CN111476597A - Resource quantity estimation result processing method and related equipment - Google Patents

Resource quantity estimation result processing method and related equipment Download PDF

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CN111476597A
CN111476597A CN202010200048.2A CN202010200048A CN111476597A CN 111476597 A CN111476597 A CN 111476597A CN 202010200048 A CN202010200048 A CN 202010200048A CN 111476597 A CN111476597 A CN 111476597A
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purchased
estimation
item
purchase
information
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谭瑞
李钢
权佳成
张瑜
陈旭阳
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Shenzhen Saiante Technology Service Co Ltd
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Ping An International Smart City Technology Co Ltd
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    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
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    • G06Q20/3829—Payment protocols; Details thereof insuring higher security of transaction involving key management

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Abstract

The embodiment of the application discloses a method for processing resource quantity estimation results and related equipment, wherein the method is applied to the technical field of data processing and comprises the following steps: after the resource quantity estimation result aiming at the object to be purchased is determined, the resource quantity estimation result and the estimation reference information are digitally signed based on a private key of a user, the digitally signed resource quantity estimation result and the estimation reference information are sent to nodes in the block chain network, so that the nodes verify the digital signature, and the resource quantity estimation result and the estimation reference information are subjected to chain linking processing after the verification is passed. Further, when receiving indication information which is returned by the node and aims at the successful uplink of the resource quantity estimation result and the object data, outputting prompt information matched with the indication information. By implementing the embodiment of the application, the processing of the resource quantity estimation result can be realized based on the block chain, and the accuracy and the reliability of the resource quantity estimation result in the processing process can be improved.

Description

Resource quantity estimation result processing method and related equipment
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a method and a related device for processing a resource amount estimation result.
Background
Currently, businesses, institutions (e.g., government agencies, schools, etc.) are involved in the purchase of objects, such as goods, projects, services, etc., during their normal operation. The amount of resources (e.g., purchase price) of the object to be purchased is of great significance to the enterprise or institution. At present, a common method is to compare multiple items of objects to be purchased by experts, determine a numerical value interval (i.e., a resource amount estimation result) corresponding to the acceptable resource amount for purchasing, and inform relevant enterprises or institutions of the determined resource amount estimation result by the experts. The whole process is not public and transparent enough, and the resource amount estimation result is at risk of being tampered.
Disclosure of Invention
The embodiment of the application provides a processing method of a resource amount estimation result and related equipment, which can realize processing of the resource amount estimation result based on a block chain and is beneficial to improving the accuracy and the reliability of the resource amount estimation result in the processing process.
In a first aspect, an embodiment of the present application provides a method for processing a resource amount estimation result, where the method is applied to a terminal device, and the method includes:
when detecting an estimation request of a user for an object to be purchased, acquiring object data of the object to be purchased;
calling a classification model to analyze the object data so as to determine a purchasing type corresponding to the object to be purchased;
acquiring pre-estimated reference information matched with the purchase type;
determining a target estimation processing strategy matched with the purchase type from at least one preset estimation processing strategy;
performing resource quantity estimation on the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determining a resource quantity estimation result aiming at the object to be purchased;
carrying out digital signature on the resource quantity estimation result and the estimation reference information based on the private key of the user;
and sending the resource quantity estimation result and the estimation reference information after the digital signature to a node in a block chain network so as to verify the digital signature by the node, and performing uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed.
And when receiving indication information which is returned by the node and aims at the resource quantity estimation result and successful uplink of the object data, outputting prompt information matched with the indication information.
In an embodiment, the purchase type includes a purchase of goods, and the specific implementation manner of obtaining the pre-estimation reference information matched with the purchase type is as follows: determining goods purchasing data matched with the goods purchasing from a preset storage area; extracting identification information of the object to be purchased from the object data; inquiring the purchase resource amount of the object to be purchased in each goods purchase item and the item information of each goods purchase item from the goods purchase data based on the identification information; and determining the purchasing resource amount of the object to be purchased in each goods purchasing item and the item information of each goods purchasing item as pre-estimated reference information.
In an embodiment, the resource amount estimation is performed on the object to be purchased based on the target estimation processing policy and the estimation reference information, and a specific implementation manner of determining the resource amount estimation result is as follows: acquiring the purchasing resource quantity of the object to be purchased in each goods purchasing item from the pre-estimated reference information; deleting the maximum resource quantity and the minimum resource quantity in the purchase resource quantities; calculating the average value of each purchased resource quantity of the deleted maximum resource quantity and the deleted minimum resource quantity; and determining the calculated average value as a resource amount estimation result aiming at the object to be purchased.
In an embodiment, the purchase type includes a service purchase, and the specific implementation manner of obtaining the pre-estimation reference information matched with the purchase type is as follows: determining service purchase data matched with the service purchase from a preset storage area, and extracting the mechanism information and the item information of the object to be purchased from the object data; screening target purchasing data of the same-level mechanism of the object to be purchased from the service purchasing data based on the mechanism information, wherein the target purchasing data comprises purchasing resource quantity of each same-level mechanism in each service purchasing item and item information of each service purchasing item; determining each reference service item of the object to be purchased from each service purchasing item corresponding to each peer mechanism according to a preset matching algorithm; and determining the purchased resource amount corresponding to each reference service item and the item information of each reference service item as pre-estimated reference information.
In one embodiment, before determining service procurement data matched with the service procurement from a preset storage area and screening target procurement data of the peer mechanism of the object to be procured from the service procurement data based on the mechanism information, the service procurement data and the mechanism information of each mechanism can be collected; and storing the service purchase data of each mechanism to a preset storage area in a tree-shaped storage structure based on the mechanism information, wherein the tree-shaped storage structure represents the hierarchical relationship among the mechanisms.
In an embodiment, the specific implementation manner of determining each reference service item of the object to be purchased from each service purchase item corresponding to each peer entity according to a preset matching algorithm is as follows: calculating the item similarity of the object to be purchased and each service purchasing item corresponding to the same level mechanism according to a matching algorithm; sequencing the service purchasing items according to the sequence of the item similarity from big to small; and determining the service purchasing items of the top N in the sequence as the reference service items of the object to be purchased.
