CN116383368A - Intelligent information pushing method and system based on big data - Google Patents
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Abstract
The invention discloses an intelligent information pushing method and system based on big data; wherein the method comprises the following steps: acquiring first big data related to a scene where a user is located and second big data related to the user; determining information pushing time according to the first big data and the second big data; performing information pushing according to the information pushing moment; according to the scheme provided by the invention, the service providing time can be accurately predicted based on the scene and the big data of the user, so that information pushing is further executed, excessive operations are not required to be executed by the user, and more intelligent service using experience can be provided for the user.
Description
Technical Field
The invention relates to the technical field of big data and information, in particular to an intelligent information pushing method and system based on the big data.
Background
With the continuous construction of smart cities, smart city systems can provide more and more high-quality service experiences for people. For example, some APP can provide taxi reservation services, and a user can issue a taxi demand as long as the user sets the taxi time and position, so that the platform can match and screen a suitable taxi to arrive at a specified position on time to provide services. However, this method still requires the user to input excessive content, and the user also needs to go to and receive the riding service at a designated time, and the user has a large uncertainty in the activities of the user in a mall or the like, so that it is generally difficult for the user to determine the accurate riding time, which results in that the driver needs to wait for a long time at the designated place, or the user must hurry to go to the designated place to receive the service, so that the use experience is poor.
The applicant of the present invention has searched the prior art and found the following: document 1 (CN 113435197 a) discloses a data pushing method for pushing a server, the method comprising: acquiring a policy information pool; determining a plurality of target policy information matched with the attribute information of the target enterprise in the policy information pool according to the attribute information of the target enterprise; acquiring the vocabulary searched by a plurality of reference enterprises corresponding to the target enterprises in a preset historical time period; determining that at least part of the words are hotwords corresponding to the target enterprises according to the frequencies of the words searched by the multiple reference enterprises in a preset historical time period; based on a preset matching model, determining push scores of the target policy information according to a plurality of preset interest words and a plurality of heat words corresponding to the target enterprise; and pushing the target policy information with the push score exceeding a preset push threshold to terminal equipment corresponding to the target enterprise.
Document 2 (CN 112927004 a) discloses an information cloud computing analysis method for big data portraits, which is applied to an information push server, the information push server is in communication connection with a plurality of mobile software servers, the information push server is implemented according to a cloud computing platform, and the method comprises: determining a first unit service representation corresponding to each of a plurality of software micro services based on micro service operation data of a service object sent by service operation nodes in the plurality of software micro services through a plurality of representation classification network models, wherein one representation classification network model is used for determining the corresponding first unit service representation based on the micro service operation data of the service object in one software micro service, and the plurality of software micro services are obtained after service differentiation is performed on the software service; and determining the overall service representation of the service object in the software business service based on the first unit service representation corresponding to each of the plurality of software micro services.
Document 3 (CN 112671886 a) discloses an information pushing method based on edge calculation and artificial intelligence, which is applied to a big data server, the big data server is communicatively connected with a plurality of information display devices, the method includes: acquiring a big data session node sequence between a target session service object and an associated session service object in a target session process page, wherein the big data session node sequence comprises a plurality of target session nodes called by the target session service object in the target session subscription service in the target session process page, a plurality of associated session nodes called by the associated session service object in the target session subscription service in the target session process page, and calling service positions of all session nodes, and the target session process page initiates and calls computing resources to perform computing operation based on the edge side of the big data server; constructing a session node intention list by using target session node intention lists corresponding to the target session nodes and associated session node intention lists corresponding to the associated session nodes, and acquiring session node intention description information according to the session node intention list, wherein the target session node intention list is used for representing key intention label distribution of the target session nodes interacted according to the calling service position, the associated session node intention list is used for representing key intention label distribution of the session nodes of the associated session nodes interacted according to the calling service position, and the session node intention description information is used for representing the target session node intention list and intention interest degree of the associated session node intention list; constructing a session node interest sequence by utilizing the target session node which is called in a target session subscription service section in the big data session node sequence and according to the service flow direction of the calling service position and the associated session node, and acquiring session node interest description information according to the session node interest sequence, wherein the session node interest description information is used for representing the intention interest degree between at least two mapping session nodes in the session node interest sequence; according to the session node intention description information and the session node interest description information, acquiring the session interest degree between the target session service object and the associated session service object, determining an interest figure between the target session service object and the associated session service object according to the session interest degree, and sending push information to information display equipment corresponding to the target session service object and the associated session service object based on the interest figure.
