A blockchain construction method based on DIKWP model for essential semantic computing and reasoning

Abstract

The present invention provides a method for constructing a blockchain based on a DIKWP model for essential semantic computing and reasoning, comprising the steps of: constructing a blockchain based on a DIKWP system, wherein the blockchain includes one or more of a data chain, an information chain, a knowledge chain, and a wisdom chain; constructing a user's DIKWP model to identify the user's intention; obtaining the user's content to be put on the chain, and typifying the content to be put on the chain according to the user's intention to obtain corresponding type resources, wherein the types of the type resources include data resources, information resources, knowledge resources, and wisdom resources, and the obtained type resources are called type resources to be put on the chain; and storing the type resources to be put on the chain in the corresponding blockchain. The method further improves the security of the content on the chain on the basis of the essential intention of the user, and the blockchain constructed by the method occupies fewer storage resources than the traditional blockchain.

Description

Technical Field

[0001] The present invention relates to the field of blockchain technology, and in particular to a blockchain construction method based on a DIKWP model for essential semantic computing and reasoning. Background Art

[0002] Blockchain is a distributed shared ledger and database with the characteristics of decentralization, immutability, full traceability, traceability, collective maintenance, openness and transparency. Based on the above characteristics, blockchain has broad application prospects and has quickly become the focus of social attention. Blockchain is essentially a "data" chain. The hash algorithm is the basis for building blocks and confirming transaction integrity. With the development of cryptography, the cracking of conventional hash algorithms is no longer as difficult as scholars thought in the past. The data security of blockchain needs to be further improved. On the other hand, as the amount of stored data increases, new blocks are constantly added to the blockchain, the length of the blockchain will become longer and longer, and the requirements for storage performance will also increase. It is necessary to improve its data storage method. Summary of the invention

[0003] In view of this, the purpose of the present invention is to provide a blockchain construction method based on the DIKWP model for essential semantic computing and reasoning, so as to overcome or at least partially solve the above-mentioned problems existing in the prior art.

[0004] To achieve the above-mentioned purpose of the invention, the present invention provides a blockchain construction method based on the DIKWP model for essential semantic computing and reasoning, and the method comprises the following steps:

[0005] Construct a blockchain based on the DIKWP system, wherein the blockchain includes one or more of a data chain, an information chain, a knowledge chain, and a wisdom chain;

[0006] Build the user's DIKWP model to identify user intent;

[0007] Obtain the user's content to be uploaded to the chain, categorize the content to be uploaded to the chain according to the user's intention, and obtain corresponding type resources. The types of type resources include data resources, information resources, knowledge resources, and wisdom resources. The obtained type resources are called type resources to be uploaded to the chain;

[0008] Store the resources to be uploaded to the corresponding blockchain.

[0009] Furthermore, the construction of the user's DIKWP model and identification of the user's intention specifically includes the following steps:

[0010] Obtain user-related content, type the user-related content, and obtain user type resources;

[0011] Build data models, information models, knowledge models, intelligence models and intention models according to user type resources;

[0012] Traverse the user intent model nodes to identify user intent.

[0013] Furthermore, the content to be uploaded to the chain is categorized according to the user's intention to obtain corresponding type resources, specifically: determining the upload method according to the user's intention, categorizing the content to be uploaded to the chain according to the upload method, and obtaining the type resources to be uploaded to the chain.

[0014] Furthermore, the chain-up method includes:

[0015] Convert all contents to be uploaded to the chain into data resources, information resources, knowledge resources and wisdom resources respectively, and upload them to the data chain, information chain, knowledge chain and wisdom chain respectively;

[0016] The content to be uploaded to the chain is randomly converted into a type of resource, and uploaded to the corresponding blockchain according to the type of the converted resource;

[0017] Divide the content to be uploaded into multiple parts, convert each part into different types of resources, and upload them to the corresponding blockchain respectively;

[0018] Based on the principle of highest efficiency and least conversion times, the content to be uploaded to the chain is converted into resources of the type to be uploaded to the chain, and the resources of the type to be uploaded to the corresponding blockchain.