In an embodiment, the resource amount estimation is performed on the object to be purchased based on the target estimation processing policy and the estimation reference information, and a specific implementation manner of determining the resource amount estimation result is as follows: acquiring the purchased resource amount corresponding to each reference service item from the pre-estimated reference information; calculating the average value of the purchased resource amount corresponding to each reference service item; and determining the average calculation result as a resource amount estimation result aiming at the object to be purchased.
In a second aspect, an embodiment of the present application provides a device for processing resource amount estimation results, where the device for processing resource amount estimation results includes modules for executing the method of the first aspect.
In a third aspect, an embodiment of the present application provides a terminal device, where the terminal device includes a processor, an output device, and a memory, where the processor, the output device, and the memory are connected to each other, where the memory is used to store a computer program that supports the terminal device to execute the method described above, and the computer program includes program instructions, and the processor is configured to call the program instructions to execute the method described above in the first aspect.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium storing a computer program, the computer program comprising program instructions that, when executed by a processor, cause the processor to perform the method of the first aspect.
In the embodiment of the application, the terminal device can acquire object data of an object to be purchased, call the classification model to analyze the object data, determine a purchase type corresponding to the object to be purchased, acquire estimation reference information matched with the purchase type, determine a target estimation processing strategy matched with the purchase type from at least one preset estimation processing strategy, estimate the resource quantity of the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determine a resource quantity estimation result for the object to be purchased. Further, the resource quantity estimation result and the estimation reference information can be digitally signed based on a private key of a user, and the resource quantity estimation result and the estimation reference information after being digitally signed are sent to a node in the block chain network, so that the node verifies the digital signature, and performs uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed. Further, when receiving indication information which is returned by the node and aims at the successful uplink of the resource quantity estimation result and the object data, outputting prompt information matched with the indication information. The processing of the resource quantity estimation result can be realized based on the block chain, and the accuracy and the reliability of the resource quantity estimation result in the processing process are improved.
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In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without creative efforts.
Fig. 1a is a schematic structural diagram of a block chain according to an embodiment of the present disclosure;
fig. 1b is a schematic diagram illustrating an architecture of a resource amount estimation result processing system according to an embodiment of the present application;
fig. 2 is a schematic flowchart of a method for processing a resource amount estimation result according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram illustrating a resource amount estimation result according to an embodiment of the present disclosure;
FIG. 4 is a schematic flow chart illustrating another method for processing resource amount estimation results according to an embodiment of the present disclosure;
FIG. 5 is a schematic diagram of a tree structure provided by an embodiment of the present application;
fig. 6 is a schematic flowchart of another method for processing resource amount estimation results according to an embodiment of the present application;
FIG. 7 is a schematic block diagram of a device for processing resource amount estimation results according to an embodiment of the present disclosure;
fig. 8 is a schematic block diagram of a terminal device according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Currently, enterprises, institutions (e.g., government agencies, schools, etc.) are involved in purchasing objects during their normal operations. Taking government procurement as an example, the government procurement means the behavior of purchasing goods, engineering and labor services for government departments or affiliated groups from domestic and foreign markets in a manner that the government departments directly pay for suppliers in a manner of public bidding, fair competition and legal manner, methods and procedures under the supervision of finance in order to develop daily government activities or provide services for the public. The essence of the method is the organic combination of a market competition mechanism and financial expense management, and the method is mainly characterized in that government purchasing behaviors are legalized and regulated.
Government procurement is one of the main measures of government expenditure, and the proportion of the government procurement expenditure accounting for the total national financial expenditure and the GDP in 2017 is calculated to be 12.2 percent and 3.9 percent respectively. How to efficiently and practically purchase budgets, and assessing the reasonability of purchasing are important problems facing government purchasing. In government purchasing, the purchasing resource amount of an object to be purchased is mainly determined by comparing multiple purchasing items through experts or purchasing personnel, and an acceptable numerical value interval is further determined.
In order to solve the above problems, the present application provides a method for processing a resource amount estimation result, which may obtain object data of an object to be purchased, call a classification model to analyze the object data, determine a purchase type corresponding to the object to be purchased, obtain estimation reference information matched with the purchase type, determine a target estimation processing policy matched with the purchase type from at least one preset estimation processing policy, perform resource amount estimation on the object to be purchased based on the target estimation processing policy and the estimation reference information, and determine and output the resource amount estimation result. The resource quantity of the object to be purchased can be efficiently estimated based on the type of the object to be purchased, in addition, different estimation processing strategies can be adopted for estimating the resource quantity of the object to be purchased aiming at different purchasing types, and the accuracy of estimating the resource quantity is favorably improved.
Further, after the resource quantity estimation result for the object to be purchased is determined, the resource quantity estimation result and the estimation reference information can be digitally signed based on a private key of the user, and the resource quantity estimation result and the estimation reference information after digital signature are sent to a node in the block chain network, so that the node verifies the digital signature, and performs uplink processing on the resource quantity estimation result and the estimation reference information after verification is passed. Further, when receiving indication information which is returned by the node and aims at the successful uplink of the resource quantity estimation result and the object data, outputting prompt information matched with the indication information.
The Block Chain (Block Chain) is a Chain data structure which combines data blocks in a sequential connection mode according to a time sequence and is a distributed book which is cryptographically used for ensuring that the data cannot be tampered and forged. Multiple independent distributed nodes (i.e., block-linked node devices) maintain the same record. The blockchain technology realizes decentralization and becomes a foundation for credible digital asset storage, transfer and transaction.
Taking the block chain structure diagram shown in fig. 1a as an example, when new data needs to be written into the block chain, the data is collected into a block (block) and added to the end of the existing block chain, and the newly added block of each node is ensured to be identical through a consensus algorithm. A plurality of transaction records are recorded in each block, and the transaction records also comprise the hash (hash) value of the previous block, and all blocks store the hash value of the previous block in the way and are connected in sequence to form a block chain. The hash value of the previous block is stored in the block head of the next block in the block chain, and when the transaction data in the current block changes, the hash value of the block is changed, so that the transaction data uploaded to the block chain network is difficult to tamper, the transaction is carried out on the block chain, the transaction process is transparent, and the reliability of the transaction data is improved.
In order to better understand the method for processing the resource amount estimation result disclosed in the embodiment of the present invention, a block chain system applicable to the embodiment of the present invention is first described below.
