CN115601081B - Online digital exhibition service management system based on big data analysis - Google Patents
Online digital exhibition service management system based on big data analysis Download PDFInfo
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Abstract
The invention relates to the technical field of on-line exhibition management, in particular to an on-line digital exhibition service management system based on big data analysis, which comprises an appointed on-line exhibition information acquisition module, a pre-exhibition product statistics module, a pre-exhibition product pre-exhibition propaganda analysis module, an effective exhibition product screening module, a service information base, an effective exhibition product actual observation parameter extraction module, an effective exhibition product key popularization user identification module and a key popularization user push content selection display module.
Description
Technical Field
The invention relates to the technical field of online exhibition management, in particular to an online digital exhibition service management system based on big data analysis.
Background
In the economic globalization and informatization age, the exhibition serves as an important platform for the establishment of the image of enterprises, the release of products and the interactive communication with spectators, and the exhibition is more and more valued by the enterprises. However, with the continuous development of the network economy form and the e-commerce economy, the original traditional offline exhibition cannot meet the current market demand, and the online exhibition is popular with enterprises by virtue of the advantages of no limitation of time and region, low construction cost and strong content expressive force. In this case, the number of online exhibition platforms and the number of days have increased dramatically, and the competition between online exhibition platforms has also increased.
In order to improve the competitiveness of online exhibition platforms, many online exhibition platforms begin to pay attention to the exhibition service quality of themselves, however, the exhibition service mode of the online exhibition platforms at present is a service using the exhibition users as a guide, namely, a vivid exhibition picture is created by applying various interaction technologies, so as to bring the visual experience of the visitors on the scene. The service effect that this kind of service mode can produce is the attention that improves the product of showing on the present exhibition, but the product attention influence that this kind of effect shows is temporary, after the exhibition finishes, if not keep, this kind of influence will disappear slowly, can't be for a long time. The final purpose of the on-line exhibition of the exhibition enterprises is to dig out the audience groups of the exhibited products through the on-line exhibition, so as to conduct targeted popularization, and the influence of the required product attention is long.
Therefore, the exhibition service mode of the online exhibition platform at present is lack of in-depth study on the online exhibition purpose of the exhibition enterprises, so that the service effect and the adaptation degree of the exhibition purpose are not high, larger use limit exists, the practical value is not high, and the development competition of the exhibition enterprises is not facilitated.
Disclosure of Invention
In order to solve the technical problems, the invention is realized by the following technical scheme: an on-line digital exhibition service management system based on big data analysis, comprising: the on-line exhibition information acquisition module is used for acquiring the theme name, the on-line propaganda duration and the exhibition duration corresponding to the on-line exhibition.
The pre-exhibition product statistics module is used for counting the number of pre-exhibition products prepared by a target exhibition enterprise for an appointed online exhibition, acquiring basic information corresponding to each pre-exhibition product and numbering each pre-exhibition product.
And the pre-exhibition product pre-exhibition propaganda analysis module is used for extracting propaganda attention parameters corresponding to each pre-exhibition product from the on-line exhibition platform after the pre-exhibition of the appointed on-line exhibition is finished, so as to analyze the propaganda attention degree corresponding to each pre-exhibition product.
And the effective showpiece screening module is used for screening out effective showpieces of target showpieces on the appointed online exhibition based on the propaganda attention degree corresponding to each pre-showpiece and the basic information and the theme name corresponding to the appointed online exhibition.
The service information base is used for storing the product category to which each product name provided by the target exhibition enterprise belongs, storing the attention effect factors corresponding to various watching behavior types and storing the effect influence factors corresponding to various interaction forms.
And the actual observation parameters of the effective exhibited products are extracted from the online exhibition platform after the specified online exhibition is held.
And the effective extension product key promotion user identification module is used for recording the numbers of the effective extension products, extracting propaganda attention parameters corresponding to each effective extension product according to the numbers, and identifying key promotion users corresponding to each effective extension product by combining the propaganda attention parameters with actual observation parameters, wherein the key promotion users comprise basic promotion users and advanced promotion users.
And the key popularization user push content selection display module is used for selecting push content of key popularization users corresponding to each effective exhibited product and displaying account numbers and push content of each key popularization user in a background mode.
The basic information includes the name and the price of the pre-sale, which is applied to the above embodiment.
The propaganda attention parameter comprises the number of the access users, account numbers, viewing time lengths and viewing behavior types corresponding to the access users.