[0019] Furthermore, the method of uploading to the chain is determined according to the user's intention, specifically: determining the user's intention to strike a balance between cognitive distance and acquisition efficiency by identifying the user's intention, and selecting a corresponding method of uploading to the chain according to the user's balance intention, the cognitive distance being the cognitive gap between the user and the attacker regarding the same content, and the acquisition efficiency being the efficiency of the data acquirer in recognizing the content uploaded by the user.

[0020] Furthermore, the calculation method of the cognitive distance specifically includes:

[0021] Build the attacker’s DIKWP model;

[0022] Compare the user's DIKWP model with the attacker's DIKWP model to determine the semantic difference between the user and the attacker for the same concept in the content to be uploaded to the chain;

[0023] The cognitive distance between the user and the attacker is calculated based on the overall semantic difference between the user and the attacker for all concepts in the type of resources to be uploaded to the chain.

[0024] Furthermore, the storing of the content to be uploaded to the corresponding blockchain specifically includes:

[0025] Before storing the type resource to be chained in the corresponding blockchain, traverse the type resources stored in all blocks in the blockchain to find the chained type resources that can obtain the type resource to be chained by performing modal operations;

[0026] If the resource of the chained type is found, only the index information and modal operation method of the resource of the chained type are written into the new block, and the new block is uploaded to the blockchain;

[0027] If the resource of the chained type is not found, the chained resource will be written into a new block and the new block will be uploaded to the blockchain.

[0028] Furthermore, the modal operation mode includes same-modal operation and cross-modal operation.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention provides a blockchain construction method based on the DIKWP model for essential semantic computing and reasoning, and constructs a blockchain based on the DIKWP system. When a user needs to upload content to the blockchain, the user's intention is identified by building the user's DIKWP model, and the content to be uploaded is typed according to the user's intention to obtain the type of resources to be uploaded. By storing the type of resources to be uploaded in the corresponding blockchain, the security of the content on the chain is further improved on the basis of the essential intention of the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0032] Figure 1 It is a schematic diagram of the overall process of a blockchain construction method based on the DIKWP model for essential semantic computing and reasoning provided by an embodiment of the present invention.

[0033] Figure 2 It is a schematic diagram of the user intention recognition process provided by an embodiment of the present invention.

[0034] Figure 3 It is a schematic diagram of the cognitive distance calculation process provided by an embodiment of the present invention.

[0035] Figure 4 It is a schematic diagram of the chain-up process of resources of the type to be chained provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0036] The principles and features of the present invention are described below in conjunction with the accompanying drawings. The enumerated embodiments are only used to explain the present invention and are not used to limit the scope of the present invention.

[0037] Reference Figure 1 This embodiment provides a blockchain construction method based on the DIKWP model for essential semantic computing and reasoning, and the method includes the following steps:

[0038] S101. Construct a blockchain based on the DIKWP system, wherein the blockchain includes one or more of a data chain, an information chain, a knowledge chain, and a wisdom chain. The DIKWP system refers to data, information, knowledge, wisdom, and purpose.

[0039] S102: Build the user's DIKWP model and identify the user's intention. The purpose of identifying the user's intention is to extract the user's intention to upload his data to the blockchain, so that in the subsequent steps, the content on the blockchain can be preprocessed accordingly according to the user's essential intention.

[0040] S103. Obtain the user's content to be uploaded to the chain, type the content to be uploaded to the chain according to the user's intention, and obtain corresponding type resources. The types of the type resources include data resources, information resources, knowledge resources and wisdom resources. The obtained type resources are called type resources to be uploaded to the chain.

[0041] S104, storing the resources to be uploaded to the corresponding blockchain. In this embodiment, each blockchain is used to store a type of resource, for example, the data chain is used to store data resources, the information chain is used to store information resources, and so on.

[0042] Reference Figure 2 In step S102, the DIKWP model of the user is constructed to identify the user's intention, which specifically includes the following steps:

[0043] S201: Obtain user-related content, categorize the user-related content, and obtain user-type resources.

[0044] The user-related content may be content actively input by the user, content published by the user obtained through the network, such as content published on social platforms, or content about the user published by a third-party platform or others. The obtained user-related content is categorized, that is, it is abstracted and conceptualized into data resources, information resources, knowledge resources, wisdom resources, and intention resources.

