Interactive multimedia wireless information issuing method and system

Abstract

The invention discloses an interactive multimedia wireless information issuing method and system, and relates to the technical field of data processing, and the method comprises the steps: obtaining a target information issuing queue and N interactive terminals; generating N interactive data sets; generating N deviation types and N deviation degrees, wherein the N deviation degrees are in one-to-one correspondence with the N deviation types; interaction node analysis is carried out based on the N interaction data sets, and N interaction node sequences are determined; according to the M pieces of to-be-released target information, the N deviation types, the N deviation degrees, the N interaction node sequences and the N interaction terminals, interaction release optimization is carried out, and N target information release schemes are obtained; and respectively transmitting the N target information publishing schemes to N interactive terminals for wireless information publishing. According to the method and the device, the technical problems of poor multimedia wireless information publishing effect and incapability of performing differentiated management in the prior art are solved, and the technical effects of improving the publishing efficiency and improving the information publishing quality are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to an interactive multimedia wireless information publishing method and system. Background Art

[0002] With the rapid increase in the amount of information, effective information release has become a focus of attention. However, the current single content push method and the unified management of information release and push have resulted in information push effects that cannot meet expectations. The existing technology has technical problems such as poor multimedia wireless information release effects and inability to perform differentiated management. Summary of the invention

[0003] The present application provides an interactive multimedia wireless information publishing method and system, which are used to solve the technical problems in the prior art that multimedia wireless information publishing effect is poor and differentiated management cannot be performed.

[0004] In view of the above problems, the present application provides an interactive multimedia wireless information publishing method and system.

[0005] In a first aspect of the present application, an interactive multimedia wireless information publishing method is provided, the method comprising: Acquire a target information publishing queue and N interactive terminals, wherein the target information publishing queue includes M target information to be published; Traversing the interaction data of N interactive terminals within a preset monitoring window to generate N interaction data sets; Based on N interaction data sets, bias analysis is performed on N interaction terminals to generate N bias types and N bias degrees, where the N bias degrees correspond one to one with the N bias types; Perform interaction node analysis based on N interaction data sets to determine N interaction node sequences; According to M target information to be released, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals, interactive release optimization is performed to obtain N target information release plans; N target information release schemes are transmitted to N interactive terminals respectively for wireless information release.

[0006] The second aspect of the present application provides an interactive multimedia wireless information publishing system, the system comprising: The terminal acquisition module is used to acquire a target information publishing queue and N interactive terminals, wherein the target information publishing queue includes M target information to be published; An interaction data set generation module, used to traverse the interaction data of N interaction terminals within a preset monitoring window to generate N interaction data sets; A bias generation module, used for performing bias analysis on N interactive terminals based on N interactive data sets, generating N bias types and N bias degrees, wherein the N bias degrees correspond to the N bias types one by one; A node sequence determination module, used to perform interaction node analysis based on N interaction data sets and determine N interaction node sequences; A publishing scheme obtaining module is used to optimize interactive publishing according to M target information to be published, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals, and obtain N target information publishing schemes; The wireless information publishing module is used to transmit N target information publishing schemes to N interactive terminals respectively for wireless information publishing.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages: The present application obtains a target information release queue and N interactive terminals, wherein the target information release queue includes M target information to be released, and then traverses the interactive data of the N interactive terminals in the preset monitoring window to generate N interactive data sets, and then performs bias analysis on the N interactive terminals based on the N interactive data sets, generates N bias types and N bias degrees, wherein the N bias degrees correspond to the N bias types one by one, performs interactive node analysis based on the N interactive data sets, determines N interactive node sequences, and then optimizes interactive release according to the M target information to be released, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals, obtains N target information release schemes, and then transmits the N target information release schemes to the N interactive terminals for wireless information release. The technical effect of improving the quality of wireless information release and improving the adaptability of released information and interactive terminals is achieved. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0009] Figure 1 A schematic diagram of a flow chart of an interactive multimedia wireless information publishing method provided in an embodiment of the present application; Figure 2 A schematic diagram of the structure of an interactive multimedia wireless information publishing system provided in an embodiment of the present application.

[0010] Explanation of reference numerals: terminal acquisition module 11 , interaction data set generation module 12 , deflection generation module 13 , node sequence determination module 14 , release plan acquisition module 15 , wireless information release module 16 . DETAILED DESCRIPTION

[0011] The present application provides an interactive multimedia wireless information publishing method and system to solve the technical problems in the prior art that multimedia wireless information publishing effect is poor and differentiated management cannot be performed.