Referring to fig. 1b, fig. 1b is a schematic diagram illustrating an architecture of a resource amount estimation result processing system according to an embodiment of the present invention. As shown in fig. 1b, the system for processing the resource amount estimation result includes at least one terminal device 101, a first node 102, and at least one second node 103. It should be noted that the blockchain network shown in fig. 1b is composed of one first node 102 and two second nodes 103, which are only used for illustration and do not constitute a limitation to the embodiment of the present invention. For example, in another example, a blockchain network may consist of one first node 102 and four second nodes 103. The first node 102 is configured to perform data interaction with the terminal device 101, and may be configured to receive a resource amount estimation result and estimation reference information uploaded by the terminal device 101 after a digital signature, for example.
In one implementation, the first node 102 may be any one of the blockchain node devices in the blockchain network, the first node 102 may also be the blockchain node device closest to the terminal device 101, and the first node 102 may also be the blockchain node device with the best communication quality with the terminal device 101, which is not limited herein.
In one implementation, the first nodes 102 are selected from all first block-link node devices in the blockchain network according to a consensus algorithm, wherein the consensus algorithm includes, but is not limited to, a Proof of workload (PoW) algorithm, a Proof of rights (PoS) algorithm, a granted Proof of rights (DPoS) algorithm, a Practical Byzantine Fault Tolerance (PBFT) algorithm, and the like. The first node 102 may also be obtained by periodic election through a consensus algorithm, and the first nodes 102 obtained by periodic election in different periods may be the same or different.
Wherein the second node 103 may be a blockchain link point device in a blockchain network other than the first node 102. The second node 103 may be a consensus node for performing consensus verification on the resource amount estimation result and the estimation reference information of the uplink.
It is to be understood that the data processing system described in the embodiment of the present invention is for more clearly illustrating the technical solution of the embodiment of the present invention, and does not constitute a limitation to the technical solution provided in the embodiment of the present invention, and as a person having ordinary skill in the art knows that along with the evolution of the system architecture and the appearance of a new service scenario, the technical solution provided in the embodiment of the present invention is also applicable to similar technical problems.
Referring to fig. 2, fig. 2 is a schematic flowchart of a method for processing a resource amount estimation result provided in an embodiment of the present application, where the method is applied to a terminal device and can be executed by the terminal device, and as shown in the figure, the method for processing the resource amount estimation result may include:
s201: when an estimation request of a user for an object to be purchased is detected, object data of the object to be purchased is obtained, and a classification model is called to analyze the object data so as to determine a purchase type corresponding to the object to be purchased. The purchase object may be a goods, an engineering project or a service purchase project. In one embodiment, a user may submit a pre-estimation request for an object to be purchased through a terminal device, where the pre-estimation request carries object data of the object to be purchased, and the terminal device may obtain the object data of the object to be purchased from the pre-estimation request.
In one embodiment, a large number of purchase sample data of different purchase types can be acquired, and classification tags of the purchase types of the purchase sample data are added to the purchase sample data. Further, the terminal device may train the initial classification model based on the purchase sample data and the corresponding classification label to obtain a classification model. Wherein the initial classification model may be a neural network model.
Furthermore, after the training of the classification model is completed, the classification model can be called to analyze the object data of the object to be purchased, and the purchasing type corresponding to the object to be purchased is determined. The purchase type may include a no-good purchase, a service (e.g., training program, insurance program, monitoring program, etc.) purchase, or an engineering purchase.
S202: and acquiring pre-estimated reference information matched with the purchase type.
The estimation reference information is some reference information required for estimating the resource quantity of the object to be purchased. For the objects to be purchased of different purchase types, the corresponding pre-estimated reference information is also different. For example, assuming that the purchase type of the object to be purchased is goods purchase, that is, the object to be purchased is a kind of goods, in this case, the pre-estimated reference information may be the amount of resources purchased by the goods in other goods purchase items and item information of the goods purchase items.
For another example, assuming that the purchasing type of the object to be purchased is engineering purchasing, that is, the object to be purchased is a kind of engineering, in this case, the estimated reference information may be the purchasing resource amount of a reference engineering project similar to the engineering and the project information of the reference engineering project. The purchase resource amount may be, for example, a purchase price of the object to be purchased in another item to be purchased.
S203: and determining a target estimation processing strategy matched with the purchase type from at least one preset estimation processing strategy.
S204: and performing resource quantity estimation on the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determining a resource quantity estimation result aiming at the object to be purchased.
In an embodiment, a corresponding relationship between the estimation processing strategy and the purchase type may be pre-established, after the terminal device determines the purchase type of the object to be purchased, a target estimation processing strategy corresponding to the purchase type of the object to be purchased may be determined from at least one preset estimation processing strategy based on the corresponding relationship, and then the resource amount estimation result is determined and output by estimating the resource amount of the object to be purchased based on the target estimation processing strategy and the estimation reference information. The resource amount estimation result may be a value (e.g., price) corresponding to the estimated resource amount. By adopting the method, the resource quantity of the object to be purchased can be efficiently estimated based on the type of the object to be purchased, in addition, different estimation processing strategies can be adopted for estimating the resource quantity of the object to be purchased aiming at different purchasing types, and the accuracy of estimating the resource quantity is favorably improved.
In one embodiment, after the terminal device determines the resource amount estimation result, the resource amount estimation result and the estimation reference information may be output in a preset display form. The preset display form may be, for example, a display form of a chart. By adopting the method, not only the resource quantity estimation result can be output, but also the estimation reference information participating in the resource quantity estimation can be output, and the information support of the resource quantity estimation result is favorably provided.
Illustratively, the purchase resource amount is a purchase price, the resource amount estimation result is an estimated price, assuming that the purchase type of the object to be purchased is a goods type, the estimated reference information matched with the purchase type of the object to be purchased includes the purchase price of the object to be purchased in 5 goods purchase items, item information (e.g., item names) of the respective goods purchase items, and the item names of the above 5 goods purchase items and the purchase price of the object to be purchased in the 5 goods purchase items are shown in table 1. In this case, the terminal device may output the estimated price and the item names of the 5 goods procurement items through a preset presentation form, as shown in fig. 3.
TABLE 1
Goods procurement project Purchase price (Wan)
Goods procurement item 1 5
Goods procurement item 2 12
Goods procurement item 3 16
Goods procurement item 4 9
Goods procurement item 5 4
S205: and digitally signing the resource quantity estimation result and the estimation reference information based on a private key of the user, sending the resource quantity estimation result and the estimation reference information subjected to digital signature to a node in the block chain network so as to enable the node to verify the digital signature, and performing uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed.
