CN110322327A - A kind of laboratory personnel shopping recommended method and device based on block chain technology - Google Patents
A kind of laboratory personnel shopping recommended method and device based on block chain technology Download PDFInfo
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Abstract
The invention discloses a kind of laboratory personnel shopping recommended method and device based on block chain technology, method includes: when detecting that consumer enters market, the facial image for obtaining consumer, identifies the facial image of consumer, obtains the identity information of consumer；The historical purchase information of consumer is obtained according to the identity information of consumer, block chain stores the corresponding historical purchase information of identity information of each consumer；Proposed algorithm mark is obtained, the intelligent contract for executing corresponding types is identified according to proposed algorithm, to obtain the whole blocks for the condition that meets；The whole blocks for the condition that meets are aggregated into history shopping list, according to history shopping list to consumer's Recommendations information.The embodiment of the present invention can make each businessman in market share user's history purchase information on block chain, targetedly carry out merchandise news recommendation to client, help client to be quickly found out oneself desired commodity, improve recommendation efficiency.
Description
Technical Field
The invention relates to the technical field of block chains, in particular to a shopping recommendation method and device for market consumers based on a block chain technology.
Background
The traditional market recommends the advertisement to the consumer mainly through snatching the user data of oneself, or, utilize web crawler technology to snatch the user data of other websites and carry out big data analysis to realize commodity advertisement recommendation.
In the prior art, historical purchase information of each user recorded by each merchant is closed and independent, and in terms of advertisement recommendation, due to the fact that the data volume is small and the recommendation algorithm is single, the advertisement recommendation accuracy and flexibility of each merchant are poor.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
In view of the defects of the prior art, the present invention aims to provide a shopping recommendation method and device for shopping consumers in a shopping mall based on a block chain technology, and aims to solve the problems that in the prior art, historical purchase information of each user recorded by each merchant is closed and independent, and in advertisement recommendation, due to the small data amount and the single recommendation algorithm, the advertisement recommendation accuracy and flexibility of each merchant are poor.
The technical scheme of the invention is as follows:
a shopping recommendation method for market consumers based on a blockchain technology, the method comprising:
when detecting that a consumer enters a market, acquiring a face image of the consumer, identifying the face image of the consumer, and acquiring identity information of the consumer;
acquiring historical purchase information of the consumers according to the identity information of the consumers, and storing the historical purchase information corresponding to the identity information of each consumer in a block chain;
acquiring a recommended algorithm identifier, and executing a corresponding type of intelligent contract according to the recommended algorithm identifier to acquire all blocks meeting conditions;
and summarizing all blocks meeting the conditions into a historical shopping list, and recommending commodity information to the consumers according to the historical shopping list.
Optionally, when it is detected that the consumer enters the mall, the obtaining of the face image of the consumer, the identifying of the face image of the consumer, and before obtaining the identity information of the consumer, includes:
the method comprises the steps that monitoring equipment is arranged at an entrance of a market in advance, and the monitoring equipment shoots face images of consumers at the entrance of a commodity.
Optionally, the recommendation algorithm identification comprises a user-based collaborative filtering algorithm identification and an article-based collaborative filtering algorithm identification, the intelligent contract comprises a user intelligent contract and an article intelligent contract,
the acquiring of the recommendation algorithm identifier executes the corresponding type of intelligent contract according to the recommendation algorithm identifier to acquire all blocks meeting the conditions, and includes:
acquiring a recommendation algorithm identifier, and judging whether the recommendation algorithm identifier is a collaborative filtering algorithm identifier based on a user or a collaborative filtering algorithm identifier based on an article;
if the collaborative filtering algorithm is based on the user, selecting and executing a user intelligent contract to obtain all blocks containing historical purchase information corresponding to other users related to the collaborative filtering algorithm of the user;
and if the article-based collaborative filtering algorithm is adopted, selecting and executing an article intelligent contract to obtain all blocks containing historical purchase information corresponding to the user identity information.
Optionally, after the summarizing all blocks meeting the condition into the historical shopping list, the method further includes:
packaging the historical shopping list into block data;
and sending the block data to a consensus node in a block chain so that the consensus node verifies the block data.