Referring to the above documents, it can be seen that in the prior art, information pushing is mainly achieved based on attributes of users, but only single information is considered, so that rationality of information pushing cannot be achieved, and better information pushing experience cannot be provided for users, and user requirements cannot be met.
Disclosure of Invention
The invention mainly aims to provide an intelligent information pushing method, an intelligent information pushing system, electronic equipment and a readable storage medium based on big data, and aims to solve the technical problems in the background art so as to provide better information pushing experience for users.
In order to achieve the above object, a first aspect of the present invention provides an intelligent information pushing method based on big data, the method comprising the steps of: acquiring first big data related to a scene where a user is located and second big data related to the user; determining information pushing time according to the first big data and the second big data; and executing information pushing according to the information pushing moment.
Optionally, before the acquiring the first big data related to the scene where the user is located and the second big data related to the user, the method further includes: receiving a service demand instruction input by a user; or automatically generating a service demand instruction according to the historical data and the real-time data of the user.
Optionally, the service demand instruction includes location data and time data; the acquiring the first big data related to the scene where the user is located and the second big data related to the user includes: determining location information according to the location data, and determining the first big data according to the location information and the time data; and determining the second big data according to the place information and the time data.
Optionally, the determining the second big data according to the location information and the time data includes: extracting place attribute information from the place information; and calling historical data of the user according to the place attribute information and the time data, and taking the historical data as the second big data.
Optionally, the determining the information pushing moment according to the first big data and the second big data includes: determining a first duration according to the first big data, and determining a second duration according to the second big data; and determining a first time according to the first time and the second time, and determining the first time as the pushing time.
Optionally, the determining the first time according to the first time length and the second time length includes: accumulating the first time length and the second time length to obtain a third time length, and determining a second time according to the time data; and determining a third moment according to the second moment and the adjusting time length, and taking the third moment as the first moment.
Optionally, the adjustment duration is determined by: determining the number of peers according to the service demand instruction, and determining the familiarity of the user with the scene according to the historical data; determining the adjustment time length according to the number of the peers and the familiarity; the adjustment time length is positively correlated with the number of people in the same person and negatively correlated with the familiarity.
The invention also provides an intelligent information pushing system based on big data, which comprises a processing module, a storage module and a communication module, wherein the processing module is respectively connected with the storage module and the communication module; wherein the storage module is used for storing executable program codes; the communication module is used for acquiring first big data related to a scene where a user is located, second big data related to the user and executing the information pushing; the processing module is configured to call the executable program code stored in the storage module to execute the method as described above.
The third aspect of the present invention also provides a computer device comprising a memory in which a computer program is stored and a processor which, when calling the computer program in the memory, can implement the steps provided by the method described above.
The fourth aspect of the present invention also provides a computer readable storage medium having stored thereon a computer program which when executed performs the steps provided by the method described above.
In the technical scheme of the invention, first big data related to a scene where a user is located and second big data related to the user are acquired; determining information pushing time according to the first big data and the second big data; and executing information pushing according to the information pushing moment. According to the scheme provided by the invention, the service providing time can be accurately predicted based on the scene and the big data of the user, so that information pushing is further executed, excessive operations are not required to be executed by the user, and more intelligent service using experience can be provided for the user.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to the structures shown in these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of an intelligent information pushing method based on big data according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an intelligent information push system based on big data according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
Advantages of the invention are further illustrated in the following description, taken in conjunction with the accompanying drawings and detailed description. It is to be understood by persons skilled in the art that the following detailed description is illustrative and not restrictive, and that this invention is not limited to the details given herein.
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the invention. Rather, they are merely examples of apparatus and methods consistent with aspects of the invention as detailed in the accompanying claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the disclosure. As used in this specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any or all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used herein to describe various information, these information should not be limited by these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the invention. The word "if" as used herein may be interpreted as "at … …" or "at … …" or "responsive to a determination", depending on the context.
