CN111091888A - Activity decision method, device, equipment and storage medium - Google Patents
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Abstract
The embodiment of the invention provides an activity decision method, an activity decision device, activity decision equipment and a storage medium. The method comprises the following steps: acquiring historical data of activity arrangement stored in a blockchain and personal information of a plurality of old people participating in the activity; training the intelligent decision-making model by adopting the historical data of the activity arrangement to obtain the trained intelligent decision-making model; according to personal information of a plurality of old people participating in the activity, a decision-making activity participation scheme is made through a trained intelligent decision-making model, and the participation scheme comprises at least one of the following: the project name of the event, the content of the event, the holding time of the event, the holding place of the event and the information of the participators; and sending the activity participation scheme to the terminal devices of the plurality of the old people or the terminal device of the activity organizer. The embodiment of the invention improves the efficiency and the accuracy of the decision of the activity participation scheme.
Description
Technical Field
The embodiments of the present invention relate to the field of communications technologies, and in particular, to an activity decision method, an activity decision device, an activity decision apparatus, and a storage medium.
Background
As the physical living standard of people is improved, the mental civilization is also improved, for example, workers in an aged-care community can regularly or irregularly organize the elderly to participate in activities.
Due to the individual differences of the elderly, for example, the elderly have different interests, different free activity times, different living places, different health conditions, etc., it is difficult for the working staff in the elderly community to quickly and accurately arrange the activities that the elderly can participate in.
Disclosure of Invention
The embodiment of the invention provides an activity decision method, an activity decision device, activity decision equipment and a storage medium, which are used for improving the efficiency and the accuracy of activity participation scheme decision.
In a first aspect, an embodiment of the present invention provides an activity decision method, including:
acquiring historical data of activity arrangement stored in a blockchain and personal information of a plurality of old people participating in the activity;
training an intelligent decision-making model by using the historical data of the activity arrangement to obtain a trained intelligent decision-making model;
according to the personal information of the plurality of the old people participating in the activity, through the trained intelligent decision-making model, deciding an activity participation scheme, wherein the participation scheme comprises at least one of the following: the project name of the event, the content of the event, the holding time of the event, the holding place of the event and the information of the participators;
and sending the activity participation scheme to the terminal equipment of the plurality of the old people or the terminal equipment of the activity organizer.
In a second aspect, an embodiment of the present invention provides an activity decision apparatus, including:
the acquisition module is used for acquiring historical data of activity arrangement stored in the blockchain and personal information of a plurality of old people participating in the activity;
the training module is used for training the intelligent decision-making model by adopting the historical data of the activity arrangement to obtain the trained intelligent decision-making model;
a decision module, configured to decide, according to the personal information of the plurality of elderly participating in the activity, an activity participation scheme through the trained intelligent decision model, where the participation scheme includes at least one of: the project name of the event, the content of the event, the holding time of the event, the holding place of the event and the information of the participators;
and the sending module is used for sending the activity participation scheme to the terminal equipment of the plurality of the old people or the terminal equipment of the activity organization personnel.
In a third aspect, an embodiment of the present invention provides a node device of a block chain network, including:
a memory;
a processor;
a communication interface; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of the first aspect.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, the computer program being executed by a processor to implement the method of the first aspect.
According to the activity decision method, the activity decision device, the activity decision equipment and the storage medium, the historical data of activity arrangement and the personal information of a plurality of old people participating in activities, which are stored in the block chain, are obtained, the historical data of the activity arrangement is adopted to train the intelligent decision model, the trained intelligent decision model is obtained, and the activity participation scheme is decided according to the personal information of the plurality of old people participating in activities and through the trained intelligent decision model, so that the efficiency and the accuracy of the activity participation scheme decision are improved.