Optionally, the consensus algorithm of the consensus verification adopts a share authorization certification algorithm,
the consensus node verifies the block data, including:
when the block chain node detects that the number of times of consensus verification failure is larger than a preset threshold value, determining a malicious area chain node, wherein the malicious area chain node is a node which does not sign and verifies the block data and causes the maximum number of times of consensus verification failure;
the block link points prohibit the malicious block link points from participating in consensus verification, reallocate shares in the rest of the block link points and verify the block data in a consensus manner;
and when the block chain node detects that the number of times of failure of the consensus verification is smaller than a preset threshold value, continuing to perform the consensus verification on the block data.
Optionally, the obtaining of the recommendation algorithm identifier and executing the corresponding type of intelligent contract according to the recommendation algorithm identifier includes:
acquiring a recommendation algorithm identifier access request, wherein the recommendation algorithm identifier access request also comprises a first certificate, and the block chain stores a second certificate; judging whether the second certificate unlocks the first certificate or not;
if yes, acquiring a recommended algorithm identifier, and selecting and executing the intelligent contract of the corresponding type according to the recommended algorithm identifier;
if not, acquiring the recommended algorithm identification, and not executing any intelligent contract.
Optionally, the commodity information includes a commodity name, a name of a shop where the commodity is located, an address of the shop where the commodity is located, and a navigation diagram of the shop where the commodity is located.
The invention further provides a shopping recommendation device for market consumers based on the block chain technology, which comprises at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the above-described method for recommending mall consumer shopping based on block chain technology.
Yet another embodiment of the present invention provides a non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform the above-described method for recommending shopping for a mall consumer based on a block chain technique.
Another embodiment of the present invention provides a computer program product comprising a computer program stored on a non-volatile computer readable storage medium, the computer program comprising program instructions which, when executed by a processor, cause the processor to perform the above-described method for recommending shopping for store consumers based on blockchain technology.
Has the advantages that: compared with the prior art, the embodiment of the invention can enable all merchants of a shopping mall to share the historical purchasing information of users on the block chain, recommend commodity information to consumers in a targeted manner, help the consumers to find the commodities desired by the consumers quickly, and improve the recommendation efficiency.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a block chain system of a preferred embodiment of a shopping recommendation method for market consumers based on block chain technology;
FIG. 2 is a flowchart illustrating a preferred embodiment of a shopping recommendation method for shopping mall consumers based on block chain technology;
FIG. 3 is a schematic diagram of a hardware structure of a preferred embodiment of a shopping mall consumer shopping recommendation device based on the blockchain technology.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is described in further detail below. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. Embodiments of the present invention will be described below with reference to the accompanying drawings.
The block chain technique is also called a distributed book, and is a distributed internet database technique. A network constructed based on the blockchain technique may be referred to as a blockchain network, where the blockchain network includes a plurality of blockchain nodes, each node corresponds to at least one blockchain, and each blockchain includes at least one block. The block chain technology has the characteristics of decentralization, openness and transparency, no tampering, trustiness and the like, so that the block chain technology is more and more widely applied.
In general, a blockchain network includes a data layer, a network layer, a consensus layer, and an intelligent contract layer. The data layer encapsulates a bottom layer data block, relevant basic data such as data encryption and a time stamp and a basic algorithm; the network layer comprises a distributed networking mechanism, a data transmission mechanism, a data verification mechanism and the like, and the consensus layer encapsulates various consensus algorithms of the network nodes; the intelligent contract layer encapsulates various scripts, algorithms and intelligent contracts.
Referring to fig. 1, fig. 1 is a schematic structural diagram of a block chain system according to an embodiment of the present invention. As shown in fig. 1, the blockchain system 100 includes an electronic device 101, a normal node 102, a proxy node 103, and a consensus node 104.
The electronic device 101 is in communication connection with a common node 102, the common node 102 is in communication connection with a proxy node 103, and the proxy node 103 is also in communication connection with a consensus node 104. The communication between each blockchain node supports a Point-to-Point communication (P2P).
