Method and system for migrating electronic documents between Internet platforms

Abstract

The present invention discloses a method and system for migrating electronic documents between Internet platforms, including: monitoring whether there is a newly stored word document on each local storage server; the management server parses the article expression structure in the newly stored word document; obtains the corresponding sample documents on each migration server, and converts each document sample in the article sample set into the corresponding sample structure; performs similarity matching on the article expression structure of the newly stored word document and the sample structure set formed by the article sample set; when it is determined that the article expression structure of the newly stored word document belongs to a member in the sample structure set, the newly stored word document is sent to the corresponding migration server. The present invention completes the migration of the updated word document on the local server and realizes the storage process based on the storage system by parsing the relevant content elements in the word document.

Description

Technical Field

[0001] The present invention relates to the technical field of electronic document storage, and in particular to a method and system for migrating electronic documents between Internet platforms. Background Art

[0002] Microsoft Office Word is a word processor application from Microsoft. Word provides users with tools for creating professional and elegant documents, helping users save time and get elegant and beautiful results. Microsoft Office Word is the most popular word processing program. Word provides many easy-to-use document creation tools, and also provides a rich set of functions for creating complex documents. The migration of word documents between Internet platforms needs to be realized, and Word documents can form electronic documents with the structure of special articles and store them in local servers. The existence of a large number of word documents with article structures on local servers will cause the Internet platform system to be unable to adaptively classify and migrate word documents for storage, which will cause great confusion in the storage of word documents on the Internet platform system. It is also inconvenient for subsequent users to process the stored word documents accordingly. The existing Internet platform system is not well suited to the migration and storage management needs of such word documents. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides a method and system for migrating electronic documents between Internet platforms. By parsing the article content elements in the word document, the key elements of the article content can be extracted from the word article content, thereby completing the migration of the word document updated on the local server based on the storage system and realizing the storage process.

[0004] In order to solve the above problems, the present invention proposes a method for migrating electronic documents between Internet platforms, the method comprising:

[0005] Monitor whether there is a new stored word document on each local storage server, and when it is determined that there is a new stored word document on each local storage server, the management server obtains the new stored word document;

[0006] The management server parses the article expression structure in the newly stored word document, wherein the article expression structure adopts a tree structure representation method;

[0007] Obtaining sample documents corresponding to each migration server, and forming an article sample set based on the sample texts corresponding to each migration server, and converting each document sample in the article sample set into a corresponding sample structure, wherein the sample structure adopts a tree structure representation method;

[0008] Performing similarity matching between the article expression structure of the newly stored word document and the sample structure set formed by the article sample set, and determining whether the article expression structure of the newly stored word document belongs to a member of the sample structure set;

[0009] When it is determined that the article expression structure of the newly stored word document belongs to a member of the sample structure set, the corresponding migration server is obtained, and the newly stored word document is sent to the corresponding migration server;

[0010] The migration server receives the newly stored word document and stores the newly stored word document.

[0011] The monitoring of whether there is a new stored word document on each local storage server includes:

[0012] Based on the preset time interval, monitor whether there is a new stored word document on each local storage server.

[0013] The monitoring based on the preset time interval whether there is a new stored word document on each local storage server includes:

[0014] Acquire internal identification information of each word document stored on a local storage server, wherein the internal identification information includes a storage time log;

[0015] Parse the storage time log in the internal identification information, and determine whether the storage time log exceeds the last monitoring time. If it exceeds the last monitoring time, determine that there is a newly stored word document on the local storage server. The word document corresponding to the storage time log that exceeds the last monitoring time is the newly stored word document.

[0016] The management server analyzes the article expression structure of the newly stored word document including:

[0017] Generate an empty article structure tree based on the article content of the newly stored word document;

[0018] The article title is used as the root node of the article structure tree, and the sub-titles and / or paragraphs of the article are added to the root node as child nodes according to the hierarchical relationship, and each child node is assigned a value.