[0012] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0013] It should be noted that the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or modules that are not explicitly listed or inherent to these processes, methods, products or devices. Embodiment 1

[0014] like Figure 1 As shown, the present application provides an interactive multimedia wireless information publishing method, wherein the method comprises: Acquire a target information publishing queue and N interactive terminals, wherein the target information publishing queue includes M target information to be published; In a possible embodiment, the target information release queue is a queue obtained by arranging multiple wireless information that need to be released for interactive multimedia information according to the release time. The N interactive terminals are multimedia wireless information release platforms, which can be station screens, elevator advertising screens, vehicle screens, etc. The target information release queue includes M target information to be released. The technical effect of obtaining the information that needs to be released and providing basic data for subsequent information release is achieved.

[0015] Traversing the interaction data of N interactive terminals within a preset monitoring window to generate N interaction data sets; Based on N interaction data sets, bias analysis is performed on N interaction terminals to generate N bias types and N bias degrees, where the N bias degrees correspond one to one with the N bias types; Furthermore, the method comprises: Extracting information types from N interaction data sets respectively to obtain N interaction information type sets, wherein each interaction information type has a frequency identifier; Traversing the N interaction information type sets, obtaining interaction types with a frequency greater than a preset interaction frequency, and adding them into the N bias types; The interaction frequencies corresponding to the N bias types are respectively divided by the total interaction frequencies of the corresponding N interaction information sets to generate N bias degrees.

[0016] In one embodiment, N interactive data sets are obtained by collecting interactive data of N interactive terminals in preset monitoring windows. The N interactive data sets include screen scan times, click times, etc. The N interactive data sets respectively reflect the data interaction situations of the N interactive terminals. The preset monitoring window is a monitoring time period preset by a person skilled in the art.

[0017] Preferably, the user interaction preferences of the N interactive terminals are analyzed according to the N interactive data sets to generate N preference types and N preference degrees. The N preference types are information data that the users of the N interactive terminals are more inclined to interact with. The N preference degrees describe the degree of user interaction of each preference type. The N preference degrees correspond one-to-one to the N preference types. In one possible embodiment, information type extraction is performed on N interaction data sets respectively to obtain N interaction information type sets, wherein each interaction information type has a frequency identifier, and the interaction information types include product push, news release, coupon issuance, and other types. Then, according to the frequency identifier, the interaction types in the N interaction information type sets whose frequency is greater than the preset interaction frequency are collected and added to the N bias types. Then, the interaction frequencies corresponding to the N bias types are respectively divided by the total interaction frequencies of the corresponding N interaction information sets to generate N bias degrees. Among them, the N bias degrees reflect the degree of bias of the information type.

[0018] Perform interaction node analysis based on N interaction data sets to determine N interaction node sequences; Furthermore, the method further comprises: Traversing the N interaction data sets to extract interaction time and generate N interaction time particle sets; Constructing N interaction spaces based on N interaction time particle sets, and dividing the N interaction spaces into N interaction subspace sets; Guided particles are determined for each of the N interaction subspace sets to generate N guide particle sets.

[0019] Furthermore, the method further comprises: Calculate the aggregation density of N guided particle sets to generate N guided aggregation density sets; Based on the analysis of N guide cluster density sets and preset interaction step lengths, N guide step length sets are generated; Based on N guide step sets, N interaction subspace sets are iteratively analyzed respectively to determine the particle points with the largest aggregation density in each interaction subspace set, and then screen and generate N first interaction node particles; N first interaction node particles are screened out from N interaction subspace sets to generate N first interaction subspace sets.

[0020] Furthermore, the method further comprises: Generating N second interaction node particles based on the N first interaction subspace sets and the N guide step length sets; After multiple iterations of analysis, N Pth interaction node particles are generated; N interaction node sequences are generated according to the N first interaction node particles, the N second interaction node particles and the N Pth interaction node particles respectively.

[0021] Furthermore, the method further comprises: The numbers of multiple guiding particles of N guiding particle sets within a preset interaction step are collected respectively to obtain N guiding particle aggregation amount sets; The peripheral particle intervals of the N guiding particle sets within the preset interaction step length are collected respectively to generate N guiding particle interval sets; The N guiding particle aggregation amount sets are respectively divided by the N guiding particle interval sets to generate N guiding aggregation density sets.