The method is applied to the embodiment, and the analysis of the propaganda attention degree corresponding to each pre-exhibitions product comprises the following steps: and extracting the viewing behavior types corresponding to the access users from the propaganda attention parameters, and matching the viewing behavior types with attention effect factors corresponding to the various viewing behavior types stored in the service information base, so as to match the attention effect factors corresponding to the access users.
Extracting the number of access users and the viewing time length corresponding to each access user from the propaganda attention parameter, and analyzing the propaganda attention degree corresponding to each pre-exhibition product by combining attention effect factors corresponding to each access userThe analytical formula isWherein->Viewing duration of the j-th access user corresponding to the i-th pre-exhibition product, i being denoted as pre-exhibition product number,/->N is expressed as the number of pre-exhibitions products prepared by the target exhibitions enterprise for the designated online exhibition, j is expressed as the access user number, +.>，/>On-line propaganda duration of the exhibition on the designated line, +.>Attention effect factor expressed as the ith pre-exhibitions product corresponding to the jth access user,/->Representing the number of access users corresponding to the ith pre-exhibitions product.
The specific operation method for screening the effective exhibition products of the target exhibition enterprises on the appointed online exhibition is as follows: and extracting names from the basic information corresponding to each pre-exhibition product, and comparing the names with the product categories of the names of the products provided by the target exhibition enterprises stored in the service information base, thereby comparing the product categories of the pre-exhibition products.
And matching the theme names corresponding to the appointed online exhibition with the product categories related to the set various themes, and matching the product categories related to the appointed online exhibition theme.
Matching the product category of each pre-exhibition product with the product category related to the appointed online exhibition theme, and if the product category of a certain pre-exhibition product is consistent with the product category related to the appointed online exhibition theme, marking the theme matching degree corresponding to the pre-exhibition product asOtherwise, the theme matching degree corresponding to the pre-exhibition product is recorded as +.>。
Extracting the pre-selling price from the basic information corresponding to each pre-exhibitions product, and evaluating the exhibitions value index corresponding to each pre-exhibitions product by combining the topic matching degree and the propaganda attention degree corresponding to each pre-exhibitions productThe calculation formula is that，/>Indicated as the corresponding pre-sale price of the i < th > pre-exhibitions product,theme matching degree corresponding to i < th > pre-exhibitions product, <>The value of (2) is +.>Or->A is a set unit duty factor, and e is a natural constant.
And comparing the display value index corresponding to each preset display product with a preset effective display value index, and if the display value index corresponding to a certain preset display product is greater than or equal to the preset effective display value index, taking the preset display product as the effective display product, so that the effective display product of the target display enterprise on the appointed online exhibition is screened out.
The actual observation parameters applied to the embodiment include account numbers, observation duration and interaction heat corresponding to the observation users.
The analysis process corresponding to the interaction heat is applied to the embodiment, and the analysis process corresponding to the interaction heat refers to the steps of collecting the interaction frequency and the interaction form corresponding to each interaction of each observation user in the process of showing each effective showing product from the showing platform corresponding to the exhibition on the appointed line.
And matching the interaction form of each observing user corresponding to each interaction with the effect influence factors corresponding to the various interaction forms stored in the service information base, and matching the effect influence factors of each observing user corresponding to each interaction.
And carrying out average value calculation on the effect influence factors of each interaction in each observation user corresponding to each effective exhibited product to obtain the interaction heat corresponding to each observation user in each effective exhibited product.
The method for identifying key popularization users corresponding to each effective exhibited product specifically comprises the following steps of: and extracting account numbers corresponding to the access users from propaganda attention parameters corresponding to the effective showings, extracting account numbers corresponding to the showings from actual showings parameters corresponding to the effective showings, and matching the account numbers of the access users in the effective showings with the account numbers corresponding to the showings, so that access users failing to be matched are extracted from the access users corresponding to the effective showings and marked as candidate users.
According to account numbers corresponding to candidate users in each effective exhibited product, extracting watching duration and watching behavior types corresponding to each candidate user from propaganda attention parameters, and accordingly evaluating watching interestingness corresponding to each candidate user in each effective exhibited product, wherein an evaluation formula is as followsWherein->Expressed as the viewing interest level corresponding to the d candidate user in the kth valid showpiece, k expressed as the valid showpiece number,/->，/>Z is denoted as the number of active exhibitions and d is denoted as the number of candidate users,/->,/>Y is expressed as the number of candidate users,、/>and respectively representing the watching duration and the attention effect factor corresponding to the d candidate user in the k effective exhibited product.