[0019] Performing similarity matching on the article expression structure of the newly stored word document and the sample structure set formed by the article sample set includes:

[0020] Extract each sample member in the sample structure set, and perform similarity matching based on each sample member and the article expression structure of the stored document;

[0021] The similarity of the tree structure between the article expression structure and each member in the sample structure set is calculated layer by layer, and the similarity value between the document expression structure and each member is calculated to form a similarity value set.

[0022] The step of determining whether the article expression structure of the newly stored word document belongs to a member of the sample structure set comprises:

[0023] Extract the maximum similarity value from the similarity value set;

[0024] It is determined whether the maximum similarity value is greater than a preset threshold value. If it is determined that the maximum similarity value is greater than the preset threshold value, it is determined that the article expression structure of the newly stored word document belongs to a member of the sample structure set.

[0025] The obtaining of the corresponding migration server and sending the newly stored word document to the corresponding migration server comprises:

[0026] The encryption algorithm corresponding to the migration server is obtained, and the newly stored word document is encrypted based on the encryption algorithm, and the encrypted newly stored word document is sent to the corresponding migration server.

[0027] Accordingly, the present invention also proposes an Internet platform system, the system comprising:

[0028] Several local storage servers are used to store the new stored word documents corresponding to the local end;

[0029] A management server is used to monitor whether there is a newly stored word document on each local storage server, and when it is determined that there is a newly stored word document on each local storage server, obtain the newly stored word document; parse the article expression structure of the newly stored word document, and the article expression structure adopts a tree structure representation method; obtain the corresponding document samples on each migration server, and form an article sample set based on the corresponding document samples on each migration server, and convert each document sample in the article sample set into a corresponding sample structure, and the sample structure adopts a tree structure representation method; perform similarity matching on the article expression structure of the newly stored word document and the sample structure set formed by the article sample set, and determine whether the article expression structure of the newly stored word document belongs to a member of the sample structure set; when it is determined that the article expression structure of the newly stored word document belongs to a member of the sample structure set, send the newly stored word document to the corresponding migration server;

[0030] A plurality of migration servers are provided, each of the plurality of migration servers stores one or more document samples and stores the newly stored word documents corresponding to the document samples.

[0031] The system also includes a plurality of API gateways, each of which communicates with more than one local storage server, and the plurality of API gateways sends the word documents updated by the plurality of local storage servers to the management server.

[0032] The embodiment of the present invention can monitor the updated word documents on different local storage servers based on the Internet platform, and use a tree structure representation method to parse the article content in the word document, so that the updated word document can be quickly matched to the corresponding migration server, so that it can be adaptively stored in the migration server according to the article content of the word document. The migration server can be implemented by a distributed storage system, which can be widely used in e-government and network office environments, and also facilitates the unified and regular management of word documents in e-government and network office environments, and reduces errors in word document regularization. In order to ensure the transmission security of electronic spreadsheet documents between servers and storage servers, the word document is encrypted, which can effectively play a role in the secure transmission of word documents. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1 is a schematic diagram of the structure of an Internet platform system in an embodiment of the present invention;

[0035] Figure 2 It is a flow chart of a method for migrating electronic documents between Internet platforms in an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] Specifically, Figure 1 A schematic diagram of the structure of an Internet platform system in an embodiment of the present invention is shown. The Internet platform system is used to store word documents. The system includes: a plurality of local storage servers, a management server, a plurality of migration servers, etc.

[0038] Several local storage servers are used to store the new stored word documents on the corresponding local terminals.

[0039] A management server is used to monitor whether there is a new stored word document on each local storage server, and when it is determined that there is a new stored word document on each local storage server, obtain the new stored word document; parse the article expression structure of the new stored word document, and the article expression structure adopts a tree structure representation method; obtain the corresponding document samples on each migration server, and form an article sample set based on the corresponding document samples on each migration server, and convert each document sample in the article sample set into a corresponding sample structure, and the sample structure adopts a tree structure representation method; perform similarity matching on the article expression structure of the new stored word document and the sample structure set formed by the article sample set, and determine whether the article expression structure of the new stored word document belongs to a member of the sample structure set; when it is determined that the article expression structure of the new stored word document belongs to a member of the sample structure set, send the new stored word document to the corresponding migration server.