In one embodiment, after receiving the resource amount estimation result and the estimation reference information after the digital signature, the node in the blockchain network may verify the digital signature according to the public key of the user, and if the verification passes, the node device may send the resource amount estimation result and the estimation reference information to a consensus node in the blockchain network, where the consensus node performs consensus verification on the resource amount estimation result and the estimation reference information, generates a new data block based on the resource amount estimation result and the estimation reference information after the consensus verification passes, and issues the new data block to a block chain maintained by the blockchain network, thereby implementing uplink processing on the resource amount estimation result and the estimation reference information. Wherein, the consensus verification comprises rationality verification and authenticity verification.
Further, after successfully linking the resource amount estimation result and the estimated reference information, the node may return indication information for indicating the resource amount estimation result and successful linking of the estimated reference information to the terminal equipment.
Or, if the uplink of the resource quantity estimation result and the estimated reference information is unsuccessful, the node may also return alarm information to the terminal equipment, so as to prompt the reason why the uplink of the resource quantity estimation result and the estimated reference information of the terminal equipment is unsuccessful. The reason may be, for example, that the digital signature verification is unsuccessful, or that the resource amount estimation result and/or the estimated reference information is not reasonable.
S206: and when receiving indication information which is returned by the node and aims at the resource quantity estimation result and successful uplink of the estimation reference information, outputting prompt information matched with the indication information. The prompt message is used for prompting the user that the uplink is successful according to the resource quantity estimation result and the estimation reference message of the object to be purchased.
In one embodiment, after successful chaining of the resource amount estimation result and the estimation reference information of the object to be purchased, the user can query or acquire the resource amount estimation result and the estimation reference information of the object to be purchased through the block chain according to the own needs. The block chain has the characteristics of decentralized multi-node backup data and tamper-proof traceability, so that the accuracy and the reliability of the resource amount estimation result in the processing process are improved.
In the embodiment of the application, the terminal device can acquire object data of an object to be purchased, call the classification model to analyze the object data, determine a purchase type corresponding to the object to be purchased, acquire estimation reference information matched with the purchase type, determine a target estimation processing strategy matched with the purchase type from at least one preset estimation processing strategy, estimate the resource quantity of the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determine a resource quantity estimation result for the object to be purchased. Further, the resource quantity estimation result and the estimation reference information can be digitally signed based on a private key of a user, and the resource quantity estimation result and the estimation reference information after being digitally signed are sent to a node in the block chain network, so that the node verifies the digital signature, and performs uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed. Further, when receiving indication information which is returned by the node and aims at the successful uplink of the resource quantity estimation result and the object data, outputting prompt information matched with the indication information. The processing of the resource quantity estimation result can be realized based on the block chain, and the accuracy and the reliability of the resource quantity estimation result in the processing process are improved.
Referring to fig. 4, fig. 4 is a schematic diagram of another method for processing resource amount estimation results provided in this embodiment of the present application, where the method is applied to a terminal device and can be executed by the terminal device, and as shown in the figure, the method for processing resource amount estimation results can include:
s401: when an estimation request of a user for an object to be purchased is detected, object data of the object to be purchased is obtained, and a classification model is called to analyze the object data so as to determine a purchase type corresponding to the object to be purchased. For a specific implementation of step S401, reference may be made to the related description of step S201 in the foregoing embodiment, and details are not described here again.
S402: and if the purchase type corresponding to the object to be purchased is service purchase, determining service purchase data matched with the service purchase from a preset storage area, and extracting the mechanism information and the item information of the object to be purchased from the object data. The organization information may be an organization identifier (e.g., organization name), an administrative level, and the like, and the to-be-purchased item information may be an item name, an item period, an item level, an item index, an item profile, and the like of the to-be-purchased item.
In one embodiment, the terminal device may collect purchase sample data corresponding to various purchase types in advance, add a type tag to the purchase sample data of different purchase types, and further store each purchase sample data and the corresponding type tag in a preset storage area in an associated manner. Further, after determining that the purchase type corresponding to the object to be purchased is service purchase, the terminal device may acquire target purchase sample data (i.e., service purchase data) stored in association with the type tag representing service purchase from the preset storage area.
S403: and screening target purchasing data of the peer mechanism of the object to be purchased from the service purchasing data based on the mechanism information, wherein the target purchasing data comprises the purchasing resource amount of each peer mechanism in each service purchasing item and the item information of each service purchasing item. The item information of each service purchase item comprises an item name, an item period, an item level, an item index, an item profile and the like of the service purchase item.
In one embodiment, the terminal device may collect service procurement data and organization information of each organization in advance, and store the service procurement data of each organization to a preset storage area in a tree-shaped storage structure based on the organization information, wherein the tree-shaped storage structure represents a hierarchical relationship between each organization.
The above structure may refer to each level of departments in an enterprise, such as a market department, a hardware development department, a software development department, a human resource department, and the like in the enterprise a, or may refer to each level of government departments, and the like. It is understood that whether it is an enterprise or a government department, there is a certain hierarchical relationship, for example, department 00A is subordinate to department 0A and is subordinate to department 00A; for example, the financial hall in Shenzhen city is subordinate to the Guangdong province financial hall and is a subordinate mechanism of the Guangdong province financial hall.
The tree-shaped storage structure comprises a plurality of storage nodes, each storage node corresponds to one mechanism, and each storage node is used for storing service purchase data of the corresponding mechanism. Illustratively, the tree structure may be, for example, as shown in fig. 5, and it can be seen from fig. 5 that the Chongqing City financial bureau and the Guangdong province financial hall belong to the same hierarchy in the tree storage structure, and both belong to the same level organization. In this case, if the type corresponding to the object to be purchased is the service type and the agency name of the object to be purchased is the Chongqing City financial bureau, the terminal device may screen the target purchase data of the peer agency "Guangdong province financial hall" of the object to be purchased from the service purchase data.
S404: and determining each reference service item of the object to be purchased from each service purchasing item corresponding to each same-level mechanism according to a preset matching algorithm.
