the information protection factor for the i-th sub-document in the k-th version of the project document, and let α′ be the adjustment factor for the information protection factor. For user operations on the i-th sub-document in the k-th version of the project document Influence function The i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document semantic similarity The dynamic weight adjustment function as a parameter, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The similarity score, where n is the number of sub-documents. For the i-th sub-document in the k-th version of the project document The amount of modification.

[0093] Specifically, dynamic weight adjustment function include:

[0094]

[0095] Where γ′ is the first adjustment factor of the dynamic weight adjustment function, and δ′ is the second adjustment factor of the dynamic weight adjustment function.

[0096] Specifically, the user operation affects the i-th sub-document in the k-th version of the project document. Influence function include:

[0097]

[0098] Where λ1 is the first adjustment factor of the influence function. For users in time window T window The i-th sub-document within the k-th version of the project document The number of edits, λ2 is the second adjustment factor of the influence function. For the user, the i-th sub-document in the k-th version of the project document The number of times the edit was accepted. For the user, the i-th sub-document in the k-th version of the project document The total number of edits, λ3 is the third adjustment factor of the influence function, w insert The weight of the insertion operation. For the user, the i-th sub-document in the k-th version of the project document The number of insertion operations, w delete As the weight of the deletion operation, For the user, the i-th sub-document in the k-th version of the project document The number of times the deletion operation was performed, w replace For the weight of the replacement operation, For the user, the i-th sub-document in the k-th version of the project document The number of replacement operations, λ4 is the fourth adjustment factor of the influence function, and τ is the fifth adjustment factor of the influence function. For the i-th sub-document in the k-th version of the project document Current modification time, For the i-th sub-document in the k-th version of the project document The last time it was modified.

[0099] Specifically, all weights and adjustment factors are fitted using gradient descent or ant colony optimization.

[0100] Specifically, the i-th sub-document in the k-th version of the project document is calculated using the Word2Vec or BERT model. With the i-th sub-document in the (k-1)-th version of the project document semantic similarity

[0101] Example 4

[0102] This invention also proposes an electronic device, including a processor and a storage medium connected to the processor. The storage medium stores multiple instructions, which can be loaded and executed by the processor to enable the processor to execute the aforementioned method for managing single-set electronic archives based on panoramic services.

[0103] Specifically, the electronic device in this embodiment can be a computer terminal, which may include one or more processors and a storage medium.

[0104] The storage medium can be used to store software programs and modules, such as the electronic archive single-set management method based on panoramic services in this embodiment of the invention. The corresponding program instructions / modules allow the processor to execute various functional applications and data processing by running the software programs and modules stored in the storage medium, thus realizing the aforementioned electronic archive single-set management method based on panoramic services. The storage medium may include high-speed random access storage media, and may also include non-volatile storage media, such as one or more magnetic storage systems, flash memory, or other non-volatile solid-state storage media. In some instances, the storage medium may further include storage media remotely configured relative to the processor, which can be connected to the terminal via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0105] The processor can call the information and application program stored in the storage medium through the transmission system to execute the following steps: step 101, obtaining all historical versions of the engineering document, dividing each version of the engineering document into a plurality of sub-documents, and extracting the engineering document of a certain version and the previous version thereof;

[0106] Specifically, the sub-document includes: a title, a paragraph, a table containing an engineering parameter, and a conclusion of the engineering document.

[0107] Step 102, calculating the similarity of a certain sub-document in the certain version and the same sub-document of the engineering document of the previous version;

[0108] Specifically, the similarity of the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document is which includes:

[0109]

[0110] wherein, α1 is the weight of the cosine similarity, is the cosine similarity of the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document , α2 is the weight of the Jaccard similarity, is the Jaccard similarity of the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document , α3 is the weight of the KL divergence, is the KL divergence of the i-th sub-document in the k-th version of the engineering document and the i-th sub-document in the k-1-th version of the engineering document , and α4 is the weight of the semantic similarity.

[0111] Step 103, obtaining the operation of the user on the certain version, and combining the similarity, calculating the information protection factor of a certain sub-document in the certain version, when the information protection factor exceeds a preset threshold, backing up the certain sub-document in the certain version and the same sub-document of the engineering document of the previous version, to complete the management of important information of the engineering document.