[0040] A plurality of migration servers are provided, each of the plurality of migration servers stores one or more document samples and stores the newly stored word documents corresponding to the document samples.

[0041] Specifically, the several local storage servers include: a first local storage server, a second local storage server, a third local storage server, a fourth local storage server, a fifth local storage server, ..., an Nth local storage server. Each of the several local storage servers can store local word documents in combination with the actual application environment, that is, each local storage server can be a PC computer, or a server under a small local area network. Each local storage server can receive new stored word documents in the local area and store the new stored word documents. It can be a department in a small area (office department), or a site in a small area (for example, a school has several office departments).

[0042] Specifically, several local storage servers are connected here through several API gateways, and several API gateways send new stored word documents on several local storage servers to the management server. Each of the several API gateways communicates with more than one first local storage server. The several API gateways here include: the first API gateway, the second API gateway, ..., the Nth API gateway. Each API gateway can connect to the local storage server in the local area network and realize the communication between the local storage server and the management server. That is, the first API gateway communicates with the first local storage server, the second local storage server, and the third local storage server, and realizes the communication between the first local storage server, the second local storage server, and the third local storage server and the management server, and the second API gateway communicates with the fourth local storage server and the fifth local storage server, and realizes the communication between the fourth local storage server and the fifth local storage server and the management server.

[0043] Specifically, the several migration servers here include: the first migration server, the second migration server, ..., the Nth migration server, each migration server stores one or more document samples, and the document sample is a word document with a special article structure. For example, the first migration server may store a word document with a special article structure based on mathematics teaching, the second migration server may store a word document with a special article structure based on Chinese teaching, the third migration server may store a word document with a special article structure based on English teaching, etc., which can construct word documents with different special article structures based on different application scenarios. Each migration server may correspond to a document server, such as a storage server for a mathematics subject library, or a storage server for a Chinese teaching subject library, etc., which facilitates the rule management of related articles.

[0044] It should be noted that the management server is also used to filter newly stored word documents and remove invalid newly stored word documents. The filtering process of newly stored word documents here includes: setting up a filtering phrase for the word document and storing the filtering phrase in a filtering library, wherein the filtering phrase at least includes file identification information, article title, article directory, number of paragraphs, language expression type in the article, etc.; filtering the acquired newly stored word documents based on the filtering library to remove invalid newly stored word documents. Here, by acquiring newly stored word documents on different local servers and then filtering the newly stored word documents based on filtering rules, the filtering process can realize the processing of invalid newly stored word documents on the one hand, and reduce the number of newly stored word documents processed by the system end on the other hand, so that the efficiency of the entire parsing process is correspondingly improved, and the storage space occupied by the system end is also reduced.

[0045] When the management server sends the newly stored word document to the corresponding migration server, it first obtains the encryption algorithm corresponding to the migration server, encrypts the newly stored word document based on the encryption algorithm, and sends the encrypted newly stored word document to the corresponding migration server. That is, the management server encrypts the newly stored word document based on the encryption algorithm, that is, adds an encryption header to the newly stored word document, and the encryption header includes a document encryption module, a document decryption module and a verification module; the newly stored word document is encrypted based on the document encryption module in the encryption header. Several migration servers can decrypt the encrypted newly stored word document, that is, after the corresponding migration server receives the encrypted newly stored word document, the verification module is triggered to verify the information of the corresponding newly stored word document; after the verification is passed, the newly stored word document is decrypted based on the document decryption module in the encryption header. Here, the verification module verifies the storage authority between the article expression structure of the newly stored word document and the migration server, and the encryption header includes encryption and decryption keys, encryption and decryption algorithms, the owner of the word document, and authorized users or organization information. In this way, the security of the newly stored word document transmitted between the management server and the migration server is guaranteed. The newly stored word document is encrypted and decrypted, which can effectively provide security protection for the newly stored word document and prevent unsafe risks caused by tampering and cracking during the file transmission process.