Drawings
Fig. 1 is a schematic diagram of an application scenario provided in an embodiment of the present invention;
FIG. 2 is a flowchart of an activity decision method according to an embodiment of the present invention;
FIG. 3 is a flowchart of an activity decision method according to another embodiment of the present invention;
FIG. 4 is a flowchart of an activity decision method according to another embodiment of the present invention;
FIG. 5 is a flowchart of an activity decision method according to another embodiment of the present invention;
FIG. 6 is a schematic structural diagram of an activity decision device according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a blockchain network node according to an embodiment of the present invention.
Specific embodiments of the present disclosure have been shown in the drawings and will be described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. The following description refers to the accompanying drawings, in which like numerals in different drawings represent the same or similar elements, unless otherwise specified. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The activity decision method provided by the embodiment of the invention can be applied to the communication system shown in fig. 1. As shown in fig. 1, the communication system includes: the blockchain network node 1-blockchain network node 5, specifically, the blockchain network node 1-blockchain network node 5 are nodes in the blockchain network, and are only schematically illustrated here, and do not limit the architecture of the blockchain network and the number of nodes in the blockchain network. In this embodiment, the terminal devices of the activity participants or the organization personnel may be nodes in a blockchain network, and one or more groups or companies participating in artificial intelligence of the senior citizen community to assist the resident in spontaneously developing activity arrangement experience sharing and management may also be nodes in the blockchain network. Enterprises or individuals registered in the blockchain network can upload historical data of relevant old-age community artificial intelligence auxiliary residents for spontaneously developing activity arrangement, personal information of a plurality of old people participating in the activity and relevant certification information to the blockchain. The information stored in the block chain has the characteristics of privacy protection, openness and transparency, traceability, low possibility of tampering and the like.
The embodiment of the invention provides an activity decision method, which aims to solve the technical problems in the prior art.
The technical solution of the present invention and how to solve the above technical problems will be described in detail with specific embodiments below. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
Fig. 2 is a flowchart of an activity decision method according to an embodiment of the present invention. The embodiment of the invention provides an activity decision method aiming at the technical problems in the prior art, and the method comprises the following specific steps:
In a blockchain network formed by terminal devices of activity participants or organization personnel, one or more groups or companies participating in sharing and managing activity arrangement experience autonomously by the residents under the assistance of artificial intelligence in the endowment community, part of nodes can be used as nodes for storing information, and part of nodes can be used as nodes for processing information, or some nodes can be used as nodes for storing information and also can be used as nodes for processing information, which is not limited herein.
For example, an information storage subsystem is included in the blockchain network, and the information storage subsystem may include a plurality of nodes that may serve as nodes for storing information. Enterprises or individuals registered in the blockchain network can upload historical data of the relevant old-age community artificial intelligence for assisting residents to spontaneously develop activity arrangement, personal information of a plurality of old people participating in activities and relevant certification information to the storage subsystem. The history data may be information of an event in which the elderly have actually participated, for example, a project name of the event in which the elderly have actually participated, content of the event, a holding time of the event, a holding place of the event, information of participants, and the like. The personal information of the plurality of elderly people participating in the event may be personal information of a plurality of elderly people about to participate in the event, for example, interest and hobby information of the elderly people (singing, dancing, painting, chess, knitting, calligraphy, collecting, drama, swimming, etc.), free activity arrangement time of the elderly people, living places of the elderly people, feedback information of the elderly people on the event in which the elderly people have participated, priority information of participation of the elderly people in the event, and physical health condition information of the elderly people (for example, information on whether the elderly people need help when going out, etc.). The related certification information may specifically include identity information of the elderly, photos and/or videos of participating in the activity, and the like.
Additionally, an active decision subsystem is included in the blockchain network, which may include a plurality of nodes that may serve as nodes for processing information. The activity decision subsystem can acquire historical data of the artificial intelligence of the endowment community to assist residents to spontaneously develop activity arrangement, personal information of a plurality of old people participating in activities and related proving information from the information storage subsystem.
The activity decision subsystem may train an intelligent decision model using the activity-arranged historical data, and optionally, the intelligent decision model may specifically be a k-nearest neighbor classification algorithm (KNN) clustering model to obtain the trained intelligent decision model.