[0022] In a possible embodiment, the interaction nodes are time nodes corresponding to different interaction levels of users of the interaction terminal, and then the interaction nodes are sorted in descending order according to the interaction level, thereby obtaining N interaction node sequences. The N interaction node sequences can provide a basis for subsequent reliable information release.

[0023] Preferably, data extraction is performed on the interaction time of N interaction data sets to obtain N interaction time particle sets. Among them, the N interaction time particle sets reflect the interaction time distribution of N interaction terminals within a preset monitoring window. Then, N interaction spaces are constructed based on the N interaction time particle sets, and the N interaction spaces are divided into N interaction subspace sets according to a certain division scale by technicians in this field in an equal division manner. The division scale is set by those skilled in the art. Then, the mean center of the particle distribution of the N interaction subspace sets is obtained respectively, and it is determined as a guide particle determination, thereby generating N guide particle sets. The N guide particle sets reflect the particle distribution center of the N interaction subspaces of the N interaction terminals.

[0024] Optionally, N guiding aggregation density sets are generated by calculating the aggregation density of N guiding particle sets. The aggregation density reflects the density of other particles gathered around the particle. N guiding particle aggregation sets are obtained by respectively collecting the number of multiple guiding particles of the N guiding particle sets within the preset interaction step, and then respectively collecting the peripheral particle intervals of the N guiding particle sets within the preset interaction step to generate N guiding particle interval sets. By obtaining the peripheral particle interval, that is, the interval time of the outermost particles, the accuracy of the density analysis is improved. Then, the N guiding particle aggregation sets are respectively compared with the N guiding particle interval sets to generate N guiding aggregation density sets.

[0025] Preferably, N guiding step length sets are generated based on the multiplication of N guiding clustering density sets and preset interaction step lengths, wherein the preset interaction step length is a step length set by a person skilled in the art. Then, the N interaction subspace sets are iteratively analyzed based on the N guiding step length sets, the particle points with the largest clustering density in each interaction subspace set are determined, and N first interaction node particles are screened and generated. Then, the N first interaction node particles are screened out from the N interaction subspace sets to generate N first interaction subspace sets. This paves the way for the subsequent screening of densely distributed particles at the next level. Then, N second interaction node particles are generated based on the N first interaction subspace sets and the N guiding step length sets, and after multiple iterative analyses, N Pth interaction node particles are generated after reaching the preset number of iterations. N interaction node sequences are generated respectively according to the N first interaction node particles, the N second interaction node particles and the N Pth interaction node particles. The N first interaction node particles, the N second interaction node particles and the N Pth interaction node particles are arranged in order respectively to obtain N interaction node sequences.

[0026] According to M target information to be released, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals, interactive release optimization is performed to obtain N target information release plans; N target information release schemes are transmitted to N interactive terminals respectively for wireless information release.

[0027] Furthermore, the method further comprises: Acquire multiple target information to be released, multiple sample bias types, multiple sample bias degrees, multiple sample interaction node sequences, multiple sample interaction terminals, and multiple sample target information release schemes as training data; The training data is used to supervise the feedforward neural network layer, and the parameters of the network layer are updated according to the supervision results during the training process until the requirements are met, thereby obtaining a trained interactive publishing optimization network layer; N bias types, N bias degrees, N interactive node sequences, and N interactive terminals are transmitted to the interactive publishing optimization network layer for optimization analysis to obtain N target information publishing schemes.

[0028] In a possible embodiment, interactive publishing optimization is performed according to M target information to be published, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals to obtain N target information publishing schemes. Wherein, the N target information publishing schemes are schemes that clarify the order in which N interactive terminals publish information. Preferably, by obtaining multiple target information to be published, multiple sample bias types, multiple sample bias degrees, multiple sample interactive node sequences, multiple sample interactive terminals, and multiple sample target information publishing schemes as training data, and then using the training data to supervise the feedforward neural network layer, and updating the parameters of the network layer according to the supervision results during the training process until the requirements are met, a trained interactive publishing optimization network layer is obtained, and then, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals are transmitted to the interactive publishing optimization network layer for optimization analysis to obtain N target information publishing schemes. Then, the N target information publishing schemes are transmitted to the N interactive terminals for wireless information publishing.