[0046] Based on the Internet platform system in the embodiment of the present invention, it can monitor the word documents updated on different local storage servers, and use the tree structure representation method to parse the article content in the word document, so that the updated word document can be quickly matched to the corresponding migration server, so that it can be adaptively stored in the migration server according to the article content of the word document, so that the word document updated on the local storage server can be quickly and effectively classified based on the article content, and it is also convenient for the management and reference of the word document. The migration server can be implemented by a distributed storage system, which can be widely used in e-government and network office environments, and it is also convenient for e-government and network office environments to uniformly manage word documents and reduce errors in word document regularization. In order to ensure the transmission security of electronic spreadsheet documents between servers and storage servers, word documents are encrypted, which can effectively play a role in the secure transmission of word documents.

[0047] based on Figure 1The method for migrating electronic documents between Internet platforms implemented by the Internet platform system shown, the method comprising: monitoring whether there is a new stored word document on each local storage server, and when it is determined that there is a new stored word document on each local storage server, the management server obtains the new stored word document; the management server parses the article expression structure of the new stored word document, and the article expression structure adopts a tree structure representation method; obtains the corresponding sample documents on each migration server, and forms an article sample set based on the corresponding sample text on each migration server, and converts each document sample in the article sample set into a corresponding sample structure, and the sample structure adopts a tree structure representation method; performs similarity matching on the article expression structure of the new stored word document and the sample structure set formed by the article sample set, and determines whether the article expression structure of the new stored word document belongs to a member of the sample structure set; when it is determined that the article expression structure of the new stored word document belongs to a member of the sample structure set, obtains the corresponding migration server, and sends the new stored word document to the corresponding migration server; the migration server receives the new stored word document and stores the new stored word document.

[0048] specific, Figure 2 A flow chart of a method for migrating electronic documents between Internet platforms in an embodiment of the present invention is shown, and the method includes:

[0049] start;

[0050] S201, monitoring whether there is a new word document stored on each local storage server, if there is a new word document stored, proceed to S202, otherwise proceed to S209;

[0051] S202, when it is determined that there is a new word document stored on each local storage server, the management server obtains the new word document;

[0052] It should be noted that when the management server obtains the newly stored word document, it also needs to filter the newly stored word document to remove invalid newly stored word documents. The filtering process of the newly stored word document here includes: setting up a filtering phrase for the word document, and storing the filtering phrase in a filtering library, wherein the filtering phrase at least includes file identification information, article title, article directory, number of paragraphs, language expression type in the article, etc.; filtering the obtained newly stored word document based on the filtering library to remove invalid newly stored word documents. Here, by obtaining the newly stored word documents on different local servers, and then filtering the newly stored word documents based on the filtering rules, the filtering process can realize the processing of invalid newly stored word documents on the one hand, and reduce the number of newly stored word documents processed by the system end on the other hand, so that the efficiency of the entire parsing process is correspondingly improved, and the storage space occupied by the system end is also reduced.

[0053] S203, the management server parses the article expression structure of the newly stored word document, the article expression structure adopts a tree structure representation method;

[0054] It should be noted that the data elements in the article structure tree can be organized according to branch relationships to represent the feature model of the article.

[0055] The management server analyzes the article expression structure of the newly stored word document, including: generating an empty article structure tree based on the article content of the newly stored word document; taking the article title as the root node of the article structure tree, adding the subtitles and / or paragraphs of the article under the root node as child nodes according to the hierarchical relationship, and assigning a value to each child node. The amplitude here represents the value of the feature of the child node.

[0056] The value of each child node can be composed of two parts. One is the ratio of all the words included under the node to the entire article, and the other is the relevance of the words contained in these words to the topic of the article. The product of the two is the value of this node.

[0057] S204, obtaining the sample documents corresponding to each migration server, and forming an article sample set based on the sample texts corresponding to each migration server, and converting each document sample in the article sample set into a corresponding sample structure, wherein the sample structure adopts a tree structure representation method;

[0058] Here, the corresponding sample documents on each migration server are first obtained, and then the article structure tree of the sample document is constructed. The same method is used to construct the article structure tree.