The activity decision subsystem may include a plurality of nodes, which may be in particular the main servers of the respective aging communities, which are responsible for training the intelligent decision model.
In a possible implementation manner, the training an intelligent decision model by using the historical data of the activity arrangement to obtain a trained intelligent decision model includes: distributing the historical data of the activity arrangement to a plurality of nodes in a block chain network, wherein the plurality of nodes store the intelligent decision model, obtaining a trained intelligent decision model according to the parameters of the intelligent decision model obtained by distributed calculation of the plurality of nodes, and storing the trained intelligent decision model to a block chain.
For example, the intelligent decision model may be stored in a blockchain. The historical data of the activity arrangement can be averagely distributed to a plurality of nodes of the activity decision subsystem, the nodes are respectively stored with intelligent decision models, the nodes can train parameters of the intelligent decision models through distributed calculation, further, the trained intelligent decision models are obtained by combining the parameters of the intelligent decision models obtained through the distributed calculation of the nodes, and the trained intelligent decision models are stored on the block chain, so that the intelligent decision models stored in the block chain are synchronized and updated.
In another possible implementation manner, the training an intelligent decision model by using the historical data of the activity arrangement to obtain a trained intelligent decision model includes: and sending the historical data of the activity arrangement and the intelligent decision-making model to a node in a block chain network, wherein the node is used for training the intelligent decision-making model according to the historical data and storing the trained intelligent decision-making model to a block chain.
For example, a node in the activity decision subsystem may download the historical data of the activity arrangement and the intelligent decision model from the blockchain at regular time, and train the intelligent decision model according to the historical data to obtain a trained intelligent decision model. Further, the node can also store the trained intelligent decision model to the block chain, so that the intelligent decision model stored in the block chain can be periodically updated.
The activity decision subsystem further inputs personal information of a plurality of old people participating in the activity into the trained intelligent decision model, and the trained intelligent decision model can be used for deciding an activity participation scheme and outputting the activity participation scheme. The participation scheme may specifically be a participation scheme of a plurality of activity items, for example, the participation scheme of each activity item includes at least one of the following: the project name of the event (e.g., a calligraphy tournament, gym, poetry, singing race, etc.), the content of the event (e.g., without limitation, genre), the time of the event (e.g., 2019, 5/1), the venue of the event (e.g., XX senior citizens' community), participant information, and the like.
And step 204, sending the activity participation scheme to the terminal equipment of the plurality of the old people or the terminal equipment of the activity organization personnel.
After the activity decision subsystem decides the activity participation scheme, the activity participation scheme can be sent to terminal equipment of the old people participating in the activity or terminal equipment of activity organization personnel. For example, if the participants of the calligraphy competition include the elderly a, the elderly B, the elderly C, and the elderly D, the activity decision subsystem may send the participation scheme corresponding to the calligraphy competition to the respective terminal devices of the elderly a, the elderly B, the elderly C, and the elderly D. Or, the activity decision subsystem may also send the participation scheme of each activity item to the terminal device of the activity organizer, so that the activity organizer can notify the corresponding participant of each activity item according to the participation scheme of each activity item.
After the activity organization is finished, the activity organization personnel can also count the actual number of participants, the actual participant information, the evaluation information of the actual participants on the activity projects participated by the activity organization personnel, and the like, and the activity organization personnel can improve the content, the form and the like of the activity projects participated by the activity organization personnel according to the evaluation information of the actual participants on the activity projects participated by the activity organization personnel. In addition, the activity organizer can also upload the actual number of participants, the actual participant information, the evaluation information of the actual participants on the activity items participated in by the activity organizer, and the like of each activity item to the blockchain network through the terminal device, so that the actual number of participants, the actual participant information, the evaluation information of the actual participants on the activity items participated in by the activity organizer, and the like of each activity item can be used as the historical data, and the intelligent decision model can be continuously trained along with the increase of the historical data, namely, the coefficients of the intelligent decision model are continuously adjusted, so that the intelligent decision model can be continuously trained, and the accuracy of the intelligent decision model is improved.