And comparing the watching interest degree corresponding to each candidate user in each effective exhibited product with the set watching interest degree, and selecting candidate users with watching interest degrees greater than the watching interest degree in each effective exhibited product as basic popularization users.
From each ofExtracting the corresponding observation duration and interaction heat of each observation user from the actual observation parameters corresponding to the effective exhibited products, and accordingly evaluating the corresponding observation preference of each observation user in each effective exhibited product, wherein the evaluation formula is as followsWherein->Expressed as the viewing preference corresponding to the f-th viewing user in the kth effective exhibited product, f expressed as the number of the viewing user,/->X is expressed as the number of viewing users, +.>、/>Respectively expressed as the corresponding exhibition duration, interaction heat degree and the like of the f-th exhibition user in the k-th effective exhibition product>Representing the corresponding exhibition duration of the designated online exhibition, < +.>And the weighing factors are expressed as the weighing factors corresponding to the preset observing duration.
And comparing the corresponding observation preference degree of each candidate user in each effective exhibited product with the set required observation preference degree, and selecting the observation users with the observation preference degree larger than the required observation interest degree in each effective exhibited product as advanced popularization users.
The method is applied to the embodiment, and the specific execution of pushing content selection for the basic popularization users and the advanced popularization users corresponding to each effective exhibition product is as follows: (1) And after the exhibition is finished, on-line exhibition videos corresponding to each effective exhibition product are called from an exhibition platform corresponding to the appointed on-line exhibition, key segments are clipped to obtain key exhibition video segments corresponding to each effective exhibition product, purchase channels corresponding to each effective exhibition commodity are obtained, and then the key exhibition video segments corresponding to each effective exhibition product and the purchase channels are used as pushing contents of basic popularization users corresponding to each effective exhibition product.
(2) And taking the purchase channels corresponding to the effective showcases as push contents of advanced popularization users corresponding to the effective showcases.
The specific implementation mode of the key segment editing applied to the embodiment is as follows, the explanation segment and the interaction segment are extracted from the online exhibition video corresponding to each effective exhibition product, the explanation video and the interaction video corresponding to each effective exhibition product are obtained, and the explanation video and the interaction video are used as key exhibition video segments corresponding to each effective exhibition product.
Compared with the prior art, the invention has the following advantages: 1. according to the online exhibition platform, the online exhibition function is added, and accordingly important popularization users corresponding to the exhibited products are identified according to propaganda attention parameters and actual exhibition parameters of formal exhibition of the exhibited products in the online exhibition platform, the final purpose of online exhibition of the exhibited enterprises is achieved, the adaptation degree of the exhibition service effect of the online exhibition platform and the exhibition purpose is improved to a certain extent, the use limit of the existing online exhibition platform on exhibition service is effectively broken, the practical value of the online exhibition platform exhibition service is improved, and subsequent development competition of the exhibited enterprises is facilitated.
2. According to the invention, before the corresponding important popularization users of the exhibited products are identified, the effective exhibited products are screened out through the analysis of the propaganda attention parameters in the pre-exhibition propaganda based on each pre-exhibited product, so that the effective exhibited products are formally exhibited, and compared with the formal exhibition of all the pre-exhibited products, the screened effective exhibited products can maximally reduce the invalid exhibited rate, further strengthen the attention degree of the exhibited products, and enable the exhibited effect to be better.
3. According to the invention, in the key popularization user identification process, the pre-exhibition propaganda click user and the actual exhibition user of the effectively exhibited product are taken as candidate popularization people, the range of the candidate popularization people is greatly expanded, the omission of potential audiences is avoided to the maximum extent, and meanwhile, the key popularization users are classified into basic popularization users and advanced popularization users based on the distinction between the click user and the actual exhibition user, so that a more refined popularization mode is provided for subsequent product popularization, and further a powerful guarantee is provided for improving the popularization effect.
4. According to the method, after the key popularization users corresponding to the effectively exhibited products are identified, the corresponding push content is selected for different key popularization users, so that the targeted popularization of different key popularization users is realized, the push content meets the requirements of the users more, and the product conversion rate is improved.