[0059] The method of obtaining the sample documents corresponding to each migration server specifically includes: when the management server receives a newly stored word document, it generates a broadcast instruction and sends the broadcast instruction to each migration server, and the broadcast instruction is used to request the sample documents corresponding to each migration server; the management server receives feedback information fed back by each storage server based on the broadcast instruction, and the feedback information stores the sample documents set in each migration server. In this way, the sample documents on each migration server are retrieved in real time, and the sample documents can be dynamically set as the documents in the migration server are adapted.

[0060] S205, performing similarity matching between the article expression structure of the newly stored word document and the sample structure set formed by the article sample set;

[0061] Here, similarity matching is performed on the sample structure set formed by the article expression structure of the newly stored word document and the article sample set, including: extracting each sample member in the sample structure set, and performing similarity matching based on each sample member and the article expression structure of the stored document; calculating the similarity of the tree structure between the article expression structure and each member in the sample structure set layer by layer, and calculating the similarity value between the document expression structure and each member to form a similarity value set.

[0062] Specifically, the similarity of the tree structure between the article expression structure and each member in the sample structure set is calculated layer by layer, including: inputting the article expression structure and the sample structure of a member in the sample structure set, comparing the article expression structure with the sample structure of a member layer by layer, each node can be regarded as a set of vectors, and then calculating the similarity of the two vectors. If the depths of the two trees are inconsistent, only the layer of the tree with a shallow depth is compared and the calculation is terminated. Finally, the approximation of each layer is accumulated to obtain a final approximation score. The higher the score, the closer the two trees are.

[0063] S206, determining whether the article expression structure of the newly stored word document belongs to a member of the sample structure set, if it does, proceeding to S207, otherwise proceeding to S209;

[0064] During the specific implementation process, the maximum similarity value in the similarity value set is extracted; and it is determined whether the maximum similarity value is greater than a preset threshold. If it is determined that the maximum similarity value is greater than the preset threshold, it is determined that the article expression structure of the newly stored word document belongs to a member of the sample structure set.

[0065] The threshold setting here is to avoid judging only by similarity value. For example, some article structure trees have great substantive differences from the sample structures in the sample structure set. After similarity matching with all members, the overall similarity value is low, and the maximum value cannot meet the threshold condition, indicating that the newly stored word document itself does not meet the requirements of this migration. The preset threshold can be set according to the actual application scenario. For example, the similarity value must reach more than 90% to meet the migration process.

[0066] S207, when it is determined that the article expression structure of the newly stored word document belongs to a member of the sample structure set, obtaining the corresponding migration server, and sending the newly stored word document to the corresponding migration server;

[0067] Specifically, the corresponding migration server can be mapped out through the maximum similarity value in S206, that is, the maximum similarity value can first map out the corresponding sample structure, and the sample structure belongs to the corresponding migration server, so the corresponding migration server is obtained.

[0068] Specifically, sending the newly stored word document to the corresponding migration server includes: obtaining the encryption algorithm corresponding to the migration server, encrypting the newly stored word document based on the encryption algorithm, and sending the encrypted newly stored word document to the corresponding migration server. That is, the management server encrypts the newly stored word document based on the encryption algorithm, that is, adding an encryption header to the newly stored word document, the encryption header includes a document encryption module, a document decryption module and a verification module; encrypting the newly stored word document based on the document encryption module in the encryption header. Several migration servers can decrypt the encrypted newly stored word document, that is, after the corresponding migration server receives the encrypted newly stored word document, trigger the verification module to verify the information of the corresponding newly stored word document; after the verification passes, the newly stored word document is decrypted based on the document decryption module in the encryption header. Here, the verification module verifies the storage authority between the article expression structure of the newly stored word document and the migration server, and the encryption header includes encryption and decryption keys, encryption and decryption algorithms, the owner of the word document, and authorized users or organization information. In this way, the security of the newly stored word document transmitted between the management server and the migration server is guaranteed. The newly stored word document is encrypted and decrypted, which can effectively provide security protection for the newly stored word document and prevent unsafe risks caused by tampering and cracking during the file transmission process.