According to the embodiment of the invention, the historical data of activity arrangement stored in the blockchain and the personal information of a plurality of old people participating in the activity are obtained, the historical data of the activity arrangement is adopted to train the intelligent decision-making model to obtain the trained intelligent decision-making model, and the activity participation scheme is decided according to the personal information of the plurality of old people participating in the activity through the trained intelligent decision-making model, so that the efficiency and the accuracy of the decision of the activity participation scheme are improved.
Fig. 3 is a flowchart of an activity decision method according to another embodiment of the present invention. On the basis of the above embodiment, the decision-making activity participation scheme, according to the personal information of the plurality of elderly participating in the activity, through the trained intelligent decision-making model, includes the following steps:
For example, a feature vector in the personal information of each of the elderly persons is extracted according to the personal information of the plurality of elderly persons participating in the activity, where the feature vector may be represented as F ═ { F1, F2, …, fn }, F1, F2, …, and fn may sequentially represent interest and hobby information of the elderly persons, free activity arrangement time of the elderly persons, living places of the elderly persons, and the like, that is, { F1, F2, …, fn }, which is { interest and hobby information of the elderly persons, free activity arrangement time of the elderly persons, living places of the elderly persons, … }. If an elderly person has a taste, a feature vector can be extracted according to personal information of the elderly person. If an elderly person has multiple interests, multiple feature vectors can be extracted according to personal information of the elderly person.
Optionally, the personal information of the elderly includes a plurality of interest and hobby information of the elderly; determining a plurality of feature vectors according to the personal information of the plurality of the elderly participating in the activity, including: and determining a feature vector corresponding to each interest and preference information in the interest and preference information according to the interest and preference information of the old people.
For example, the elderly a have two interests, namely calligraphy and swimming, and two feature vectors can be extracted according to personal information of the elderly a, wherein the two feature vectors can be represented as F1 and F2, specifically, F1 ═ calligraphy, free activity schedule time of the elderly a, living place of the elderly a, … }; f2 ═ swim, free activity schedule time for senior a, place of residence for senior a, … }. Similarly, if other elderly people participating in activities also have multiple interests, multiple feature vectors can be extracted according to personal information of the elderly people, and the interest and the feature vectors of the same elderly people are in one-to-one correspondence.
And 302, clustering the plurality of feature vectors by adopting the intelligent decision model to obtain the activity participation scheme.
In a possible implementation manner, the clustering the plurality of feature vectors by using the intelligent decision model to obtain the activity participation scheme includes: assigning the plurality of feature vectors to a plurality of nodes in a blockchain network; and obtaining the active participation scheme according to a clustering result obtained by clustering the distributed characteristic vectors of each node in the plurality of nodes by adopting the intelligent decision model, and storing the active participation scheme to a block chain.
For example, a plurality of nodes in the blockchain network may be responsible for cluster computation, e.g., there are n nodes responsible for cluster computation, and the computation power of each of the n nodes is the same. The data size of the feature vector to be clustered in a certain period of time in the blockchain network is m, and the size relationship between m and n is not limited here. Further, the feature vectors to be clustered may be equally allocated to the plurality of nodes, for example, each node is allocated to a feature vector with a data size of m/n. Each node may perform clustering calculation on the assigned feature vectors with the size of m/n by using an intelligent decision model, for example, the trained intelligent decision model as described above, further obtain the activity participation scheme by combining the clustering results obtained after the clustering calculation of the n nodes, and store the activity participation scheme in the block chain.
In another possible implementation manner, the clustering the feature vectors by using the intelligent decision model to obtain the activity participation scheme includes: and sending the plurality of feature vectors to a node in a block chain network, wherein the node is used for clustering the plurality of feature vectors by adopting the intelligent decision model to obtain the activity participation scheme, and storing the activity participation scheme to a block chain.