[0045] The data resources are discrete objects without binding intentions collected by directly observing a segment of existing semantics. Data resources are divided into numerical data, probabilistic data, logical data, and range data according to different attributes and structures. Numerical data is a specific numerical value obtained by observation, measurement or simple calculation, including Arabic numerals, time, date, or numerical data associated with character data. Probabilistic data represents an inference or prediction of the development trend of other things based on personal cognition, and is an uncertain description. Logical data uses (yes / no) to represent data resources, which can filter and classify things and use digital codes to represent each category. Range data is a data type used to describe a value of a certain data type. It can express multiple data of a single data object. The higher the overlap of range data, the more similar it is. Range data is divided into bounded ranges and unbounded ranges according to whether there are boundaries.

[0046] The information resource is formed by data directly or indirectly associated with one or more intentions and is time-sensitive. Information can be partial order information, usage information and change information. Partial order information is the comparison of data objects of the same type or different types based on the comparison intention at the same standard level under the premise of the same attributes. Usage information is to analyze the functional attributes of data based on the usage intention to achieve the ultimate goal. Change information is a description of the process of modifying the selected object and causing changes.

[0047] The knowledge resource is a structured and formalized category reasoning of data resources and / or information resources or empirical rules derived based on probability statistics. The wisdom resource reflects the user's value orientation and is used to describe universal values ​​and the user's personal values. The intention resource is used to reflect what the user wants to do and what purpose he wants to achieve.

[0048] In addition, the type resources can be converted through modal operations to obtain new type resources. The modal operations include homomodal operations and cross-modal operations. Homomodal operations are to obtain new type resources by operating on type resources of the same modality. Cross-modal operations are to obtain new type resources by operating on type resources of different modalities. For example, new information resources can be obtained by performing cross-modal operations on data resources and information resources.

[0049] S202, construct data models, information models, knowledge models, wisdom models and intention models respectively according to user type resources. After the user-related content is categorized, the corresponding DIKWP model is constructed according to the type resources, for example, a data model is constructed according to data resources, an information model is constructed according to information resources, and so on. The data model, information model, knowledge model, wisdom model, intention model, etc. can all be represented in the form of a graph.

[0050] S203: traverse the user intention model nodes to identify the user intention.

[0051] Each node in the user intent model corresponds to an intent. By typifying user-related content, multiple user intents may be obtained at the same time. Each intent can be further subdivided into multiple specific intents. In the intent model, the further splitting of intent is manifested in the form of parent nodes and child nodes. The purpose of traversing the user intent model nodes in this step is to find out the intent content related to the user uploading content to the blockchain, so as to determine how to pre-process the on-chain content in the subsequent steps.

[0052] Users may have different intentions for the content uploaded to the blockchain. For example, for some unimportant content, users may just want to store and share the content; while for some more important content, users have higher requirements for confidentiality. In this embodiment, when typifying the content on the chain, the user's essential intention for the content on the chain is taken into account, and the chain method is determined according to the user's intention. Different typification methods are adopted for the content on the chain according to different chain methods, and the corresponding type resources to be chained are obtained, so that the typed resources on the chain of the same content are different according to different user intentions, and the protection of the content on the chain is also different.

[0053] Exemplarily, the chaining method includes:

[0054] All contents to be uploaded to the chain are converted into data resources, information resources, knowledge resources and wisdom resources, and uploaded to the data chain, information chain, knowledge chain and wisdom chain respectively. For example, if a user wants to upload the contents of a book to the chain, when this method of uploading to the chain is adopted, all the contents of the book are converted into data resources, information resources, knowledge resources and wisdom resources respectively, and the obtained type resources are uploaded to the corresponding DIKWP system blockchain according to their types.

[0055] The content to be uploaded to the chain is randomly converted into a type of resource, and uploaded to the corresponding blockchain according to the type of the converted resource.

[0056] Divide the content to be uploaded into multiple parts, convert each part into different types of type resources, and upload them to the corresponding blockchains respectively. For example, the content to be uploaded can be divided into a first part and a second part, and the first part is typed as a data resource and uploaded to the data chain, and the second part is typed as an information resource and uploaded to the information chain. It can be understood that in the above three ways of uploading, when the content to be uploaded is typed, the number of conversions can be multiple times to obtain different types of resources. For example, after the content to be uploaded is typed to obtain data resources and information resources, the data resources and information resources can be further modally operated to obtain knowledge resources and wisdom resources.