[0069] S208, the migration server receives the newly stored word document, and stores the newly stored word document;

[0070] S209: Trigger a monitoring process based on a preset time interval.

[0071] It should be noted that the management server here monitors whether there are new word documents stored on each local storage server based on a preset time interval, by obtaining the internal identification information of each word document stored on the local storage server, the internal identification information includes a storage time log; parsing the storage time log in the internal identification information, and judging whether the storage time log exceeds the last monitoring time, if it exceeds the last monitoring time, it is judged that there is a new word document stored on the local storage server, and the word document corresponding to the storage time log exceeding the last monitoring time is a new word document. This time interval can refer to hours or days to set a specific monitoring time point.

[0072] Based on the method in the embodiment of the present invention, the updated word documents on different local storage servers can be monitored, and the article content in the word document can be parsed using a tree structure representation method, so that the updated word document can be quickly matched to the corresponding migration server, so that it can be adaptively stored in the migration server according to the article content of the word document, so that the updated word document on the local storage server can be quickly and effectively classified based on the article content, and it is also convenient for the management and reference of the word document. The migration server can be implemented using a distributed storage system, which can be widely used in e-government and network office environments, and it is also convenient for the unified and regular management of word documents in e-government and network office environments, and reduces errors in the regularization of word documents. In order to ensure the transmission security of electronic spreadsheet documents between the server and the storage server, the word document is encrypted, which can effectively play a role in the secure transmission of the word document.

[0073] The embodiment of the present application also provides a computer storage medium, in which instructions are stored, and when the instructions are executed on a computer or a processor, the computer or the processor executes one or more steps of the method described in any of the above embodiments. If the components of the above-mentioned device are implemented in the form of software functional units and sold or used as independent products, they can be stored in the computer-readable storage medium. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer product is stored in a computer-readable storage medium.

[0074] The embodiments of the present invention are described in detail above. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A method for migrating electronic documents between Internet platforms, characterized in that: The method comprises: Monitor whether there is a new stored word document on each local storage server, and when it is determined that there is a new stored word document on each local storage server, the management server obtains the new stored word document; The management server parses the article expression structure in the newly stored word document, wherein the article expression structure adopts a tree structure representation method; Obtaining sample documents corresponding to each migration server, and forming an article sample set based on the sample texts corresponding to each migration server, and converting each document sample in the article sample set into a corresponding sample structure, wherein the sample structure adopts a tree structure representation method; Performing similarity matching between the article expression structure of the newly stored word document and the sample structure set formed by the article sample set, and determining whether the article expression structure of the newly stored word document belongs to a member of the sample structure set; When it is determined that the article expression structure of the newly stored word document belongs to a member of the sample structure set, the corresponding migration server is obtained, and the newly stored word document is sent to the corresponding migration server; The migration server receives the newly stored word document and stores the newly stored word document; The similarity matching between the article expression structure of the newly stored word document and the sample structure set formed by the article sample set includes: extracting each sample member in the sample structure set, and performing similarity matching based on each sample member with the article expression structure of the stored document; calculating the similarity of the tree structure between the article expression structure and each member in the sample structure set layer by layer, and calculating the similarity value between the document expression structure and each member to form a similarity value set; Calculating the similarity of the tree structure between the article expression structure and each member in the sample structure set layer by layer includes: inputting the article expression structure and the sample structure of a member in the sample structure set, comparing the article expression structure with the sample structure of a member layer by layer, treating each node as a set of vectors, and then calculating the similarity of the two vectors; if the depths of the two trees are inconsistent, only the layer of the tree with a shallow depth is compared and the calculation is terminated; finally, accumulating the similarity of each layer to obtain a final similarity score, and the higher the score, the closer the two trees are.