[0112] Specifically, the information protection factor includes:

[0113]

[0114] wherein, Let α be the information protection factor for the i-th sub-document in the k-th version of the project document, and let α′ be the adjustment factor for the information protection factor. For user operations on the i-th sub-document in the k-th version of the project document Influence function The i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document semantic similarity The dynamic weight adjustment function as a parameter, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The similarity score, where n is the number of sub-documents. For the i-th sub-document in the k-th version of the project document The amount of modification.

[0115] Specifically, dynamic weight adjustment function include:

[0116]

[0117] Where γ′ is the first adjustment factor of the dynamic weight adjustment function, and δ′ is the second adjustment factor of the dynamic weight adjustment function.

[0118] Specifically, the user operation affects the i-th sub-document in the k-th version of the project document. Influence function include:

[0119]

[0120] Where λ1 is the first adjustment factor of the influence function. For users in time window T window The i-th sub-document within the k-th version of the project document The number of edits, λ2 is the second adjustment factor of the influence function. For the user, the i-th sub-document in the k-th version of the project document The number of times the edit was accepted. For the user, the i-th sub-document in the k-th version of the project document The total number of edits, λ3 is the third adjustment factor of the influence function, w insert The weight of the insertion operation. For the user, the i-th sub-document in the k-th version of the project document The number of insertion operations, w delete As the weight of the deletion operation, For the user, the i-th sub-document in the k-th version of the project document The number of times the deletion operation was performed, w replace For the weight of the replacement operation, For the user, the i-th sub-document in the k-th version of the project document The number of replacement operations, λ4 is the fourth adjustment factor of the influence function, and τ is the fifth adjustment factor of the influence function. For the u-th sub-document in the k-th version of the project document Current modification time, For the i-th sub-document in the k-th version of the project document The last time it was modified.

[0121] Specifically, all weights and adjustment factors are fitted using gradient descent or ant colony optimization.

[0122] Specifically, the i-th sub-document in the k-th version of the project document is calculated using the Word2Vec or BERT model. With the i-th sub-document in the (k-1)-th version of the project document semantic similarity

[0123] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0124] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0125] In the several embodiments provided by this invention, it should be understood that the disclosed technical content can be implemented in other ways. The system embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces, indirect coupling or communication connection between units or modules, and may be electrical or other forms.

[0126] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0127] In addition, each function unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software function unit.

[0128] The integrated unit, if realized in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the technical solutions of the present application, essentially or in the form of a contribution to the prior art, or all or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, and includes several instructions for causing a computer machine (which can be a personal computer, a server, or a network machine, etc.) to execute all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: a U disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a mobile hard disk, a magnetic disk or an optical disk, and various media that can store program codes.

[0129] Obviously, the above embodiments are merely examples for clear illustration, and are not a limitation on the implementation modes. Based on the above description, other different forms of changes or variations can be made by those of ordinary skill in the art. Here, it is not necessary and also impossible to enumerate all the implementation modes. The obvious changes or variations derived therefrom are still within the protection scope of the present application.

Claims

1. A method for managing electronic archives in a single set system based on a panoramic service, for managing engineering documents in a single set system, characterized in that, The method comprises the following steps: acquiring all historical versions of the engineering document, dividing the engineering document of each version into multiple sub-documents, and extracting the engineering document of a certain version and the previous version thereof; calculating the similarity between a certain sub-document in the certain version and the same sub-document of the engineering document of the previous version; acquiring the operation of the user on the certain version, and combining the similarity to calculate the information protection factor of a certain sub-document in the certain version, and when the information protection factor exceeds a preset threshold, backing up the certain sub-document in the certain version and the same sub-document of the engineering document of the previous version, so as to complete the management of important information of the engineering document; the information protection factor comprises: in, Let α be the information protection factor of the i-th sub-document in the k-th version of the project document, and let α′ be the adjustment factor of the information protection factor. For user operations on the i-th sub-document in the k-th version of the project document Influence function The i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document semantic similarity The dynamic weight adjustment function as a parameter, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The similarity score, where n is the number of sub-documents. For the i-th sub-document in the k-th version of the project document The amount of modification; a function of the user operation on the i-th sub-document in the k-th version engineering document comprises:​ Where λ1 is the first adjustment factor of the influence function. For users in time window T window The i-th sub-document within the k-th version of the project document The number of edits, λ2 is the second adjustment factor of the influence function. For the user, the i-th sub-document in the k-th version of the project document The number of times the edit was accepted. For the user, the i-th sub-document in the k-th version of the project document The total number of edits, λ3 is the third adjustment factor of the influence function, w insert The weight of the insertion operation. For the user, the i-th sub-document in the k-th version of the project document The number of insertion operations, w delete As the weight of the deletion operation, For the user, the i-th sub-document in the k-th version of the project document The number of times the deletion operation was performed, w replace For the weight of the replacement operation, For the user, the i-th sub-document in the k-th version of the project document The number of replacement operations, λ4 is the fourth adjustment factor of the influence function, and τ is the fifth adjustment factor of the influence function. For the i-th sub-document in the k-th version of the project document Current modification time, For the i-th sub-document in the k-th version of the project document The last time it was modified.