The electronic equipment 101 provides a commodity page for a user to purchase commodities, when the user finishes purchasing commodities on the commodity page, the ordinary node 102 of the electronic equipment 101 sends a commodity purchasing success request, and the ordinary node 102 forwards the commodity purchasing success request to the proxy node 103, so that the proxy node 103 selects an intelligent contract of a corresponding type to execute;
the electronic device 101 may also recommend the item to the user on an item page.
The regular nodes 102 hold the current electronic money and have the right to vote in the blockchain system. The common node 102 can perform related transaction operations, but has no block packaging accounting right, and can only synchronously record block data from the related node with the packaging accounting right;
in some embodiments, the generic node 102 may also perform commodity information maintenance work.
The agent node 103 is written with an intelligent contract code, and the normal node 102 sends the original block data to the agent node 103, and triggers the intelligent contract of the agent node 103, so that the intelligent contract of the agent node executes the original block data. Where the regular nodes 102 maintain an intelligent contract list that records a list of various proxy nodes that are capable of executing intelligent contracts. Each time the ordinary node 102 receives the original block data, the ordinary node 102 calls up the intelligent contract list, finds out the addresses of the respective proxy nodes from the intelligent contract list, and sends the original block data to the respective proxy nodes.
In this embodiment, the agent node 103 may pre-store multiple types of intelligent contracts, and may parse the execution type of the intelligent contract according to the trigger request sent by the general node 102. And the agent node 103 executes the corresponding intelligent contract according to the execution type of the analyzed intelligent contract.
When a certain proxy node goes into fault, other proxy nodes broadcast the address of the certain proxy node to the whole network, the common node 102 monitors the broadcast information and updates the intelligent contract list, and when the original data of the block is sent subsequently, the common node 102 does not send data to the certain proxy node 103, so as to improve the working efficiency. The code of the intelligent contract is written according to the business scenario logic.
After executing the original block data according to the intelligent contract, the proxy node 103 outputs the block data to be verified. Then, the proxy node 103 also signs the block data to be verified, and packages and sends the signed block data to the consensus node 104. The consensus node 104 verifies the signed block data by using the public key of the proxy node 103, and if the verification is successful, the signed block data is considered to be sent by the valid proxy node 103, and then the consensus processing is performed on the block data. If the verification is not successful, the signed block data is considered to be sent by the illegal proxy node 103. For example, the proxy node 103 uses its own private key to perform a signature operation on the hash content of the current block, and obtains the signature.
The consensus node 104 is used for consensus verification of the block data uploaded by the proxy node 103. The consensus node 104 may support any one of the following consensus algorithms: proof of Work (PoW), Proof of rights and interests (PoS), Proof of equity authority (released Proof of stamp, DPoS), Practical Byzantine Fault Tolerance (PBFT), authorized Byzantine Fault Tolerance (DBFT), and so on.
Each consensus node 104 needs to register with the proxy node 103, and after successful registration, the consensus node is a legal consensus node. The registration process is as follows:
1. the consensus node 104 submits registration information to the agent node 103; wherein the registration information includes one or more of the following: the device serial number SN, the user information, and the miner wallet address of the consensus node 104;
2. the proxy node 103 checks the registration information; the checking process comprises the following steps: it is checked whether the SN numbering format is correct, whether the SN is present in a database, whether the SN has been bound to other users, etc.
3. The proxy node 103 records registration information.
4. The proxy node 103 returns the registration result to the consensus node 104.
5. The proxy node 103 broadcasts the new registration data to the blockchain system 100.
In the blockchain system 100, blocks are carriers for storing transaction summary information, each block includes a block header and a block body, and information recorded in the block header is used to identify the block itself, a summary of information of a previous block, and a position of the block in the entire account book. The block body is used for storing the transaction summary information and verifying the transaction information and keeping the transaction from being tampered.
The block chain is formed by connecting each block one by one according to the sequence of the generation time. In the whole block chain, the first block is called a created block, the block schedule of the first block is 0, the block height of each subsequent block is sequentially added with 1, and the hash value of the previous block header is written in the block header. And all blocks on the block chain are linked by the last block head hash value on each block.
Therefore, the block chains have non-tamper-proof properties. Based on the above, the embodiment of the invention provides a shopping recommendation method for market consumers based on a block chain technology, which is applied to markets.