[0029] In summary, the embodiments of the present application have at least the following technical effects: This application obtains the target information release queue and N interactive terminals, generates N interactive data sets, generates N bias types and N bias degrees, where the N bias degrees correspond to the N bias types one by one, then performs interactive node analysis based on the N interactive data sets, determines N interactive node sequences, optimizes interactive release according to M target information to be released, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals, obtains N target information release plans, and transmits the N target information release plans to N interactive terminals for wireless information release. The technical effect of improving release efficiency and improving information release quality is achieved. Embodiment 2

[0030] Based on the same inventive concept as the interactive multimedia wireless information publishing method in the aforementioned embodiment, Figure 2 As shown, the present application provides an interactive multimedia wireless information publishing system, and the system and method embodiments in the present application embodiments are based on the same inventive concept. The system includes: The terminal acquisition module 11 is used to acquire a target information publishing queue and N interactive terminals, wherein the target information publishing queue includes M target information to be published; An interaction data set generation module 12, used to traverse the interaction data of N interaction terminals within a preset monitoring window to generate N interaction data sets; A bias generation module 13, configured to perform bias analysis on N interactive terminals based on N interactive data sets, and generate N bias types and N bias degrees, wherein the N bias degrees correspond to the N bias types one by one; A node sequence determination module 14 is used to perform interaction node analysis based on N interaction data sets to determine N interaction node sequences; A publishing scheme obtaining module 15 is used to perform interactive publishing optimization according to M target information to be published, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals to obtain N target information publishing schemes; The wireless information publishing module 16 is used to transmit N target information publishing schemes to N interactive terminals respectively for wireless information publishing.

[0031] Furthermore, the system also includes: Extracting information types from N interaction data sets respectively to obtain N interaction information type sets, wherein each interaction information type has a frequency identifier; Traversing the N interaction information type sets, obtaining interaction types with a frequency greater than a preset interaction frequency, and adding them into the N bias types; The interaction frequencies corresponding to the N bias types are respectively divided by the total interaction frequencies of the corresponding N interaction information sets to generate N bias degrees.

[0032] Furthermore, the system also includes: Traversing the N interaction data sets to extract interaction time and generate N interaction time particle sets; Constructing N interaction spaces based on N interaction time particle sets, and dividing the N interaction spaces into N interaction subspace sets; Guided particles are determined for each of the N interaction subspace sets to generate N guide particle sets.

[0033] Furthermore, the system also includes: Calculate the aggregation density of N guided particle sets to generate N guided aggregation density sets; Based on the analysis of N guide cluster density sets and preset interaction step lengths, N guide step length sets are generated; Based on N guide step sets, N interaction subspace sets are iteratively analyzed respectively to determine the particle points with the largest aggregation density in each interaction subspace set, and then screen and generate N first interaction node particles; N first interaction node particles are screened out from N interaction subspace sets to generate N first interaction subspace sets.

[0034] Furthermore, the system also includes: Generating N second interaction node particles based on the N first interaction subspace sets and the N guide step length sets; After multiple iterations of analysis, N Pth interaction node particles are generated; N interaction node sequences are generated according to the N first interaction node particles, the N second interaction node particles and the N Pth interaction node particles respectively.

[0035] Furthermore, the system also includes: The numbers of multiple guiding particles of N guiding particle sets within a preset interaction step are collected respectively to obtain N guiding particle aggregation amount sets; The peripheral particle intervals of the N guiding particle sets within the preset interaction step length are collected respectively to generate N guiding particle interval sets; The N guiding particle aggregation amount sets are respectively divided by the N guiding particle interval sets to generate N guiding aggregation density sets.

[0036] Furthermore, the system also includes: Acquire multiple target information to be released, multiple sample bias types, multiple sample bias degrees, multiple sample interaction node sequences, multiple sample interaction terminals, and multiple sample target information release schemes as training data; The training data is used to supervise the feedforward neural network layer, and the parameters of the network layer are updated according to the supervision results during the training process until the requirements are met, thereby obtaining a trained interactive publishing optimization network layer; N bias types, N bias degrees, N interactive node sequences, and N interactive terminals are transmitted to the interactive publishing optimization network layer for optimization analysis to obtain N target information publishing schemes.

[0037] It should be noted that the above-mentioned sequence of the embodiments of the present application is only for description and does not represent the advantages and disadvantages of the embodiments. And the above-mentioned specific embodiments of this specification are described. Other embodiments are within the scope of the attached claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0038] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.

[0039] This specification and drawings are merely exemplary illustrations of the present application and are deemed to cover any and all modifications, variations, combinations or equivalents within the scope of the present application. Obviously, a person skilled in the art may make various modifications and variations to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalents, the present application intends to include these modifications and variations.