Drawings
The invention will be further described with reference to the accompanying drawings, in which embodiments do not constitute any limitation of the invention, and other drawings can be obtained by one of ordinary skill in the art without inventive effort from the following drawings.
FIG. 1 is a schematic diagram of a system connection according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, the on-line digital exhibition service management system based on big data analysis is provided, which comprises an on-line exhibition information acquisition module, a pre-exhibition product statistics module, a pre-exhibition product exhibition front propaganda analysis module, an effective exhibition product screening module, a service information base, an effective exhibition product actual visiting parameter extraction module, an effective exhibition product key promotion user identification module and a key promotion user push content selection display module, wherein the pre-exhibition product statistics module is connected with the pre-exhibition product front propaganda analysis module, the on-line exhibition information acquisition module and the pre-exhibition product front propaganda analysis module are both connected with the effective exhibition product screening module, the effective exhibition product screening module is connected with the effective exhibition product actual visiting parameter extraction module, the pre-exhibition product front propaganda analysis module and the effective exhibition product actual visiting parameter extraction module are both connected with the effective exhibition product key promotion user identification module, and the promotion content selection display module are respectively connected with the pre-exhibition product actual exhibition product visiting parameter extraction module and the effective exhibition product actual exhibition parameter extraction module.
The appointed online exhibition information acquisition module is used for acquiring the theme name, the online propaganda duration and the exhibition duration corresponding to the appointed online exhibition.
The pre-exhibition product statistics module is used for counting the number of pre-exhibition products prepared by a target exhibition enterprise for an appointed online exhibition, and acquiring basic information corresponding to each pre-exhibition product, and numbering each pre-exhibition product, wherein the basic information comprises names and pre-sale prices.
The pre-exhibition product pre-exhibition propaganda analysis module is used for extracting propaganda attention parameters corresponding to each pre-exhibition product from the on-line exhibition platform after the pre-exhibition of the specified on-line exhibition is ended, wherein the propaganda attention parameters comprise the number of access users, account numbers, watching time lengths and watching behavior types corresponding to each access user, so that the propaganda attention degree corresponding to each pre-exhibition product is analyzed, and the method specifically comprises the following steps of: and extracting the viewing behavior types corresponding to the access users from the propaganda attention parameters, and matching the viewing behavior types with attention effect factors corresponding to the various viewing behavior types stored in the service information base, so as to match the attention effect factors corresponding to the access users.
It should be noted that the above-mentioned viewing behavior types include, but are not limited to, praise, collection, forwarding.
Extracting the number of access users from the propaganda attention parameters and the corresponding watching time length of each access user, combining the access users with each accessAsking the user to analyze the corresponding propaganda attention degree of each pre-exhibition product by the corresponding attention effect factorsThe analysis formula is that,wherein->Viewing duration of the j-th access user corresponding to the i-th pre-exhibition product, i being denoted as pre-exhibition product number,/->N is expressed as the number of pre-exhibitions products prepared by the target exhibitions enterprise for the designated online exhibition, j is expressed as the access user number, +.>，/>On-line propaganda duration of the exhibition on the designated line, +.>Attention effect factor expressed as the ith pre-exhibitions product corresponding to the jth access user,/->Representing the number of access users corresponding to the ith pre-exhibitions product.
In the propaganda attention degree calculation formula, the number of access users, the access time length and the attention effect corresponding to the pre-exhibited product have positive influence on the propaganda attention degree.
The effective showpiece screening module is used for screening out effective showpieces of target showpieces on an appointed online exhibition based on propaganda attention degree corresponding to each pre-showpiece, basic information and theme names corresponding to the appointed online exhibition, and the specific operation method is as follows: and extracting names from the basic information corresponding to each pre-exhibition product, and comparing the names with the product categories of the names of the products provided by the target exhibition enterprises stored in the service information base, thereby comparing the product categories of the pre-exhibition products.
And matching the theme names corresponding to the appointed online exhibition with the product categories related to the set various themes, and matching the product categories related to the appointed online exhibition theme.
Matching the product category of each pre-exhibition product with the product category related to the appointed online exhibition theme, and if the product category of a certain pre-exhibition product is consistent with the product category related to the appointed online exhibition theme, marking the theme matching degree corresponding to the pre-exhibition product asOtherwise, the theme matching degree corresponding to the pre-exhibition product is recorded as +.>Exemplary, <' > A->The value of (1),>the value of (2) is 0.