In an embodiment, the terminal device may calculate, according to a preset matching algorithm, item similarities of the object to be purchased and service purchasing items (hereinafter referred to as peer service purchasing items) corresponding to the same-level organization, sort the service purchasing items according to a descending order of the item similarities, and determine a service purchasing item N before the sorting as each reference service item of the object to be purchased, where N is an integer greater than 0.
In an embodiment, the terminal device may compare the similarity between the item information to be purchased of the object to be purchased and the item information of each statistical service purchase item, to obtain the item similarity between the object to be purchased and each peer service purchase item.
S405: and determining the purchased resource amount corresponding to each reference service item and the item information of each reference service item as pre-estimated reference information.
For example, assuming that the reference service items include service procurement item 1 and service procurement item 2, the terminal device may determine the procurement resource amount and item information corresponding to each of service procurement item 1 and service procurement item 2 as the pre-estimated reference information of the object to be procured.
S406: and determining a target estimation processing strategy matched with the purchase type from at least one preset estimation processing strategy, estimating the resource quantity of the object to be purchased based on the target estimation processing strategy and estimation reference information, and determining a resource quantity estimation result aiming at the object to be purchased.
In one embodiment, if the purchase type corresponding to the object to be purchased is service purchase, performing resource amount prediction on the object to be purchased based on the target prediction processing strategy and the prediction reference information, and determining a resource amount prediction result includes: and calculating the average value of the purchased resource amount corresponding to each reference service item from the purchased resource amount corresponding to each reference service item in the pre-estimated reference information, and determining the average value calculation result as the resource amount pre-estimation result aiming at the object to be purchased.
In one embodiment, if the purchasing type corresponding to the object to be purchased is engineering purchasing, the resource amount of the object to be purchased can be estimated by using a method similar to service purchasing. Specifically, engineering procurement data matched with the engineering procurement can be determined from a preset storage area, organization information and project information to be procured of the object to be procured are extracted from the object data, and target procurement data of the same-level organization of the object to be procured are screened from the engineering procurement data based on the organization information, wherein the target procurement data comprise procurement resource amount of each same-level organization in each engineering procurement project and project information of each engineering procurement project. Further, the terminal device can determine each reference engineering project of the object to be purchased from each engineering purchasing project corresponding to each same-level organization according to a preset matching algorithm, and further determine the purchasing resource amount corresponding to each reference engineering project and the project information of each reference engineering project as the pre-estimated reference information.
S407: and digitally signing the resource quantity estimation result and the estimation reference information based on a private key of the user, sending the resource quantity estimation result and the estimation reference information subjected to digital signature to a node in the block chain network so as to enable the node to verify the digital signature, and performing uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed.
S408: and when receiving indication information which is returned by the node and aims at the resource quantity estimation result and successful uplink of the estimation reference information, outputting prompt information matched with the indication information.
For specific implementation of steps S407 to S408, refer to the related description of steps S205 to S206 in the above embodiment, and are not described herein again.
In the embodiment of the application, the terminal device can acquire object data of an object to be purchased, call the classification model to analyze the object data, determine a purchase type corresponding to the object to be purchased, determine service purchase data matched with the service purchase from a preset storage area if the purchase type corresponding to the object to be purchased is service purchase, extract mechanism information and item information of the object to be purchased from the object data, and screen target purchase data of a peer mechanism of the object to be purchased from the service purchase data based on the mechanism information. Further, determining each reference service item of the object to be purchased from each service purchase item corresponding to each same-level mechanism according to a preset matching algorithm, determining the purchase resource amount corresponding to each reference service item and the item information of each reference service item as pre-estimation reference information, further determining a target pre-estimation processing strategy matched with the purchase type from at least one pre-estimation processing strategy, performing resource amount pre-estimation on the object to be purchased based on the target pre-estimation processing strategy and the pre-estimation reference information, and determining a resource amount pre-estimation result for the object to be purchased. The resource quantity estimation of the object to be purchased of the service purchase type can be efficiently realized.
Referring to fig. 6, fig. 6 is a schematic diagram of another method for processing resource amount estimation results provided in this embodiment of the present application, where the method is applied to a terminal device and can be executed by the terminal device, and as shown in the figure, the method for processing resource amount estimation results can include:
s601: when an estimation request of a user for an object to be purchased is detected, object data of the object to be purchased is obtained, and a classification model is called to analyze the object data so as to determine a purchase type corresponding to the object to be purchased. For a specific implementation of step S601, reference may be made to the related description of step S201 in the foregoing embodiment, and details are not described here again.
S602: and if the purchase type corresponding to the object to be purchased is the goods purchase, acquiring goods purchase data matched with the goods purchase from the preset storage area.
In one embodiment, the terminal device may collect purchase sample data corresponding to various purchase types in advance, add a type tag to the purchase sample data of different purchase types, and further store each purchase sample data and the corresponding type tag in a preset storage area in an associated manner. Further, after the terminal device determines that the purchase type corresponding to the object to be purchased is the goods purchase, target goods purchase sample data (i.e. goods purchase data) stored in association with the type tag representing the goods purchase can be acquired from the preset storage area.
S603: and extracting the identification information of the object to be purchased from the object data, and inquiring the purchasing resource amount of the object to be purchased in each goods purchasing item and the item information of each goods purchasing item from the goods purchasing data based on the identification information. The identification information of the object to be purchased may refer to information for uniquely identifying the object to be purchased, such as a goods number, a goods name, and the like. The item information of the goods procurement item can be an item name, an item period, an item level, an item index, an item profile and the like of the goods procurement item.
S604: and determining the purchase resource amount of the object to be purchased in each goods purchase item and the item information of each goods purchase item as the pre-estimated reference information.
For example, assuming that the goods procurement items include a goods procurement item 1 and a goods procurement item 2, the terminal device may determine the procurement resource amount and the item information of the goods procurement item corresponding to each of the goods procurement item 1 and the goods procurement item 2 as the pre-estimation reference information of the object to be procured.
S605: and determining a target estimation processing strategy matched with the purchase type from at least one preset estimation processing strategy, estimating the resource quantity of the object to be purchased based on the target estimation processing strategy and estimation reference information, and determining a resource quantity estimation result aiming at the object to be purchased.