Claims

1. An interactive multimedia wireless information publishing method, characterized in that: The method comprises: Acquire a target information publishing queue and N interactive terminals, wherein the target information publishing queue includes M target information to be published; Traversing the interaction data of N interactive terminals within a preset monitoring window to generate N interaction data sets; Based on N interaction data sets, bias analysis is performed on N interaction terminals to generate N bias types and N bias degrees, where the N bias degrees correspond one to one with the N bias types; Perform interaction node analysis based on N interaction data sets to determine N interaction node sequences; According to M target information to be released, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals, interactive release optimization is performed to obtain N target information release plans; N target information release schemes are transmitted to N interactive terminals respectively for wireless information release.

2. The method according to claim 1, characterized in that The method comprises: Extracting information types from N interaction data sets respectively to obtain N interaction information type sets, wherein each interaction information type has a frequency identifier; Traversing the N interaction information type sets, obtaining interaction types with a frequency greater than a preset interaction frequency, and adding them into the N bias types; The interaction frequencies corresponding to the N bias types are respectively divided by the total interaction frequencies of the corresponding N interaction information sets to generate N bias degrees.

3. The method according to claim 1, characterized in that The method further comprises: Traversing the N interaction data sets to extract interaction time and generate N interaction time particle sets; Constructing N interaction spaces based on N interaction time particle sets, and dividing the N interaction spaces into N interaction subspace sets; Guided particles are determined for each of the N interaction subspace sets to generate N guide particle sets.

4. The method according to claim 3, characterized in that The method further comprises: Calculate the aggregation density of N guided particle sets to generate N guided aggregation density sets; Based on the analysis of N guide cluster density sets and preset interaction step lengths, N guide step length sets are generated; Based on N guide step sets, N interaction subspace sets are iteratively analyzed respectively to determine the particle points with the largest aggregation density in each interaction subspace set, and then screen and generate N first interaction node particles; N first interaction node particles are screened out from N interaction subspace sets to generate N first interaction subspace sets.

5. The method according to claim 4, characterized in that The method further comprises: Generating N second interaction node particles based on the N first interaction subspace sets and the N guide step length sets; After multiple iterations of analysis, N Pth interaction node particles are generated; N interaction node sequences are generated according to the N first interaction node particles, the N second interaction node particles and the N Pth interaction node particles respectively.

6. The method according to claim 5, characterized in that The method further comprises: The numbers of multiple guiding particles of N guiding particle sets within a preset interaction step are collected respectively to obtain N guiding particle aggregation amount sets; The peripheral particle intervals of the N guiding particle sets within the preset interaction step length are collected respectively to generate N guiding particle interval sets; The N guiding particle aggregation amount sets are respectively divided by the N guiding particle interval sets to generate N guiding aggregation density sets.

7. The method according to claim 1, characterized in that The method further comprises: Acquire multiple target information to be released, multiple sample bias types, multiple sample bias degrees, multiple sample interaction node sequences, multiple sample interaction terminals, and multiple sample target information release schemes as training data; The training data is used to supervise the feedforward neural network layer, and the parameters of the network layer are updated according to the supervision results during the training process until the requirements are met, thereby obtaining a trained interactive publishing optimization network layer; N bias types, N bias degrees, N interactive node sequences, and N interactive terminals are transmitted to the interactive publishing optimization network layer for optimization analysis to obtain N target information publishing schemes.

8. Interactive multimedia wireless information publishing system, characterized in that: The system comprises: The terminal acquisition module is used to acquire a target information publishing queue and N interactive terminals, wherein the target information publishing queue includes M target information to be published; An interaction data set generation module, used to traverse the interaction data of N interaction terminals within a preset monitoring window to generate N interaction data sets; A bias generation module, used for performing bias analysis on N interactive terminals based on N interactive data sets, generating N bias types and N bias degrees, wherein the N bias degrees correspond to the N bias types one by one; A node sequence determination module, used to perform interaction node analysis based on N interaction data sets and determine N interaction node sequences; A publishing scheme obtaining module is used to optimize interactive publishing according to M target information to be published, N bias types, N bias degrees, N interactive node sequences, and N interactive terminals, and obtain N target information publishing schemes; The wireless information publishing module is used to transmit N target information publishing schemes to N interactive terminals respectively for wireless information publishing.

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