As an example, the theme name corresponding to the exhibition on the above specified line is an intelligent home, and the product category related to the intelligent home includes an intelligent sound box, an intelligent air conditioner, an intelligent door lock, an intelligent sweeping robot, and the like.
Extracting the pre-selling price from the basic information corresponding to each pre-exhibitions product, and evaluating the exhibitions value index corresponding to each pre-exhibitions product by combining the topic matching degree and the propaganda attention degree corresponding to each pre-exhibitions productThe calculation formula is that，/>Indicated as the corresponding pre-sale price of the i < th > pre-exhibitions product,theme matching degree corresponding to i < th > pre-exhibitions product, <>The value of (2) is +.>Or->A is a set unit duty factor, and e is a natural constant.
And comparing the display value index corresponding to each preset display product with a preset effective display value index, and if the display value index corresponding to a certain preset display product is greater than or equal to the preset effective display value index, taking the preset display product as the effective display product, so that the effective display product of the target display enterprise on the appointed online exhibition is screened out.
According to the invention, before the corresponding important popularization users of the exhibited products are identified, the effective exhibited products are screened out through the analysis of the propaganda attention parameters in the pre-exhibition propaganda based on each pre-exhibited product, so that the effective exhibited products are formally exhibited, and compared with the formal exhibition of all the pre-exhibited products, the screened effective exhibited products can maximally reduce the invalid exhibited rate, further strengthen the attention degree of the exhibited products, and enable the exhibited effect to be better.
The service information base is used for storing product categories to which each product name provided by a target exhibition enterprise belongs, storing attention effect factors corresponding to various watching behavior types and storing effect influence factors corresponding to various interaction forms.
The actual observation parameters of the effective exhibition products are extracted from an online exhibition platform after the online exhibition is held, wherein the actual observation parameters comprise account numbers, observation duration and interaction heat corresponding to each observation user.
It should be noted that the above mentioned interaction forms include barrages, questions, brushing gifts, etc.
And matching the interaction form of each observing user corresponding to each interaction with the effect influence factors corresponding to the various interaction forms stored in the service information base, and matching the effect influence factors of each observing user corresponding to each interaction.
And carrying out average value calculation on the effect influence factors of each interaction in each observation user corresponding to each effective exhibited product to obtain the interaction heat corresponding to each observation user in each effective exhibited product.
The effective showpiece product key promotion user identification module is used for recording the numbers of the effective showpiece products, extracting propaganda attention parameters corresponding to each effective showpiece product according to the numbers, and identifying key promotion users corresponding to each effective showpiece product by combining actual showpiece parameters, wherein the key promotion users comprise basic promotion users and advanced promotion users, and the key promotion users specifically comprise the following steps: and extracting account numbers corresponding to the access users from propaganda attention parameters corresponding to the effective showings, extracting account numbers corresponding to the showings from actual showings parameters corresponding to the effective showings, and matching the account numbers of the access users in the effective showings with the account numbers corresponding to the showings, so that access users failing to be matched are extracted from the access users corresponding to the effective showings and marked as candidate users.
According to account numbers corresponding to candidate users in each effective exhibited product, extracting watching duration and watching behavior types corresponding to each candidate user from propaganda attention parameters, and accordingly evaluating watching interestingness corresponding to each candidate user in each effective exhibited product, wherein an evaluation formula is as followsWherein->Expressed as the viewing interest level corresponding to the d candidate user in the kth valid showpiece, k expressed as the valid showpiece number,/->，/>Z is denoted as the number of active exhibitions and d is denoted as the number of candidate users,/->,/>Y is expressed as the number of candidate users, +.>、/>And respectively representing the watching duration and the attention effect factor corresponding to the d candidate user in the k effective exhibited product.
And comparing the watching interest degree corresponding to each candidate user in each effective exhibited product with the set watching interest degree, and selecting candidate users with watching interest degrees greater than the watching interest degree in each effective exhibited product as basic popularization users.
The above-mentioned basic popularization users refer to that access behaviors exist in the process of publicizing before exhibition and watching interests are large, but watching is not performed in the process of formal exhibition, and the users may miss the observation due to the fact that the formal exhibition time is not caught up or other objective reasons, and if the users are ignored, some potential audiences are lost.