In one embodiment, if the purchase type corresponding to the object to be purchased is goods purchase, performing resource quantity estimation on the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determining a resource quantity estimation result includes: acquiring the purchase resource amount of the object to be purchased in each goods purchase item from the pre-estimation reference information, deleting the maximum resource amount and the minimum resource amount in each purchase resource amount, carrying out average value calculation on each purchase resource amount after deleting the maximum resource amount and the minimum resource amount, and determining the average value obtained by calculation as a resource amount pre-estimation result aiming at the object to be purchased. The purchase resource amount may be a purchase price, the maximum resource amount may be a maximum price, and the minimum resource amount may be a minimum price.
Exemplarily, assuming that the purchased resource amount is a purchase price, the maximum resource amount is a maximum price, the minimum resource amount is a minimum price, the number of goods purchased items corresponding to the object to be purchased is 5, and the respective purchased resource amounts are shown in table 1, the terminal device may remove the maximum price "16 ten thousand" and the minimum price "4 ten thousand" based on the target estimation processing policy, perform average calculation on the remaining "5 ten thousand", "12 ten thousand" and "9 ten thousand" to obtain an average value of 8.6 ten thousand, and may determine 8.6 ten thousand as the resource amount estimation result for the object to be purchased.
S606: and digitally signing the resource quantity estimation result and the estimation reference information based on a private key of the user, sending the resource quantity estimation result and the estimation reference information subjected to digital signature to a node in the block chain network so as to enable the node to verify the digital signature, and performing uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed.
S607: and when receiving indication information which is returned by the node and aims at the resource quantity estimation result and successful uplink of the estimation reference information, outputting prompt information matched with the indication information.
For specific implementation of steps S606 to S607, reference may be made to the related description of steps S205 to S206 in the foregoing embodiment, and details are not repeated here.
In the embodiment of the application, the resource quantity estimation of the object to be purchased of the goods purchase type can be efficiently realized.
The embodiment of the application also provides a device for processing the resource amount estimation result. The apparatus includes means configured to execute the method described in fig. 2, fig. 4, or fig. 6, and is configured to be executed by a terminal device. Specifically, referring to fig. 7, a schematic block diagram of a processing apparatus for resource amount estimation results provided in the embodiment of the present application is shown. The device for processing the resource amount estimation result of the embodiment comprises:
the acquisition module 70 is configured to acquire object data of an object to be purchased when an estimation request of a user for the object to be purchased is detected;
the processing module 71 is configured to invoke a classification model to analyze the object data to determine a purchasing type corresponding to the object to be purchased;
the obtaining module 70 is further configured to obtain pre-estimated reference information matched with the purchase type;
the processing module 71 is further configured to determine a target pre-estimation processing strategy matched with the purchase type from at least one pre-estimation processing strategy, perform resource amount pre-estimation on the object to be purchased based on the target pre-estimation processing strategy and the pre-estimation reference information, and determine a resource amount pre-estimation result for the object to be purchased;
the processing module 71 is further configured to digitally sign the resource amount estimation result and the estimation reference information based on a private key of the user;
the communication module 72 is configured to send the resource amount estimation result and the estimation reference information after the digital signature to a node in a block chain network, so that the node verifies the digital signature, and performs uplink processing on the resource amount estimation result and the estimation reference information after the verification is passed;
the communication module 72 is further configured to receive indication information of successful uplink for the resource amount estimation result and the estimation reference information, which is returned by the node;
the output module 73 is further configured to, when it is detected that the communication module 72 receives the indication information, output prompt information matching the indication information.
In an embodiment, the purchase type includes service purchase, the obtaining of pre-estimated reference information matching the purchase type is performed, and the obtaining module 70 is specifically configured to determine service purchase data matching the service purchase from a preset storage area, and extract organization information and item information of the object to be purchased from the object data; screening target purchasing data of the same-level mechanism of the object to be purchased from the service purchasing data based on the mechanism information, wherein the target purchasing data comprises purchasing resource quantity of each same-level mechanism in each service purchasing item and item information of each service purchasing item; determining each reference service item of the object to be purchased from each service purchasing item corresponding to each peer mechanism according to a preset matching algorithm; and determining the purchased resource amount corresponding to each reference service item and the item information of each reference service item as pre-estimated reference information.
In one embodiment, the processing module 71 is further configured to collect service procurement data and institution information of each institution; and storing the service purchase data of each mechanism to a preset storage area in a tree-shaped storage structure based on the mechanism information, wherein the tree-shaped storage structure represents the hierarchical relationship among the mechanisms.
In an embodiment, the obtaining module 70 is further specifically configured to calculate, according to a preset matching algorithm, item similarities between the object to be purchased and each service purchase item corresponding to the peer mechanism; sequencing the service purchasing items according to the sequence of the item similarity from big to small; and determining the service purchasing items of the top N in the sequence as the reference service items of the object to be purchased, wherein N is an integer greater than 0.
In an embodiment, the processing module 71 is specifically configured to obtain the purchased resource amount corresponding to each reference service item from the pre-estimated reference information; calculating the average value of the purchased resource amount corresponding to each reference service item; and determining the average calculation result as a resource amount estimation result aiming at the object to be purchased.
In an embodiment, the purchase type includes a goods purchase, and the obtaining module 70 is specifically configured to obtain, from a preset storage area, goods purchase data matching the goods purchase; extracting identification information of the object to be purchased from the object data; inquiring the purchase resource amount of the object to be purchased in each goods purchase item and the item information of each goods purchase item from the goods purchase data based on the identification information; and determining the purchasing resource amount of the object to be purchased in each goods purchasing item and the item information of each goods purchasing item as pre-estimated reference information.
In an embodiment, the processing module 71 is specifically configured to obtain, from the pre-estimated reference information, a purchase resource amount of the object to be purchased in each item of goods purchased; deleting the maximum resource quantity and the minimum resource quantity in the purchase resource quantities; calculating the average value of each purchased resource amount after deleting the maximum resource amount and the minimum resource amount; and determining the calculated average value as a resource amount estimation result aiming at the object to be purchased.
It should be noted that the functions of each functional module of the processing apparatus for the resource amount estimation result described in the embodiment of the present application may be specifically implemented according to the method in the method embodiment described in fig. 2, fig. 4, or fig. 6, and the specific implementation process may refer to the description related to the method embodiment in fig. 2, fig. 4, or fig. 6, which is not described herein again.