[0057] Based on the principle of highest efficiency and least conversion times, the content to be uploaded to the chain is converted into resources of the type to be uploaded to the corresponding blockchain. This type of chaining method is used to process content to be uploaded to the chain that users only intend to store. The importance of this content is not high, so when processing this content, we should try to pursue high efficiency and occupy less computer resources.

[0058] As a preferred example, the method of determining the chaining method according to the user's intention is specifically as follows: by identifying the user's intention, the user's intention to balance the cognitive distance and the acquisition efficiency is determined, and the corresponding chaining method is selected according to the user's intention to balance. The cognitive distance is the cognitive gap between the user and the attacker for the same content, and the acquisition efficiency is the efficiency of the data acquirer to recognize the content uploaded by the user. For the user, out of consideration for content protection, it is definitely hoped that it is difficult for the attacker to effectively recognize the content on the blockchain, so the greater the cognitive distance between the attacker and the user, the better. In terms of data sharing, if the content on the blockchain is difficult or even impossible for the data acquirer to recognize, then the content quality will be greatly reduced. Therefore, it is necessary to determine the user's intention to balance the cognitive distance and the acquisition efficiency, so that the chaining method can strike a balance between the two based on the user's intention. For example, if the user is more inclined to protect the content from being leaked to the attacker, then when choosing the chaining method, a method that can increase the difficulty of the content on the chain to be recognized should be selected, and the acquisition efficiency will be reduced accordingly, and vice versa.

[0059] As a preferred example, refer to Figure 3 , the method for calculating the cognitive distance specifically includes the following steps:

[0060] S301, establish the DIKWP model of the attacker. In the network, the real identity of the attacker is usually difficult to accurately grasp, but the purpose and intention of stealing content may be similar, such as seeking improper benefits. In this embodiment, when establishing the DIKWP model of the attacker, if the real identity of the attacker is unclear, the attacker is regarded as a hypothetical "person" and the DIKWP model is established based on the capabilities that such attackers usually have, the actions and intentions that may be taken against the target content, etc.

[0061] S302, based on the comparison of the user's DIKWP model with the attacker's DIKWP model, determine the semantic difference between the user and the attacker for the same concept in the resources to be put on the chain. Since the educational background, social experience, and areas of expertise of the user and the attacker are usually different, the same concept may have different understandings and interpretations for different people, resulting in the semantic differences between the multiple concepts in the resources to be put on the chain for the user and the attacker. It is necessary to analyze the essential semantics represented by different concepts based on the DIKWP models of the user and the attacker, respectively, to form their respective semantic systems, and then determine the semantic difference between the user and the attacker for the same concept in the content to be put on the chain based on the comparison between the semantic systems.

[0062] S303. Calculate the cognitive distance between the user and the attacker based on the overall semantic differences between the user and the attacker for all concepts in the resource type to be chained. The more overall semantic differences, the greater the cognitive distance; the fewer overall semantic differences, the closer the cognitive distance. Exemplarily, more weights can be appropriately assigned to the semantic differences of important concepts so that their semantic differences can more obviously affect the cognitive distance.

[0063] As a preferred example, refer to Figure 4 , storing the content to be uploaded to the corresponding blockchain specifically includes the following steps:

[0064] S401. Before storing the type of resources to be put on the chain in the corresponding blockchain, traverse the type of resources stored in all blocks in the blockchain to find the type of resources that have been put on the chain and can obtain the type of resources to be put on the chain by performing modal operations.

[0065] S402. If the on-chain type resource is found, only the index information and modal operation method of the on-chain type resource are written into a new block, and the new block is uploaded to the blockchain.

[0066] S403: If the on-chain type resource is not found, the on-chain resource is written into a new block, and the new block is uploaded to the blockchain.