Extracting the corresponding observation time length and interaction heat of each observation user from the actual observation parameters corresponding to each effective observation product, and evaluating the corresponding observation time length and interaction heat of each observation user in each effective observation productThe evaluation formula of the preference degree is thatWherein->Expressed as the viewing preference corresponding to the f-th viewing user in the kth effective exhibited product, f expressed as the number of the viewing user,/->X is expressed as the number of viewing users, +.>、/>Respectively expressed as the corresponding exhibition duration, interaction heat degree and the like of the f-th exhibition user in the k-th effective exhibition product>Representing the corresponding exhibition duration of the designated online exhibition, < +.>And the weighing factors are expressed as the weighing factors corresponding to the preset observing duration.
And comparing the corresponding observation preference degree of each candidate user in each effective exhibited product with the set required observation preference degree, and selecting the observation users with the observation preference degree larger than the required observation interest degree in each effective exhibited product as advanced popularization users.
According to the invention, in the key popularization user identification process, the pre-exhibition propaganda click user and the actual exhibition user of the effectively exhibited product are taken as candidate popularization people, the range of the candidate popularization people is greatly expanded, the omission of potential audiences is avoided to the maximum extent, and meanwhile, the key popularization users are classified into basic popularization users and advanced popularization users based on the distinction between the click user and the actual exhibition user, so that a more refined popularization mode is provided for subsequent product popularization, and further a powerful guarantee is provided for improving the popularization effect.
The key popularization user push content selection display module is used for selecting push content of key popularization users corresponding to each effective exhibited product, and displaying account numbers and push content of each key popularization user in a background mode, and specifically comprises the following steps: (1) And after the exhibition is finished, on-line exhibition videos corresponding to each effective exhibition product are called from an exhibition platform corresponding to the appointed on-line exhibition, key segments are clipped to obtain key exhibition video segments corresponding to each effective exhibition product, purchase channels corresponding to each effective exhibition commodity are obtained, and then the key exhibition video segments corresponding to each effective exhibition product and the purchase channels are used as pushing contents of basic popularization users corresponding to each effective exhibition product.
The specific implementation mode of the middle key segment editing is as follows, the explanation segment and the interaction segment are extracted from the online exhibition videos corresponding to the effective exhibition products, the explanation videos and the interaction videos corresponding to the effective exhibition products are obtained, and the explanation videos and the interaction videos are used as key exhibition video segments corresponding to the effective exhibition products.
(2) And taking the purchase channels corresponding to the effective showcases as push contents of advanced popularization users corresponding to the effective showcases.
According to the method, after the key popularization users corresponding to the effectively exhibited products are identified, the corresponding push content is selected for different key popularization users, so that the targeted popularization of different key popularization users is realized, the push content meets the requirements of the users more, and the product conversion rate is improved.
According to the online exhibition platform, the online exhibition function is added, and accordingly important popularization users corresponding to the exhibited products are identified according to propaganda attention parameters and actual exhibition parameters of formal exhibition of the exhibited products in the online exhibition platform, the final purpose of online exhibition of the exhibited enterprises is achieved, the adaptation degree of the exhibition service effect of the online exhibition platform and the exhibition purpose is improved to a certain extent, the use limit of the existing online exhibition platform on exhibition service is effectively broken, the practical value of the online exhibition platform exhibition service is improved, and subsequent development competition of the exhibited enterprises is facilitated.
The foregoing is merely illustrative of the structures of this invention and various modifications, additions and substitutions for those skilled in the art can be made to the described embodiments without departing from the scope of the invention or from the scope of the invention as defined in the accompanying claims.