2. The electronic file management method based on the panoramic service according to claim 1, wherein, Dynamic weight adjustment function Comprising: wherein γ' is the first adjustment factor of the dynamic weight adjustment function, and δ' is the second adjustment factor of the dynamic weight adjustment function.

3. The electronic file management method based on the panoramic service according to claim 1, wherein, the i-th sub-document in the k-th version engineering document similarity with the i-th sub-document in the k-1-th version engineering document comprises:​ Where α1 is the weight of the cosine similarity, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The cosine similarity is given by α2, where α2 is the weight of the Jaccard similarity. For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The Jaccard similarity, where α3 is the weight of the KL divergence. For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The KL divergence is given by α4, where α4 is the weight of semantic similarity.

4. The electronic file single set management method based on panoramic service according to any one of claims 1-3, characterized in that, All weights and adjustment factors are fitted by using the gradient descent method or the ant colony algorithm.

5. The electronic file management method based on the panoramic service according to claim 1, wherein, Computing semantic similarity of the i-th sub-document in the k-th version engineering document with the i-th sub-document in the k-1-th version engineering document by Word2Vec or BERT model ​ 6. The electronic file management method based on the panoramic service according to claim 1, wherein, The sub-document comprises the title, the paragraph, the table containing the engineering parameter, and the conclusion of the engineering document.

7. An electronic file single set management system based on panoramic service, used for single set management of engineering documents, characterized in that, The method comprises the following steps: a document division module, which is used for acquiring all historical versions of the engineering document, dividing the engineering document of each version into multiple sub-documents, and extracting the engineering document of a certain version and the previous version thereof; a similarity calculation module, which is used for calculating the similarity between a certain sub-document in the certain version and the same sub-document of the engineering document of the previous version; a backup module, which is used for acquiring the operation of the user on the certain version, combining the similarity to calculate the information protection factor of a certain sub-document in the certain version, and when the information protection factor exceeds a preset threshold, backing up the certain sub-document in the certain version and the same sub-document of the engineering document of the previous version, so as to complete the management of important information of the engineering document; the information protection factor comprises: in, Let α be the information protection factor of the i-th sub-document in the k-th version of the project document, and let α′ be the adjustment factor of the information protection factor. For user operations on the i-th sub-document in the i-th version of the project document Influence function The i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document semantic similarity The dynamic weight adjustment function as a parameter, For the i-th sub-document in the k-th version of the project document With the i-th sub-document in the (k-1)-th version of the project document The similarity score, where n is the number of sub-documents. For the i-th sub-document in the k-th version of the project document The amount of modification; A function of the influence of user operations on the i-th sub-document in the k-th version engineering document includes: includes: Where λ1 is the first adjustment factor of the influence function. For users in time window T window The i-th sub-document within the k-th version of the project document The number of edits, λ2 is the second adjustment factor of the influence function. For the user, the i-th sub-document in the k-th version of the project document The number of times the edit was accepted. For the user, the i-th sub-document in the k-th version of the project document The total number of edits, λ3 is the third adjustment factor of the influence function, w insert The weight of the insertion operation. For the user, the i-th sub-document in the k-th version of the project document The number of insertion operations, w delete As the weight of the deletion operation, For the user, the i-th sub-document in the k-th version of the project document The number of times the deletion operation was performed, w replace For the weight of the replacement operation, For the user, the i-th sub-document in the k-th version of the project document The number of replacement operations, λ4 is the fourth adjustment factor of the influence function, and τ is the fifth adjustment factor of the influence function. For the i-th sub-document in the k-th version of the project document Current modification time, For the i-th sub-document in the k-th version of the project document The last time it was modified.

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