Specifically, a certain node in the blockchain network, for example, a main server in the blockchain network or a main server in an aging community, may download the intelligent decision model in the blockchain to the local, cluster the plurality of feature vectors according to the intelligent decision model to obtain the activity participation scheme, and store the activity participation scheme in the blockchain.
Optionally, the clustering the plurality of feature vectors by using the intelligent decision model to obtain the activity participation scheme includes the following steps as shown in fig. 4:
For example, at least one feature vector corresponding to the personal information of each elderly person participating in the activity is input into the KNN clustering model as described above, and the KNN clustering model can output an activity category C { C1, C2, …, cm } corresponding to the hobbies of interest of each elderly person, such as { calligraphic tournament, fitness exercise, poetry, singing competition, etc }, and it can be understood that the activity category here is specifically the item name of the activity described in the above embodiment. In addition, the KNN clustering model can also output activity content, holding time, holding place, participant information and the like corresponding to each activity category. Thus, the project name, the content, the holding time, the holding place, the participant information and the like of each event constitute the participation scheme of the event project.
For example, if the elderly a has two interests, namely calligraphy and swimming, the elderly a may be simultaneously assigned to the calligraphy tournament and the swimming project, and if the calligraphy tournament is designated as c1 and the swimming project is designated as c2, an activity project that best matches the interests of the elderly a may be determined from c1 and c2 according to the priority selection information and the historical feedback information of the elderly a for calligraphy and swimming.
Optionally, the determining, according to the priority selection information and the historical feedback information of the elderly person on the multiple different activity items, an activity item that is most matched with the interests and hobbies of the elderly person in the multiple different activity items includes: determining the scoring value of each of the plurality of different activity items according to the priority selection information and the historical feedback information of the old people on the plurality of different activity items; and taking the activity item with the highest scoring value in the plurality of different activity items as the activity item which is most matched with the interest and hobbies of the old.
For example, if the priority selection information of the elder a on the calligraphy match is a _ c1, the priority selection information of the elder a on the swimming item is a _ c2, the historical feedback information of the elder a on the calligraphy match is B _ c1, and the historical feedback information of the elder a on the swimming item is B _ c2, the activity item which is most matched with the interest and hobbies of the elder a can be determined according to a { a _ c1, a _ c2} and B { B _ c1, B _ c2 }. Specifically, the score values of the calligraphic tournament and the swimming item may be calculated according to a { a _ c1, a _ c2} and B { B _ c1, B _ c2}, for example, the score value of the calligraphic tournament is denoted as P (c1), the score value of the swimming item is denoted as P (c2), P (c1) ═ a1 × a _ c1+ a2 × B _ c1, and P (c2) ═ a1 × a _ c2+ a2 × B _ c2, where a1 and a2 are preset parameters, and the present embodiment does not limit the specific values of a1 and a 2. After calculating P (c1) and P (c2), it can be compared which of P (c1) and P (c2) is the largest, and if P (c1) is the largest, the calligraphy tournament is the activity item that best matches the hobbies of elderly a, and if P (c2) is the largest, the swimming item is the activity item that best matches the hobbies of elderly a.
Without loss of generality, the input of the KNN clustering model is F ═ F1, F2, …, fn, the output of the KNN clustering model is C { C1, C2, …, cm }, and assuming that a certain elderly X is assigned to k activity classes, namely { C1, C2, …, ck }, and k is less than or equal to m, the activity item most matched with the interest of the elderly X can be determined according to the priority selection information { a1, a2, …, Ak } and the historical feedback information { B1, B2, …, Bk } of the elderly X for each of the k activity classes.
Specifically, the score value of each of the k activity categories is calculated, for example, the score value of each of the k activity categories is denoted as p (ci), i is greater than or equal to 1, i is less than or equal to k, p (ci) ═ a1 Ai + a2 Bi, and the activity category corresponding to the largest value of p (ci) is used as the activity item that most matches the interest and hobbies of the elderly X.