In the description of the present invention, it should be understood that the terms "longitudinal," "transverse," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," and the like indicate orientations or positional relationships based on the orientation or positional relationships shown in the drawings, merely to facilitate describing the present invention and simplify the description, and do not indicate or imply that the devices or elements referred to must have a specific orientation, be configured and operated in a specific orientation, and therefore should not be construed as limiting the present invention.
In the description of the present invention, unless otherwise specified and defined, it should be noted that the terms "mounted," "connected," and "coupled" are to be construed broadly, and may be, for example, mechanical or electrical, or may be in communication with each other between two elements, directly or indirectly through intermediaries, as would be understood by those skilled in the art, in view of the specific meaning of the terms described above.
Embodiment one: referring to fig. 1, fig. 1 is a flow chart of an intelligent information pushing method based on big data according to an embodiment of the present invention. As shown in fig. 1, the invention provides an intelligent information pushing method based on big data, which comprises the following steps: acquiring first big data related to a scene where a user is located and second big data related to the user; determining information pushing time according to the first big data and the second big data; and executing information pushing according to the information pushing moment.
In the embodiment of the invention, the scheme of the invention respectively acquires big data related to the scene of the user and the user, analyzes and predicts when the user needs to provide service based on the big data, and determines the proper moment to push information. According to the scheme provided by the invention, the service providing time can be accurately predicted based on the scene and the big data of the user, so that information pushing is further executed, excessive operations are not required to be executed by the user, and more intelligent service using experience can be provided for the user.
It should be noted that, the solution of the present invention is preferably implemented in an intelligent terminal device, that is, a corresponding Application (APP) is installed in the intelligent terminal device, where the intelligent terminal device may be a User Equipment (UE), a mobile device, a User terminal, a cellular phone, a cordless phone, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, or the like. In addition, the scheme of the invention can be realized on a platform end which can be in communication connection with the intelligent terminal equipment to provide corresponding services for corresponding application programs (APP) installed in the intelligent terminal equipment, wherein the platform end is built based on a server, the server can be an independent physical server, a server cluster or a distributed system formed by a plurality of physical servers, and can also be a cloud server for providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, network acceleration services (Content Delivery Network, CDN), basic cloud computing services such as big data and artificial intelligent platforms and the like. Wherein the server may be a node in a blockchain.
In addition, the information pushing in the solution of the present invention may further include two aspects, that is, pushing service information to the intelligent terminal device of the user based on the determined pushing moment, for example, "is a taxi to be called now? If the user feeds back the confirmation, the reservation information is further transmitted to another service provider (for example, a taxi, another business, or the like). Therefore, the user can go to the place B to receive the second service after the place A receives the first service, and the seamless connection between the two services can be realized as much as possible because the pushing moment is very accurate in determination, so that the user experience is improved.
Optionally, before the acquiring the first big data related to the scene where the user is located and the second big data related to the user, the method further includes: receiving a service demand instruction input by a user; or automatically generating a service demand instruction according to the historical data and the real-time data of the user.
In the embodiment of the invention, the scheme of the invention can be triggered and implemented based on two modes, 1) a user manually inputs a service demand instruction on intelligent terminal equipment, for example, the user can directly input an 'I offer car' on an offer car APP in advance, and at the moment, the platform can execute the information pushing method of the invention and push information to the user and a service provider at proper time; 2) The platform stores the historical data of the user, can also acquire the real-time data of the user, and can predict the service requirement of the user based on the historical data and the real-time data, thereby automatically executing the information pushing method of the invention. For example, when it is determined that the user arrives at the mall a on weekend days based on real-time data, it is determined that the user needs to be about the taxi with a high probability, and the method of the present invention may be automatically performed.
Optionally, the service demand instruction includes location data and time data; the acquiring the first big data related to the scene where the user is located and the second big data related to the user includes: determining location information according to the location data, and determining the first big data according to the location information and the time data; and determining the second big data according to the place information and the time data.