[0067] In the traditional blockchain, as the content of stored data increases, the length of the blockchain will become longer and longer. When the node records the content of the blockchain locally, it will occupy more and more data resources. In this embodiment, before storing the type of resources to be chained in the corresponding blockchain, the type of resources stored in all blocks in the blockchain (including other blockchains that do not store type resources corresponding to the type of resources to be chained) are traversed to find out whether there are chained type resources that can obtain the type of resources to be chained through modal operations. If so, it means that the type of resources to be chained are reachable based on the type of resources already on the chain. It is only necessary to write the index information and modal operation method of the type of resources that can reach the type of resources to be chained after modal operation into the new block and add it to the blockchain, thereby reducing the size of the block and slowing down the speed of increasing the amount of data stored in the blockchain, so that less storage resources can be occupied when storing the same content. When the content of the type of resource needs to be obtained later, the corresponding type of resource that has been chained is found according to the index information in the block, and the type of resource is converted according to the modal operation method recorded in the block.

[0068] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A blockchain construction method based on the DIKWP model for essential semantic computing and reasoning, characterized in that: The method comprises the following steps: Construct a blockchain based on the DIKWP system, wherein the blockchain includes one or more of a data chain, an information chain, a knowledge chain, and a wisdom chain; Build the user's DIKWP model to identify user intent; Obtain the user's content to be uploaded to the chain, categorize the content to be uploaded to the chain according to the user's intention, and obtain corresponding type resources. The types of type resources include data resources, information resources, knowledge resources, and wisdom resources. The obtained type resources are called type resources to be uploaded to the chain; Store the resources to be uploaded to the corresponding blockchain; The construction of the user's DIKWP model and identification of the user's intention specifically includes the following steps: Obtain user-related content, type the user-related content, and obtain user type resources; Build data models, information models, knowledge models, intelligence models and intention models according to user type resources; Traverse the user intent model nodes and identify the user intent; The categorizing the content to be uploaded to the chain according to the user intention to obtain the corresponding type resource is specifically: determining the upload method according to the user intention, categorizing the content to be uploaded to the chain according to the upload method, and obtaining the type resource to be uploaded to the chain; The chain-up method includes: Convert all contents to be uploaded to the chain into data resources, information resources, knowledge resources and wisdom resources respectively, and upload them to the data chain, information chain, knowledge chain and wisdom chain respectively; The content to be uploaded to the chain is randomly converted into a type of resource, and uploaded to the corresponding blockchain according to the type of the converted resource; Divide the content to be uploaded into multiple parts, convert each part into different types of resources, and upload them to the corresponding blockchain respectively; Based on the principle of highest efficiency and least conversion times, the content to be uploaded to the chain is converted into resources of the type to be uploaded to the chain, and the resources of the type to be uploaded to the corresponding blockchain; The method of uploading to the chain is determined according to the user's intention, specifically: determining the user's intention to strike a balance between cognitive distance and acquisition efficiency by identifying the user's intention, and selecting the corresponding method of uploading to the chain according to the user's intention to strike a balance, wherein the cognitive distance is the cognitive gap between the user and the attacker regarding the same content, and the acquisition efficiency is the efficiency of the data acquirer in recognizing the content uploaded by the user.

2. According to claim 1, a blockchain construction method based on the DIKWP model for essential semantic computing and reasoning is characterized in that: The calculation method of the cognitive distance specifically includes: Build the attacker’s DIKWP model; Compare the user's DIKWP model with the attacker's DIKWP model to determine the semantic difference between the user and the attacker for the same concept in the content to be uploaded to the chain; The cognitive distance between the user and the attacker is calculated based on the overall semantic difference between the user and the attacker for all concepts in the resources to be uploaded to the chain.

3. According to claim 1, a blockchain construction method based on the DIKWP model for essential semantic computing and reasoning is characterized in that: The storing of the resources to be uploaded to the corresponding blockchain specifically includes: Before storing the type resource to be chained in the corresponding blockchain, traverse the type resources stored in all blocks in the blockchain to find the chained type resources that can obtain the type resource to be chained by performing modal operations; If the resource of the chained type is found, only the index information and modal operation method of the resource of the chained type are written into the new block, and the new block is uploaded to the blockchain; If the resource of the type that has been put on the chain is not found, the resource of the type to be put on the chain is written into a new block, and the new block is uploaded to the blockchain.

4. According to claim 3, a blockchain construction method based on the DIKWP model for essential semantic computing and reasoning is characterized in that: The modal operation mode includes same-modal operation and cross-modal operation.

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