Referring to fig. 8, fig. 8 is a schematic block diagram of a terminal device according to an embodiment of the present application, and as shown in fig. 8, the terminal device includes a processor 801, a memory 802, an output device 803, and a communication interface 804. The processor 801, the memory 802, the output device 803 and the communication interface 804 may be connected by a bus or other means, and fig. 8 shows an example of the connection by the bus in the embodiment of the present application. Wherein the memory 802 is configured to store a computer program comprising program instructions and the processor 801 is configured to execute the program instructions stored by the memory 802. Wherein the processor 801 is configured to invoke the program instructions to perform: when detecting an estimation request of a user for an object to be purchased, acquiring object data of the object to be purchased; calling a classification model to analyze the object data so as to determine a purchasing type corresponding to the object to be purchased; acquiring pre-estimated reference information matched with the purchase type; determining a target estimation processing strategy matched with the purchase type from at least one preset estimation processing strategy; performing resource quantity estimation on the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determining a resource quantity estimation result; carrying out digital signature on the resource quantity estimation result and the estimation reference information based on the private key of the user; sending the resource quantity estimation result and the estimation reference information after the digital signature to a node in a block chain network through a communication interface communication module 804, so that the node verifies the digital signature and performs uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed; when receiving indication information, which is returned by the node and is directed to the resource amount estimation result and the uplink success of the estimation reference information, through the communication interface 804, outputting prompt information matched with the indication information through the output device 803.
In an embodiment, the purchase type includes service purchase, the obtaining of pre-estimated reference information matching with the purchase type is performed, and the processor 801 is specifically configured to determine service purchase data matching with the service purchase from a preset storage area, and extract organization information and item information of the object to be purchased from the object data; screening target purchasing data of the same-level mechanism of the object to be purchased from the service purchasing data based on the mechanism information, wherein the target purchasing data comprises purchasing resource quantity of each same-level mechanism in each service purchasing item and item information of each service purchasing item; determining each reference service item of the object to be purchased from each service purchasing item corresponding to each peer mechanism according to a preset matching algorithm; and determining the purchased resource amount corresponding to each reference service item and the item information of each reference service item as pre-estimated reference information.
In one embodiment, the processor 801 is further configured to collect service procurement data and organization information of each organization; and storing the service purchase data of each mechanism to a preset storage area in a tree-shaped storage structure based on the mechanism information, wherein the tree-shaped storage structure represents the hierarchical relationship among the mechanisms.
In an embodiment, the processor 801 is further specifically configured to calculate, according to a preset matching algorithm, item similarities between the object to be purchased and each service purchasing item corresponding to the peer mechanism; sequencing the service purchasing items according to the sequence of the item similarity from big to small; and determining the service purchasing items of the top N in the sequence as the reference service items of the object to be purchased, wherein N is an integer greater than 0.
In an embodiment, the processor 801 is further specifically configured to obtain the purchased resource amount corresponding to each reference service item from the pre-estimated reference information; calculating the average value of the purchased resource amount corresponding to each reference service item; and determining the average calculation result as a resource amount estimation result aiming at the object to be purchased.
In an embodiment, the purchase type includes a goods purchase, and the processor 801 is specifically configured to obtain goods purchase data matching the goods purchase from a preset storage area; extracting identification information of the object to be purchased from the object data; inquiring the purchase resource amount of the object to be purchased in each goods purchase item and the item information of each goods purchase item from the goods purchase data based on the identification information; and determining the purchasing resource amount of the object to be purchased in each goods purchasing item and the item information of each goods purchasing item as pre-estimated reference information.
In an embodiment, the processor 801 is further specifically configured to obtain, from the pre-estimation reference information, a purchase resource amount of the object to be purchased in each item of goods purchased; deleting the maximum resource quantity and the minimum resource quantity in the purchase resource quantities; calculating the average value of each purchased resource amount after deleting the maximum resource amount and the minimum resource amount; and determining the calculated average value as a resource amount estimation result aiming at the object to be purchased.
It should be understood that, in the embodiment of the present Application, the Processor 801 may be a Central Processing Unit (CPU), and the Processor 801 may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The output devices 803 may include a display (L CD, etc.), speakers, etc.
The memory 802 may include both read-only memory and random access memory, and provides instructions and data to the processor 801. A portion of the memory 802 may also include non-volatile random access memory. For example, the memory 802 may also store device type information.
In specific implementation, the processor 801, the memory 802, the output device 803, and the communication interface 804 described in this embodiment of the present application may execute the implementation described in the method embodiment described in fig. 2, fig. 4, or fig. 6 provided in this embodiment of the present application, and may also execute the implementation of the processing apparatus for the resource amount estimation result described in this embodiment of the present application, which is not described herein again.
In another embodiment of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing a computer program comprising program instructions that when executed by a processor implement: when detecting an estimation request of a user for an object to be purchased, acquiring object data of the object to be purchased; calling a classification model to analyze the object data so as to determine a purchasing type corresponding to the object to be purchased; acquiring pre-estimated reference information matched with the purchase type; determining a target estimation processing strategy matched with the purchase type from at least one preset estimation processing strategy; performing resource quantity estimation on the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determining a resource quantity estimation result aiming at the object to be purchased; carrying out digital signature on the resource quantity estimation result and the estimation reference information based on the private key of the user; sending the resource quantity estimation result and the estimation reference information after the digital signature to a node in a block chain network so as to enable the node to verify the digital signature, and performing uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed; and when receiving indication information which is returned by the node and aims at the resource quantity estimation result and successful uplink of the estimation reference information, outputting prompt information matched with the indication information.
The computer-readable storage medium may be an internal storage unit of the terminal device according to any of the foregoing embodiments, for example, a hard disk or a memory of the terminal device. The computer readable storage medium may also be an external storage device of the terminal device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), and the like provided on the terminal device. Further, the computer-readable storage medium may also include both an internal storage unit and an external storage device of the terminal device. The computer-readable storage medium is used for storing the computer program and other programs and data required by the terminal device. The computer readable storage medium may also be used to temporarily store data that has been output or is to be output.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by a computer program, which can be stored in a computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. The storage medium may be a magnetic disk, an optical disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), or the like.