In addition, in this embodiment, the block chain network further includes a system performance evaluation subsystem, where the system performance evaluation subsystem may evaluate timeliness, effectiveness, and accuracy of the artificial intelligence assisted householder for the senior community to spontaneously develop activity arrangement experience sharing and management system, and continuously adjust and optimize system parameters based on an intelligent decision method for optimizing the combination of multiple factors such as personal interests, time, location, trip, feedback, activity priority of the elderly and dynamic combination of related activities of interest of the elderly, so as to effectively implement the artificial intelligence assisted householder for spontaneously developing activity arrangement experience sharing and management in the block chain network, thereby effectively promoting effective popularization of the block chain technology applied to the artificial intelligence assisted householder for the senior community in developing activity arrangement experience sharing and management.
According to the embodiment of the invention, the activity item which is most matched with the interests and hobbies of the old is determined according to the priority selection information and the historical feedback information of the old on the plurality of different activity items, so that the accuracy of the activity decision method is improved.
Fig. 5 is a flowchart of an activity decision method according to another embodiment of the present invention. As shown in fig. 5, the present embodiment specifically introduces the functions and roles of the blockchain network building subsystem, the information storage and information authentication data format defining subsystem, the information storage subsystem, the activity decision subsystem, and the system performance evaluation subsystem. In addition, the present embodiment also provides an example of transaction information, and it can be understood that the transaction information herein is generally referred to as transaction information, that is, one information entry in the blockchain network is one transaction. The transaction information is shown in table 1 below:
TABLE 1
The transaction information shown in table 1 can be stored in a block of the blockchain, that is, the transaction information in table 1 can be linked, for example, the personal information of the elderly, the historical data, i.e., the experience information, the activity participation scheme of the elderly analyzed by the system, etc. can be linked. The method and the device have the advantages that the personal information, the historical data, the activity participation scheme of the old people and other information of the old people can be stored in the blocks according to a specific data format, and the data storage and data processing efficiency is improved.
Fig. 6 is a schematic structural diagram of an activity decision device according to an embodiment of the present invention. The activity decision device may specifically be the activity decision system in the above embodiment, or a node in the activity decision. The activity decision device provided in the embodiment of the present invention may execute the processing flow provided in the embodiment of the activity decision method, as shown in fig. 6, the activity decision device 60 includes: an acquisition module 61, a training module 62, a decision module 63 and a sending module 64; the acquiring module 61 is used for acquiring historical data of activity arrangement stored in the blockchain and personal information of a plurality of old people participating in the activity; the training module 62 is configured to train the intelligent decision model by using the activity arrangement historical data to obtain a trained intelligent decision model; the decision module 63 is configured to decide, according to the personal information of the plurality of elderly people participating in the activity, an activity participation scheme through the trained intelligent decision model, where the participation scheme includes at least one of: the project name of the event, the content of the event, the holding time of the event, the holding place of the event and the information of the participators; the sending module 64 is configured to send the activity participation scheme to the terminal devices of the plurality of elderly people or the terminal device of the activity organization personnel.
Optionally, the decision module 63 includes a determination module 631 and a clustering module 632; wherein the determining module 631 is configured to determine a plurality of feature vectors according to the personal information of the plurality of elderly people participating in the activity, and each feature vector of the plurality of feature vectors includes at least one of the following: the interest and hobby information of the old, the free activity arrangement time of the old and the living place of the old; the clustering module 632 is configured to cluster the plurality of feature vectors by using the intelligent decision model to obtain the activity participation scheme. .
Optionally, the personal information of the elderly includes a plurality of interest and hobby information of the elderly; the determining module 631 is specifically configured to: and determining a feature vector corresponding to each interest and preference information in the interest and preference information according to the interest and preference information of the old people.