In the embodiment of the invention, the current place where the user is located can be determined based on the position data, such as a certain restaurant, a beauty parlor and the like, and accordingly, first big data corresponding to the place and time data, such as passenger flow data, average dining time length and the like of noon in the restaurant in the last month, can be called, wherein the first big data is used for representing the time length (such as waiting time length of the user) required by the place to provide service; on the other hand, for the second largest data related to the user, location information and time data may be determined. Therefore, the time spent by the user for receiving the service at the place can be analyzed from the two aspects of the place and the user, and the information pushing time can be determined later.
Optionally, the determining the second big data according to the location information and the time data includes: extracting place attribute information from the place information; and calling historical data of the user according to the place attribute information and the time data, and taking the historical data as the second big data.
In the embodiment of the invention, the second maximum data related to the user is obtained and determined comprehensively based on the location attribute information and the time data, namely, the historical data of the location with the same attribute and the same time as the user is called. By the arrangement, the acquired second big data can more accurately reflect the possible time consumption of the user in the current place.
Optionally, the determining the information pushing moment according to the first big data and the second big data includes:
determining a first duration according to the first big data, and determining a second duration according to the second big data; and determining a first time according to the first time and the second time, and determining the first time as the pushing time.
In the embodiment of the invention, after the first big data and the second big data are acquired, the first time length for the user to wait for the service at the place and the second time length for the user to accept the service can be determined based on the first big data, so that the user can be reminded of the proper time for pushing information, and in addition, the user can also push information to other service providers (such as the taxi) after confirmation.
Optionally, the determining the first time according to the first time length and the second time length includes: accumulating the first time length and the second time length to obtain a third time length, and determining a second time according to the time data; and determining a third moment according to the second moment and the adjusting time length, and taking the third moment as the first moment.
In the embodiment of the invention, the total time spent by the user in the place can be determined according to the first time spent by the user waiting for the service in the place and the second time spent by the user receiving the service, and the second time spent by the user leaving the place can be determined based on the time data of sending the service demand instruction; meanwhile, the user leaves the place to arrive at the designated place to receive the service of another service provider, and the other service provider arrives at the designated place to wait for providing the service for a certain time, so the invention sets the adjustment time length to push information in advance, thereby enabling the two services to be in seamless connection as much as possible.
Optionally, the adjustment duration is determined by: determining the number of peers according to the service demand instruction, and determining the familiarity of the user with the scene according to the historical data; determining the adjustment time length according to the number of the peers and the familiarity; the adjustment time length is positively correlated with the number of people in the same person and negatively correlated with the familiarity.
In the embodiment of the invention, the service demand instruction sent by the intelligent terminal equipment of the user also comprises the number of the same-party people, and the more the number of the same-party people is, the more uncertain the duration of the same-party people for receiving the service in the place is, namely the more inaccurate the second moment predicted by the method is, and the slower the advancing speed of the intelligent terminal equipment of the user is, the more uncertain the time for reaching the appointed place is, so the invention sets the adjusting duration to be positively related with the number of the same-party people, namely the more the number of the same-party people is, the more the time length is advanced to push the information. Meanwhile, the familiarity degree of the user and the scene can be determined based on the historical data of the user, for example, the more familiar the user is with a certain market, the greater the possibility that the user can arrive at a taxi pick-up and pick-off point on time, so that the setting adjustment time length is inversely related to the familiarity degree. The familiarity may be determined based on the number of times the user records in the scene, which is not described in detail herein.
Embodiment two: the embodiment of the invention also provides a structural schematic diagram of the intelligent information pushing system based on the big data. As shown in fig. 2, the intelligent information push system (100) based on big data comprises a processing module (101), a storage module (102) and a communication module (103), wherein the processing module (101) is respectively connected with the storage module (102) and the communication module (103); wherein, the liquid crystal display device comprises a liquid crystal display device,
-said memory module (102) for storing executable program code; the communication module (103) is used for acquiring first big data related to a scene where a user is located, second big data related to the user and executing the information pushing; the processing module (101) is configured to invoke the executable program code stored in the storage module (102) to perform the method according to the previous embodiment.