Referring to fig. 2, fig. 2 is a flowchart illustrating a shopping recommendation method for shopping mall consumers based on the block chain technology according to a preferred embodiment of the present invention. As shown in fig. 2, it includes the steps of:
s100, when detecting that a consumer enters a market, acquiring a face image of the consumer, identifying the face image of the consumer, and acquiring identity information of the consumer;
s200, acquiring historical purchase information of the consumers according to the identity information of the consumers, and storing the historical purchase information corresponding to the identity information of each consumer in a block chain;
step S300, acquiring a recommended algorithm identifier, and executing a corresponding type of intelligent contract according to the recommended algorithm identifier to acquire all blocks meeting conditions;
and S400, summarizing all blocks meeting the conditions into a historical shopping list, and recommending commodity information to the consumers according to the historical shopping list.
In a specific implementation, the Block chain provided in the embodiment of the present invention may adopt one of a Public Block chain (Public Block Chains), a joint Block chain (Consortium Block Chains), and a Private Block chain (Private Block Chains).
When a person is detected to enter a mall in step S100 and an APP of the mall is opened through the electronic device, the electronic device sends an access request to a common node, the common node in the mall block chain acquires a face image of a consumer, the face image is acquired through a preset monitoring device, the common node performs face recognition on the face image, and after the face recognition, identity information of the consumer is acquired, where the identity information of the consumer may be an account number or other identifier registered by the user in the APP mall, and the identity information of each consumer is unique.
In step S200, historical shopping information owned by the consumer is obtained according to the identified identity information of the consumer, where the historical shopping information may be historical shopping information of a commodity owned by the consumer and recorded. Each merchant can add a common node in the blockchain, and after the merchant purchases a commodity, the merchant can generate historical purchase information corresponding to the user identity information from the purchase information of the user at this time and upload the historical purchase information to the common node, so that the blockchain stores the historical purchase information corresponding to the identity information of each consumer.
The recommendation algorithm identifier in step S300 is used to identify the algorithm type of the recommendation algorithm, where the recommendation algorithm identifier can be edited by the designer according to the business requirement. Because the data required by each recommendation algorithm is different, the agent node can extract the user data corresponding to the recommendation algorithm for the electronic equipment according to the requirements of the electronic equipment. Therefore, according to the corresponding algorithm, the corresponding intelligent contract is executed, and all the corresponding blocks are obtained.
In step S400, the commodity information includes a commodity name, a name of a shop where the commodity is located, an address of the shop where the commodity is located, and a navigation diagram of the shop where the commodity is located. Therefore, on one hand, the commodity is recommended to the consumer, the name and the address of the shop where the commodity is located and the navigation schematic diagram of the shop are also provided, the consumer can conveniently find the corresponding position of the commodity, and convenience is brought to the consumer for shopping. When the electronic device recommends a commodity to the user according to the historical shopping list, the method specifically includes: the electronic equipment analyzes historical purchase information corresponding to other users associated with the collaborative filtering algorithm based on the user by adopting a UserCF algorithm, and recommends commodities for the user according to an analysis result. Or the electronic equipment analyzes historical purchase information corresponding to the user identity information by adopting an ItemCF algorithm, and recommends commodities for the user according to an analysis result.
On one hand, as the blockchain has the characteristics of non-falsification, decentralization and high transparency, merchants rely on the historical purchase information of users recorded by the blockchain, and can share the historical purchase information of the users on the blockchain, so that the data volume of the historical purchase information of the users on the blockchain is large, and the merchants can recommend advertisements to the users more accurately. On the other hand, the block chain can provide corresponding user data for the merchants according to the recommendation algorithm selected by the merchants, so that the merchants can recommend advertisements to the users more flexibly and accurately.
In some other embodiments, after the agent node collects all blocks into the historical shopping list, the agent node may package the historical shopping list into block data and send the block data to the consensus node so that the consensus node verifies the block data. Thus, it is able to record recommended behavior of the electronic device.
In a further embodiment, when it is detected that the consumer enters the mall, acquiring a facial image of the consumer, identifying the facial image of the consumer, and before acquiring the identity information of the consumer, the method includes:
the method comprises the steps that monitoring equipment is arranged at an entrance of a market in advance, and the monitoring equipment shoots face images of consumers at the entrance of a commodity.