Optionally, the clustering module 632 is specifically configured to: clustering the plurality of feature vectors by adopting the intelligent decision model to obtain activity items matched with the interests and hobbies of the old; and if the same old person is distributed in a plurality of different activity items, determining the activity item which is most matched with the interest and hobbies of the old person in the plurality of different activity items according to the priority selection information and the historical feedback information of the old person on the plurality of different activity items.
Optionally, when determining, according to the priority selection information and the historical feedback information of the elderly on the multiple different activity items, an activity item that is most matched with the interests and hobbies of the elderly in the multiple different activity items, the clustering module 632 is specifically configured to: determining the scoring value of each of the plurality of different activity items according to the priority selection information and the historical feedback information of the old people on the plurality of different activity items; and taking the activity item with the highest scoring value in the plurality of different activity items as the activity item which is most matched with the interest and hobbies of the old.
Optionally, the training module 62 trains the intelligent decision model by using the activity-arranged historical data, and when the trained intelligent decision model is obtained, the training module is specifically configured to: distributing the historical data of the activity arrangement to a plurality of nodes in a block chain network, wherein the nodes store the intelligent decision model, obtaining a trained intelligent decision model according to the parameters of the intelligent decision model obtained by distributed calculation of the nodes, and storing the trained intelligent decision model to a block chain; or sending the historical data of the activity arrangement and the intelligent decision-making model to a node in a block chain network, wherein the node is used for training the intelligent decision-making model according to the historical data and storing the trained intelligent decision-making model to a block chain.
Optionally, the clustering module 632 is configured to cluster the plurality of feature vectors by using the intelligent decision model, and when the activity participation scheme is obtained, specifically configured to: assigning the plurality of feature vectors to a plurality of nodes in a blockchain network; obtaining the activity participation scheme according to a clustering result obtained by clustering the distributed characteristic vectors of each node in the plurality of nodes by adopting the intelligent decision model, and storing the activity participation scheme to a block chain; or sending the plurality of feature vectors to a node in a block chain network, wherein the node is used for clustering the plurality of feature vectors by adopting the intelligent decision model to obtain the activity participation scheme, and storing the activity participation scheme to a block chain.
The activity decision device of the embodiment shown in fig. 6 can be used to implement the technical solutions of the above method embodiments, and the implementation principles and technical effects thereof are similar and will not be described herein again.
Fig. 7 is a schematic structural diagram of a blockchain network node according to an embodiment of the present invention. The blockchain network node may specifically be the node in the activity decision in the above embodiments. As shown in fig. 7, the blockchain network node 70 may execute the processing procedure provided in the embodiment of the activity decision method, and includes: memory 71, processor 72, computer programs and communication interface 73; wherein a computer program is stored in the memory 71 and is configured to perform the activity decision method as described above by the processor 72.
The block chain network node of the embodiment shown in fig. 7 may be used to implement the technical solution of the above method embodiment, and the implementation principle and technical effect are similar, and are not described herein again.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the activity decision method described in the foregoing embodiment.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
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 also be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of hardware and a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
It is obvious to those skilled in the art that, for convenience and simplicity of description, the above-mentioned division of the functional modules is merely used as an example, and in practical applications, the above-mentioned functional allocation may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above-mentioned functions. For the specific working process of the device described above, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and such modifications and substitutions do not depart from the spirit and scope of the present invention as defined by the appended claims.
Claims (10)
1. An activity decision method, comprising:
acquiring historical data of activity arrangement stored in a blockchain and personal information of a plurality of old people participating in the activity;
training an intelligent decision-making model by using the historical data of the activity arrangement to obtain a trained intelligent decision-making model;
according to the personal information of the plurality of the old people participating in the activity, through the trained intelligent decision-making model, deciding an activity participation scheme, wherein the participation scheme comprises at least one of the following: the project name of the event, the content of the event, the holding time of the event, the holding place of the event and the information of the participators;
and sending the activity participation scheme to the terminal equipment of the plurality of the old people or the terminal equipment of the activity organizer.