2. The method for migrating electronic documents between Internet platforms as claimed in claim 1, characterized in that: The monitoring of whether there is a new stored word document on each local storage server includes: Based on the preset time interval, monitor whether there is a new stored word document on each local storage server.

3. The method for migrating electronic documents between Internet platforms as claimed in claim 2, characterized in that: The monitoring based on the preset time interval whether there is a new stored word document on each local storage server includes: Acquire internal identification information of each word document stored on a local storage server, wherein the internal identification information includes a storage time log; Parse the storage time log in the internal identification information, and determine whether the storage time log exceeds the last monitoring time. If it exceeds the last monitoring time, determine that there is a newly stored word document on the local storage server. The word document corresponding to the storage time log that exceeds the last monitoring time is the newly stored word document.

4. The method for migrating electronic documents between Internet platforms as claimed in claim 1, characterized in that: The management server analyzes the article expression structure of the newly stored word document including: Generate an empty article structure tree based on the article content of the newly stored word document; The article title is used as the root node of the article structure tree, and the sub-titles and / or paragraphs of the article are added to the root node as child nodes according to the hierarchical relationship, and each child node is assigned a value.

5. The method for migrating electronic documents between Internet platforms as claimed in claim 4, characterized in that: The step of determining whether the article expression structure of the newly stored word document belongs to a member of the sample structure set comprises: Extract the maximum similarity value from the similarity value set; It is determined whether the maximum similarity value is greater than a preset threshold value. If it is determined that the maximum similarity value is greater than the preset threshold value, it is determined that the article expression structure of the newly stored word document belongs to a member of the sample structure set.

6. The method for migrating electronic documents between Internet platforms according to any one of claims 1 to 5, characterized in that: The obtaining of the corresponding migration server and sending the newly stored word document to the corresponding migration server comprises: The encryption algorithm corresponding to the migration server is obtained, and the newly stored word document is encrypted based on the encryption algorithm, and the encrypted newly stored word document is sent to the corresponding migration server.

7. An Internet platform system, characterized in that: The system comprises: Several local storage servers are used to store the new stored word documents corresponding to the local end; A management server is used to monitor whether there is a newly stored word document on each local storage server, and when it is determined that there is a newly stored word document on each local storage server, obtain the newly stored word document; parse the article expression structure of the newly stored word document, and the article expression structure adopts a tree structure representation method; obtain the corresponding document samples on each migration server, and form an article sample set based on the corresponding document samples on each migration server, and convert each document sample in the article sample set into a corresponding sample structure, and the sample structure adopts a tree structure representation method; perform similarity matching on the article expression structure of the newly stored word document and the sample structure set formed by the article sample set, and determine whether the article expression structure of the newly stored word document belongs to a member of the sample structure set; when it is determined that the article expression structure of the newly stored word document belongs to a member of the sample structure set, send the newly stored word document to the corresponding migration server; A plurality of migration servers, each of the plurality of migration servers storing one or more document samples and storing the newly stored word documents corresponding to the document samples; The similarity matching between the article expression structure of the newly stored word document and the sample structure set formed by the article sample set includes: extracting each sample member in the sample structure set, and performing similarity matching based on each sample member with the article expression structure of the stored document; calculating the similarity of the tree structure between the article expression structure and each member in the sample structure set layer by layer, and calculating the similarity value between the document expression structure and each member to form a similarity value set; Calculating the similarity of the tree structure between the article expression structure and each member in the sample structure set layer by layer includes: inputting the article expression structure and the sample structure of a member in the sample structure set, comparing the article expression structure with the sample structure of a member layer by layer, treating each node as a set of vectors, and then calculating the similarity of the two vectors; if the depths of the two trees are inconsistent, only the layer of the tree with a shallow depth is compared and the calculation is terminated; finally, accumulating the similarity of each layer to obtain a final similarity score, and the higher the score, the closer the two trees are.

8. The Internet platform system according to claim 7, characterized in that: The system also includes a plurality of API gateways, each of which communicates with more than one local storage server, and the plurality of API gateways sends the word documents updated by the plurality of local storage servers to the management server.

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