When the method is specifically implemented, the monitoring equipment is arranged at the entrance of the market in advance, the monitoring equipment can adopt equipment such as a camera, and the monitoring equipment shoots the face image of the commodity entrance for subsequent identification information identification. The corresponding relation between the face and the identity information is also stored in the agent node in advance.
Further, the recommendation algorithm identification comprises a user-based collaborative filtering algorithm identification and an article-based collaborative filtering algorithm identification, the intelligent contract comprises a user intelligent contract and an article intelligent contract,
the acquiring of the recommendation algorithm identifier executes the corresponding type of intelligent contract according to the recommendation algorithm identifier to acquire all blocks meeting the conditions, and includes:
acquiring a recommendation algorithm identifier, and judging whether the recommendation algorithm identifier is a collaborative filtering algorithm identifier based on a user or a collaborative filtering algorithm identifier based on an article;
if the collaborative filtering algorithm is based on the user, selecting and executing a user intelligent contract to obtain all blocks containing historical purchase information corresponding to other users related to the collaborative filtering algorithm of the user;
and if the article-based collaborative filtering algorithm is adopted, selecting and executing an article intelligent contract to obtain all blocks containing historical purchase information corresponding to the user identity information.
In specific implementation, the recommendation algorithm identifier is used for identifying the algorithm type of the recommendation algorithm, wherein the recommendation algorithm identifier can be edited by a designer according to business requirements. For example, the recommendation algorithm includes a user-based collaborative filtering algorithm (UserCF algorithm), and an item-based collaborative filtering algorithm (ItemCF algorithm), the recommendation algorithm identifier corresponding to the UserCF algorithm may be U1, and the recommendation algorithm identifier corresponding to the ItemCF algorithm may be U2.
For the UserCF algorithm, the purchasing behaviors or user images among users have similarity, and can be recommended to the users according to the things purchased by the similar users, wherein the user similarity represents the similar consumption habits and consumption abilities of the users.
For the ItemCF algorithm, it is essential to recommend items to the user that are similar to the items they previously liked. Generally, the closer the static attributes of 1, two item costs, selling prices, etc., the higher their similarity; 2. the similarity between the two articles is higher when the article types are close; 3. two items that are commonly liked by many users, the higher the similarity of the two items.
For example, for the user cf algorithm, if a product is to be recommended, the required data is historical purchase information corresponding to other users associated with the product recommendation algorithm. For the ItemCF algorithm, it only needs all historical purchase information corresponding to the user identity information.
Therefore, the agent node executes the intelligent contract of the corresponding type, and the intelligent contract comprises the following processes:
firstly, the agent node responds to an access request and judges whether a recommendation algorithm identifier is a collaborative filtering algorithm identifier based on a user or a collaborative filtering algorithm identifier based on an article;
secondly, if the user-based collaborative filtering algorithm is identified, selecting and executing a user intelligent contract to obtain all blocks containing historical purchase information corresponding to other users associated with the user-based collaborative filtering algorithm;
and if the article-based collaborative filtering algorithm is identified, selecting and executing an article intelligent contract to obtain all blocks containing historical purchase information corresponding to the user identity information.
Therefore, the agent node can extract the user data corresponding to the recommendation algorithm for the electronic equipment according to the requirements of the electronic equipment.
Further, acquiring a recommendation algorithm identifier, and executing the intelligent contract of the corresponding type according to the recommendation algorithm identifier, including:
acquiring a recommendation algorithm identifier access request, wherein the recommendation algorithm identifier access request also comprises a first certificate, and the block chain stores a second certificate; judging whether the second certificate unlocks the first certificate or not;
if yes, acquiring a recommended algorithm identifier, and selecting and executing the intelligent contract of the corresponding type according to the recommended algorithm identifier;
if not, acquiring the recommended algorithm identification, and not executing any intelligent contract.
In specific implementation, the recommendation algorithm identifier access request further includes a first certificate, and the blockchain stores a second certificate. In the process that the agent node responds to the access request and selects and executes the intelligent contract of the corresponding type according to the recommended algorithm identifier, firstly, the agent node responds to the access request and judges whether the second certificate unlocks the first certificate or not; if yes, selecting and executing the intelligent contract of the corresponding type according to the recommended algorithm identification; if not, the intelligent contract of the corresponding type is not selected and executed.