In this embodiment, the specific function of the intelligent information push system based on big data refers to the foregoing embodiment, and because the system in this embodiment adopts all the technical solutions of the foregoing embodiment, at least all the beneficial effects brought by the technical solutions of the foregoing embodiment are provided, and will not be described in detail herein.
Embodiment III: the embodiment of the invention also provides a computer device, referring to fig. 3, which may include a memory and a processor, where the memory stores a computer program, and when the processor invokes the computer program in the memory, the processor may implement the steps provided in the foregoing embodiment. Of course, the computer device may also include various network interfaces, power supplies, and the like.
Embodiment four: the embodiment of the present invention also provides a computer readable storage medium having a computer program stored thereon, which when executed can implement the steps provided in the above embodiment. The storage medium may include: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
In the description, each embodiment is described in a progressive manner, and each embodiment is mainly described by the differences from other embodiments, so that the same similar parts among the embodiments are mutually referred. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section. It should be noted that it would be obvious to those skilled in the art that various improvements and modifications can be made to the present application without departing from the principles of the present application, and such improvements and modifications fall within the scope of the claims of the present application.
It should also be noted that in this specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
Claims (10)
1. The intelligent information pushing method based on the big data is characterized by comprising the following steps: acquiring first big data related to a scene where a user is located and second big data related to the user; determining information pushing time according to the first big data and the second big data; and executing information pushing according to the information pushing moment.
2. The intelligent information pushing method based on big data according to claim 1, wherein the method comprises the following steps: before the first big data related to the scene where the user is located and the second big data related to the user are acquired, the method further comprises: receiving a service demand instruction input by a user; or automatically generating a service demand instruction according to the historical data and the real-time data of the user.
3. The intelligent information pushing method based on big data according to claim 2, wherein the method is characterized in that: the service demand instruction comprises position data and time data; the acquiring the first big data related to the scene where the user is located and the second big data related to the user includes: determining location information according to the location data, and determining the first big data according to the location information and the time data; and determining the second big data according to the place information and the time data.
4. The intelligent information pushing method based on big data according to claim 3, wherein the method comprises the following steps: the determining the second big data according to the location information and the time data includes: extracting place attribute information from the place information; and calling historical data of the user according to the place attribute information and the time data, and taking the historical data as the second big data.
5. The intelligent information pushing method based on big data according to claim 3 or 4, wherein the method comprises the following steps: the determining the information pushing moment according to the first big data and the second big data includes: determining a first duration according to the first big data, and determining a second duration according to the second big data; and determining a first time according to the first time and the second time, and determining the first time as the pushing time.
6. The intelligent information pushing method based on big data according to claim 5, wherein the method comprises the following steps: the determining a first time according to the first time and the second time includes: accumulating the first time length and the second time length to obtain a third time length, and determining a second time according to the time data; and determining a third moment according to the second moment and the adjusting time length, and taking the third moment as the first moment.
7. The intelligent information pushing method based on big data according to claim 6, wherein the method comprises the following steps: the adjustment time period is determined by the following method: determining the number of the same-person people according to the service demand instruction, and determining the familiarity of the user and the scene according to the historical data; determining the adjustment time length according to the number of the peers and the familiarity; the adjustment time length is positively correlated with the number of people in the same person and negatively correlated with the familiarity.
8. The intelligent information pushing system based on big data comprises a processing module, a storage module and a communication module, wherein the processing module is respectively connected with the storage module and the communication module; wherein the storage module is used for storing executable program codes; the communication module is used for acquiring first big data related to a scene where a user is located, second big data related to the user and executing the information pushing; the method is characterized in that: the processing module being adapted to invoke the executable program code stored in the memory module to perform the method according to any of claims 1-7.
9. A computer device comprising a memory and a processor, the memory having a computer program stored therein, the processor, when calling the computer program in the memory, being adapted to carry out the steps provided by the method according to any of claims 1-7.
10. A computer-readable storage medium having a computer program stored thereon, characterized by: which computer program, when being executed, is adapted to carry out the steps provided by the method according to any one of claims 1-7.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202310455068.8A CN116383368B (en) | 2023-04-25 | 2023-04-25 | Intelligent information pushing method and system based on big data |
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