2. The method of claim 1, wherein said deciding an activity participation scheme according to personal information of said plurality of elderly participating in an activity through said trained intelligent decision model comprises:
determining a plurality of feature vectors according to personal information of a plurality of the old people participating in the activity, wherein each feature vector in the plurality of feature vectors comprises at least one of the following: the interest and hobby information of the old, the free activity arrangement time of the old and the living place of the old;
and clustering the plurality of characteristic vectors by adopting the intelligent decision-making model to obtain the activity participation scheme.
3. The method of claim 2, wherein the personal information of the elderly person includes a plurality of hobby information of the elderly person;
determining a plurality of feature vectors according to the personal information of the plurality of the elderly participating in the activity, including:
and determining a feature vector corresponding to each interest and preference information in the interest and preference information according to the interest and preference information of the old people.
4. The method of claim 3, wherein clustering the plurality of feature vectors using the intelligent decision model to obtain the campaign participation scheme comprises:
clustering the plurality of feature vectors by adopting the intelligent decision model to obtain activity items matched with the interests and hobbies of the old;
and if the same old person is distributed in a plurality of different activity items, determining the activity item which is most matched with the interest and hobbies of the old person in the plurality of different activity items according to the priority selection information and the historical feedback information of the old person on the plurality of different activity items.
5. The method of claim 4, wherein determining the activity item of the plurality of different activity items that best matches the elderly's hobbies based on the elderly's priority selection information and historical feedback information for the plurality of different activity items comprises:
determining the scoring value of each of the plurality of different activity items according to the priority selection information and the historical feedback information of the old people on the plurality of different activity items;
and taking the activity item with the highest scoring value in the plurality of different activity items as the activity item which is most matched with the interest and hobbies of the old.
6. The method of claim 1, wherein training an intelligent decision model using the historical data of the activity schedule to obtain a trained intelligent decision model comprises:
distributing the historical data of the activity arrangement to a plurality of nodes in a block chain network, wherein the nodes store the intelligent decision model, obtaining a trained intelligent decision model according to the parameters of the intelligent decision model obtained by distributed calculation of the nodes, and storing the trained intelligent decision model to a block chain; or
And sending the historical data of the activity arrangement and the intelligent decision-making model to a node in a block chain network, wherein the node is used for training the intelligent decision-making model according to the historical data and storing the trained intelligent decision-making model to a block chain.
7. The method according to any one of claims 2 to 6, wherein the clustering the plurality of feature vectors using the intelligent decision model to obtain the activity participation scheme comprises:
assigning the plurality of feature vectors to a plurality of nodes in a blockchain network; obtaining the activity participation scheme according to a clustering result obtained by clustering the distributed characteristic vectors of each node in the plurality of nodes by adopting the intelligent decision model, and storing the activity participation scheme to a block chain; or
And sending the plurality of feature vectors to a node in a block chain network, wherein the node is used for clustering the plurality of feature vectors by adopting the intelligent decision model to obtain the activity participation scheme, and storing the activity participation scheme to a block chain.
8. An activity decision device, comprising:
the acquisition module is used for acquiring historical data of activity arrangement stored in the blockchain and personal information of a plurality of old people participating in the activity;
the training module is used for training the intelligent decision-making model by adopting the historical data of the activity arrangement to obtain the trained intelligent decision-making model;
a decision module, configured to decide, according to the personal information of the plurality of elderly participating in the activity, an activity participation scheme through the trained intelligent decision model, where the participation scheme includes at least one of: the project name of the event, the content of the event, the holding time of the event, the holding place of the event and the information of the participators;
and the sending module is used for sending the activity participation scheme to the terminal equipment of the plurality of the old people or the terminal equipment of the activity organization personnel.
9. A blockchain network node, comprising:
a memory;
a processor;
a communication interface; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to implement the method of any one of claims 1-7.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-7.
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