In this way, it is possible to improve the security of the blockchain system.
Further, after all blocks meeting the conditions are collected into a historical shopping list, the method further comprises the following steps:
packaging the historical shopping list into block data;
and sending the block data to a consensus node in a block chain so that the consensus node verifies the block data.
In specific implementation, the ordinary node forwards the historical purchase information corresponding to the user identity information to the proxy node, the proxy node packages the historical purchase information corresponding to the user identity information into original block data and sends the original block data to the consensus node, and the consensus node verifies the original block data and packages the original block data into a block.
Further, the consensus algorithm of the consensus verification adopts a share authorization certification algorithm,
the consensus node verifies the block data, including:
when the block chain node detects that the number of times of consensus verification failure is larger than a preset threshold value, determining a malicious area chain node, wherein the malicious area chain node is a node which does not sign and verifies the block data and causes the maximum number of times of consensus verification failure;
the block link points prohibit the malicious block link points from participating in consensus verification, reallocate shares in the rest of the block link points and verify the block data in a consensus manner;
and when the block chain node detects that the number of times of failure of the consensus verification is smaller than a preset threshold value, continuing to perform the consensus verification on the block data.
In each embodiment, when the agent node sends the block data to the common node, the agent node performs signature operation on the block data by using its own private key to obtain a block signature, and a public key corresponding to the private key is broadcasted to the blockchain system. And secondly, the block signature and the block data are packaged by the agent node and are sent to the common identification node, when the common identification node verifies the signed block data, the common identification node verifies the block signature by using a legal public key of the agent node, and if the block signature is legal, the block data are considered to be sent by the legal agent node. If the block signature is illegal, the block data is considered to be sent by the illegal proxy node, so that the security of the block data can be improved by adopting the mode.
When the consensus nodes verify that the block data is sent by the legal agent node, each consensus node verifies the block data by adopting a Proof of equity (POS) algorithm or a Delegated Proof of equity (DPOS) algorithm. When the block data common identification node is verified to complete other block information, the other block information comprises a block signature, a time stamp and the like, block data is packaged, and the whole network is broadcasted.
When the common identification node verifies that the block data is sent by the illegal proxy node, the block data is discarded.
In some embodiments, the block chain-based commodity recommendation method is applied to a federation chain, and shares of the share authorization certification algorithm are distributed according to the unmanned store scale of each operator when the share authorization certification algorithm is adopted as a consensus mechanism. For example, each blockchain node of the federation chain is a server erected by each operator of an unmanned store, the size of the unmanned store including the total area of the unmanned store or the number of registered users, and the like. The unmanned stores of the operator A are the largest in scale, the percentage is 10%, the operator B is 6%, and the operator C is 3%. The.
Some common identification nodes are in failure or wrongness (do not sign and verify new blockchain data), and in order to ensure that the blockchain system can normally go out of blocks, other common identification nodes can do view updating to stop the common identification right of the failure or wrongness common identification nodes. Therefore, in some embodiments, in the process of consensus node consensus verification of block data, when the number of times of detecting consensus verification failure is greater than a preset threshold, a consensus server group composed of consensus nodes determines a malicious consensus node, where the malicious consensus node is a node that does not sign verification block data and causes the maximum number of times of consensus verification failure. The consensus server group consisting of the consensus nodes prohibits the malicious consensus nodes from participating in consensus verification, shares are redistributed to the rest consensus nodes, and data of the consensus verification block is consensus-verified, for example, the proportion of the consensus nodes A is 10% bad, so that the consensus server group stops voting right of the consensus nodes A firstly, and distributes the proportion of the consensus nodes A of 10% to the rest consensus nodes according to a preset rule secondly, for example, the consensus nodes are distributed to the rest consensus nodes uniformly, or the consensus nodes are distributed to the rest nodes according to the working ages of the consensus nodes, wherein the longer the working age is, the higher the distribution proportion is, the shorter the working age is, and the lower the distribution proportion is.