While the invention has been described with reference to a number of embodiments, it will be understood by those skilled in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (10)

1. A method for processing resource amount estimation results is characterized by comprising the following steps:
when detecting an estimation request of a user for an object to be purchased, acquiring object data of the object to be purchased;
calling a classification model to analyze the object data so as to determine a purchasing type corresponding to the object to be purchased;
acquiring pre-estimated reference information matched with the purchase type;
determining a target estimation processing strategy matched with the purchase type from at least one preset estimation processing strategy;
performing resource quantity estimation on the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determining a resource quantity estimation result aiming at the object to be purchased;
carrying out digital signature on the resource quantity estimation result and the estimation reference information based on the private key of the user;
sending the resource quantity estimation result and the estimation reference information after the digital signature to a node in a block chain network so as to enable the node to verify the digital signature, and performing uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed;
and when receiving indication information which is returned by the node and aims at the resource quantity estimation result and successful uplink of the estimation reference information, outputting prompt information matched with the indication information.
2. The method of claim 1, wherein the purchase type includes a service purchase, and wherein obtaining pre-estimated reference information matching the purchase type includes:
determining service purchase data matched with the service purchase from a preset storage area, and extracting the mechanism information and the item information of the object to be purchased from the object data;
screening target purchasing data of the same-level mechanism of the object to be purchased from the service purchasing data based on the mechanism information, wherein the target purchasing data comprises purchasing resource quantity of each same-level mechanism in each service purchasing item and item information of each service purchasing item;
determining each reference service item of the object to be purchased from each service purchasing item corresponding to each peer mechanism according to a preset matching algorithm;
and determining the purchased resource amount corresponding to each reference service item and the item information of each reference service item as pre-estimated reference information.
3. The method as claimed in claim 2, wherein before determining the service procurement data matching with the service procurement from the preset storage area and screening the target procurement data of the peer organization of the object to be procured from the service procurement data based on the organization information, the method further comprises:
collecting service purchase data and organization information of each organization;
and storing the service purchase data of each mechanism to a preset storage area in a tree-shaped storage structure based on the mechanism information, wherein the tree-shaped storage structure represents the hierarchical relationship among the mechanisms.
4. The method as claimed in claim 2, wherein the determining, according to a preset matching algorithm, each reference service item of the object to be purchased from each service purchase item corresponding to each peer entity includes:
calculating the item similarity of the object to be purchased and each service purchasing item corresponding to the same level mechanism according to a preset matching algorithm;
sequencing the service purchasing items according to the sequence of the item similarity from big to small;
and determining the service purchasing items of the top N in the sequence as the reference service items of the object to be purchased, wherein N is an integer greater than 0.
5. The method according to any one of claims 2 to 4, wherein the performing resource amount estimation on the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determining a resource amount estimation result for the object to be purchased comprises:
acquiring the purchased resource amount corresponding to each reference service item from the pre-estimated reference information;
calculating the average value of the purchased resource amount corresponding to each reference service item;
and determining the average calculation result as a resource amount estimation result aiming at the object to be purchased.
6. The method of claim 1, wherein the type of purchase comprises a purchase of goods, and wherein obtaining pre-estimated reference information matching the type of purchase comprises:
acquiring goods purchasing data matched with the goods purchasing from a preset storage area;
extracting identification information of the object to be purchased from the object data;
inquiring the purchase resource amount of the object to be purchased in each goods purchase item and the item information of each goods purchase item from the goods purchase data based on the identification information;
and determining the purchasing resource amount of the object to be purchased in each goods purchasing item and the item information of each goods purchasing item as pre-estimated reference information.
7. The method of claim 6, wherein the performing resource amount estimation on the object to be purchased based on the target estimation processing strategy and the estimation reference information, and determining a resource amount estimation result for the object to be purchased comprises:
acquiring the purchasing resource quantity of the object to be purchased in each goods purchasing item from the pre-estimated reference information;
deleting the maximum resource quantity and the minimum resource quantity in the purchase resource quantities;
calculating the average value of each purchased resource amount after deleting the maximum resource amount and the minimum resource amount;
and determining the calculated average value as a resource amount estimation result aiming at the object to be purchased.
8. An apparatus for processing resource amount estimation results, the apparatus comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring object data of an object to be purchased when an estimation request of a user for the object to be purchased is detected;
the processing module is used for calling a classification model to analyze the object data so as to determine a purchasing type corresponding to the object to be purchased;
the acquisition module is also used for acquiring the pre-estimated reference information matched with the purchase type;
the processing module is further configured to determine a target pre-estimation processing strategy matched with the purchase type from at least one pre-estimation processing strategy, perform resource amount estimation on the object to be purchased based on the target pre-estimation processing strategy and the pre-estimation reference information, and determine a resource amount estimation result for the object to be purchased;
the processing module is further used for carrying out digital signature on the resource quantity estimation result and the estimation reference information based on the private key of the user;
the communication module is used for sending the resource quantity estimation result and the estimation reference information after the digital signature to a node in a block chain network so as to verify the digital signature by the node and carry out uplink processing on the resource quantity estimation result and the estimation reference information after the verification is passed;
the communication module is further configured to receive indication information, which is returned by the node and is directed to the resource amount estimation result and the uplink success of the estimation reference information;
and the output module is further used for outputting prompt information matched with the indication information when the communication module is detected to receive the indication information.
9. A terminal device comprising a processor and a memory, the processor and the memory being interconnected, wherein the memory is configured to store a computer program comprising program instructions, and wherein the processor is configured to invoke the program instructions to perform the method of any one of claims 1-7.
10. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program, which is executed by a processor to implement the method of any one of claims 1-7.
CN202010200048.2A 2020-03-19 2020-03-19 Resource quantity estimation result processing method and related equipment Pending CN111476597A (en)

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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112445441A (en) * 2020-11-23 2021-03-05 深圳平安综合金融服务有限公司 Printing processing system, method and related equipment
CN114387085A (en) * 2022-01-12 2022-04-22 见知数据科技(上海)有限公司 Method and device for processing pipeline data, computer equipment and storage medium

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112445441A (en) * 2020-11-23 2021-03-05 深圳平安综合金融服务有限公司 Printing processing system, method and related equipment
CN114387085A (en) * 2022-01-12 2022-04-22 见知数据科技(上海)有限公司 Method and device for processing pipeline data, computer equipment and storage medium
CN114387085B (en) * 2022-01-12 2024-04-16 见知数据科技(上海)有限公司 Method, device, computer equipment and storage medium for processing stream data

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