And thirdly, when the number of times of detecting that the consensus verification fails is smaller than the preset threshold value, the consensus server group continues to verify the block data.
In this way, it is ensured that the block chain system can smoothly go out of blocks.
It should be noted that, in the foregoing embodiments, a certain order does not necessarily exist among the steps, and it can be understood by those skilled in the art according to the description of the embodiments of the present invention that, in different embodiments, the steps may have different execution orders, that is, may be executed in parallel, may be executed interchangeably, and the like.
Another embodiment of the present invention provides a shopping recommendation device for market consumers based on a block chain technology, as shown in fig. 3, the device 10 includes:
one or more processors 110 and a memory 120, where one processor 110 is illustrated in fig. 3, the processor 110 and the memory 120 may be connected by a bus or other means, and the connection by the bus is illustrated in fig. 3.
Processor 110 is used to implement various control logic for apparatus 10, which may be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA), a single chip microcomputer, an ARM (Acorn RISCMache) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination of these components. Also, the processor 110 may be any conventional processor, microprocessor, or state machine. Processor 110 may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The memory 120 is a non-volatile computer-readable storage medium, and can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions corresponding to the shopping recommendation method for shopping by market consumers based on the block chain technology in the embodiment of the present invention. The processor 110 executes various functional applications and data processing of the apparatus 10 by executing the nonvolatile software programs, instructions and units stored in the memory 120, so as to implement the shopping recommendation method for market consumers based on the block chain technology in the above method embodiment.
The memory 120 may include a storage program area and a storage data area, wherein the storage program area may store an application program required for operating the device, at least one function; the storage data area may store data created according to the use of the device 10, and the like. Further, the memory 120 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 120 optionally includes memory located remotely from processor 110, which may be connected to device 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more units are stored in the memory 120, and when executed by the one or more processors 110, perform the shopping recommendation method for market consumers based on blockchain technology in any of the above-described method embodiments, for example, performing the above-described method steps S100 to S400 in fig. 2.
Embodiments of the present invention provide a non-transitory computer-readable storage medium storing computer-executable instructions for execution by one or more processors, e.g., to perform method steps S100-S400 of fig. 2 described above.
By way of example, non-volatile storage media can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in many forms such as Synchronous RAM (SRAM), dynamic RAM, (DRAM), Synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), Synchlink DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The disclosed memory components or memory of the operating environment described herein are intended to comprise one or more of these and/or any other suitable types of memory.
Another embodiment of the present invention provides a computer program product comprising a computer program stored on a non-volatile computer readable storage medium, the computer program comprising program instructions which, when executed by a processor, cause the processor to perform the method for recommending mall consumer shopping based on blockchain technology of the above method embodiment. For example, the method steps S100 to S400 in fig. 2 described above are performed.
The above-described embodiments are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a general hardware platform, and may also be implemented by hardware. With this in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer electronic device (which may be a personal computer, a server, or a network electronic device, etc.) to execute the methods of the various embodiments or some parts of the embodiments.
Conditional language such as "can," "might," or "may" is generally intended to convey that a particular embodiment can include (yet other embodiments do not include) particular features, elements, and/or operations, among others, unless specifically stated otherwise or otherwise understood within the context as used. Thus, such conditional language is not generally intended to imply that features, elements, and/or operations are in any way required for one or more embodiments or that one or more embodiments necessarily include logic for deciding, with or without student input or prompting, whether such features, elements, and/or operations are included or are to be performed in any particular embodiment.
What has been described herein in the specification and drawings includes examples of methods and apparatus capable of providing store consumer shopping recommendation based on blockchain techniques. It will, of course, not be possible to describe every conceivable combination of components and/or methodologies for purposes of describing the various features of the disclosure, but it can be appreciated that many further combinations and permutations of the disclosed features are possible. It is therefore evident that various modifications can be made to the disclosure without departing from the scope or spirit thereof. In addition, or in the alternative, other embodiments of the disclosure may be apparent from consideration of the specification and drawings and from practice of the disclosure as presented herein. It is intended that the examples set forth in this specification and the drawings be considered in all respects as illustrative and not restrictive. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.
Claims (10)
1. A shopping recommendation method for market consumers based on a block chain technology is characterized by comprising the following steps:
when detecting that a consumer enters a market, acquiring a face image of the consumer, identifying the face image of the consumer, and acquiring identity information of the consumer;
acquiring historical purchase information of the consumers according to the identity information of the consumers, and storing the historical purchase information corresponding to the identity information of each consumer in a block chain;
acquiring a recommended algorithm identifier, and executing a corresponding type of intelligent contract according to the recommended algorithm identifier to acquire all blocks meeting conditions;
and summarizing all blocks meeting the conditions into a historical shopping list, and recommending commodity information to the consumers according to the historical shopping list.
2. A shopping recommendation method for consumers in shopping malls based on block chain technology as claimed in claim 1, wherein before the steps of obtaining the face image of the consumer when the consumer is detected to enter the shopping mall, recognizing the face image of the consumer and obtaining the identity information of the consumer, the method comprises:
the method comprises the steps that monitoring equipment is arranged at an entrance of a market in advance, and the monitoring equipment shoots face images of consumers at the entrance of a commodity.
3. The method of claim 1, wherein the recommendation algorithm identifier comprises a user-based collaborative filtering algorithm identifier and an item-based collaborative filtering algorithm identifier, the intelligent contract comprises a user intelligent contract and an item intelligent contract,
the acquiring of the recommendation algorithm identifier executes the corresponding type of intelligent contract according to the recommendation algorithm identifier to acquire all blocks meeting the conditions, and includes:
acquiring a recommendation algorithm identifier, and judging whether the recommendation algorithm identifier is a collaborative filtering algorithm identifier based on a user or a collaborative filtering algorithm identifier based on an article;
if the collaborative filtering algorithm is based on the user, selecting and executing a user intelligent contract to obtain all blocks containing historical purchase information corresponding to other users related to the collaborative filtering algorithm of the user;
and if the article-based collaborative filtering algorithm is adopted, selecting and executing an article intelligent contract to obtain all blocks containing historical purchase information corresponding to the user identity information.
4. The method of claim 1, wherein after the step of summarizing all blocks satisfying the condition into a historical shopping list, the method further comprises:
packaging the historical shopping list into block data;
and sending the block data to a consensus node in a block chain so that the consensus node verifies the block data.
5. The method of claim 4, wherein the consensus algorithm for consensus verification employs a share proof of authority algorithm,
the consensus node verifies the block data, including:
when the block chain node detects that the number of times of consensus verification failure is larger than a preset threshold value, determining a malicious area chain node, wherein the malicious area chain node is a node which does not sign and verifies the block data and causes the maximum number of times of consensus verification failure;
the block link points prohibit the malicious block link points from participating in consensus verification, reallocate shares in the rest of the block link points and verify the block data in a consensus manner;
and when the block chain node detects that the number of times of failure of the consensus verification is smaller than a preset threshold value, continuing to perform the consensus verification on the block data.
6. The method of claim 1, wherein the obtaining of the recommendation algorithm identifier and the executing of the corresponding type of smart contract according to the recommendation algorithm identifier comprises:
acquiring a recommendation algorithm identifier access request, wherein the recommendation algorithm identifier access request also comprises a first certificate, and the block chain stores a second certificate; judging whether the second certificate unlocks the first certificate or not;
if yes, acquiring a recommended algorithm identifier, and selecting and executing the intelligent contract of the corresponding type according to the recommended algorithm identifier;
if not, acquiring the recommended algorithm identification, and not executing any intelligent contract.
7. A shopping recommendation method for market consumers based on block chain technology as claimed in any one of claims 1-6, wherein the goods information comprises the name of the goods, the name of the shop where the goods are located, the address of the shop where the goods are located, and the navigation diagram of the shop where the goods are located.
8. A shopping mall consumer shopping recommendation device based on a block chain technology, characterized in that the device comprises at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of shopping recommendation for store consumers based on blockchain technology of any one of claims 1 to 7.
9. A non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform the method for block-chain technology-based mall consumer shopping recommendation according to any one of claims 1-7.
10. A computer program product, characterized in that the computer program product comprises a computer program stored on a non-volatile computer-readable storage medium, the computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method for block-chain technology based mall consumer shopping recommendation according to any one of claims 1-7.
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