Claims (8)
1. On-line digital exhibition service management system based on big data analysis, which is characterized by comprising:
the on-line exhibition information acquisition module is used for acquiring the theme name, the on-line propaganda duration and the exhibition duration corresponding to the on-line exhibition;
the pre-exhibition product statistics module is used for counting the number of pre-exhibition products prepared by a target exhibition enterprise for an appointed online exhibition, acquiring basic information corresponding to each pre-exhibition product and numbering each pre-exhibition product;
the pre-exhibition product pre-exhibition propaganda analysis module is used for extracting propaganda attention parameters corresponding to each pre-exhibition product from the on-line exhibition platform after the pre-exhibition of the specified on-line exhibition is finished, so as to analyze the propaganda attention degree corresponding to each pre-exhibition product;
the effective showpiece screening module is used for screening out effective showpieces of target showpieces on the appointed online exhibition based on the propaganda attention degree corresponding to each pre-showpiece, the basic information and the theme name corresponding to the appointed online exhibition;
the service information base is used for storing product categories to which each product name provided by a target exhibition enterprise belongs, storing attention effect factors corresponding to various watching behavior types and storing effect influence factors corresponding to various interaction forms;
the device comprises an effective exhibition product actual observation parameter extraction module, a real observation parameter extraction module and a real observation parameter extraction module, wherein the effective exhibition product actual observation parameter extraction module is used for extracting actual observation parameters corresponding to each effective exhibition product from an online exhibition platform after the on-line exhibition is held;
the effective extension product key promotion user identification module is used for recording the numbers of the effective extension products, extracting propaganda attention parameters corresponding to each effective extension product according to the numbers, and identifying key promotion users corresponding to each effective extension product by combining the propaganda attention parameters with actual observation parameters, wherein the key promotion users comprise basic promotion users and advanced promotion users;
the key popularization user push content selection display module is used for selecting push content of key popularization users corresponding to each effective exhibited product and displaying account numbers and push content of each key popularization user in a background mode;
the analysis of the propaganda attention degree corresponding to each pre-exhibition product comprises the following steps:
extracting the watching behavior types corresponding to each access user from the propaganda focusing parameters, matching the watching behavior types with focusing effect factors corresponding to various watching behavior types stored in a service information base, and matching the focusing effect factors corresponding to each access user;
extracting the number of access users and the viewing time length corresponding to each access user from the propaganda attention parameter, and analyzing the propaganda attention degree corresponding to each pre-exhibition product by combining attention effect factors corresponding to each access userThe analytical formula isWherein->Viewing duration of the j-th access user corresponding to the i-th pre-exhibition product, i being denoted as pre-exhibition product number,/->N is expressed as the number of pre-exhibitions products prepared by the target exhibitions enterprise for the designated online exhibition, j is expressed as the access user number, +.>，/>On-line propaganda duration of the exhibition on the designated line, +.>Attention effect factor expressed as the ith pre-exhibitions product corresponding to the jth access user,/->Representing the number of access users corresponding to the ith pre-exhibition product;
the specific operation method for screening the effective exhibition products of the target exhibition enterprises on the appointed online exhibition is as follows:
extracting names from basic information corresponding to each pre-exhibition product, and comparing the names with product categories to which each product name provided by a target exhibition enterprise stored in a service information base belongs, thereby comparing the product categories to which each pre-exhibition product belongs;
matching the theme names corresponding to the appointed online exhibition with the product categories related to the set various themes, and matching the product categories related to the appointed online exhibition themes;
matching the product category of each pre-exhibition product with the product category related to the appointed online exhibition theme, and if the product category of a certain pre-exhibition product is consistent with the product category related to the appointed online exhibition theme, marking the theme matching degree corresponding to the pre-exhibition product asOtherwise, the theme matching degree corresponding to the pre-exhibition product is recorded as +.>；
Extracting the pre-selling price from the basic information corresponding to each pre-exhibitions product, and evaluating the exhibitions value index corresponding to each pre-exhibitions product by combining the topic matching degree and the propaganda attention degree corresponding to each pre-exhibitions productThe calculation formula is that，/>Indicated as the corresponding pre-sale price of the i < th > pre-exhibitions product,theme matching degree corresponding to i < th > pre-exhibitions product, <>The value of (2) is +.>Or->A is expressed as a set unit duty factor, and e is expressed as a natural constant;
and comparing the display value index corresponding to each preset display product with a preset effective display value index, and if the display value index corresponding to a certain preset display product is greater than or equal to the preset effective display value index, taking the preset display product as the effective display product, so that the effective display product of the target display enterprise on the appointed online exhibition is screened out.
2. The online digital exhibition service management system based on big data analysis of claim 1, wherein: the basic information includes a name and a pre-sale price.
3. The online digital exhibition service management system based on big data analysis of claim 2, wherein: the propaganda attention parameters comprise the number of access users, account numbers corresponding to the access users, viewing duration and viewing behavior types.
4. The online digital exhibition service management system based on big data analysis of claim 1, wherein: the actual viewing parameters comprise account numbers, viewing duration and interaction heat corresponding to each viewing user.
5. The online digital exhibition service management system based on big data analysis of claim 4, wherein: the analysis process corresponding to the interaction heat is as follows:
collecting interaction frequency corresponding to each observation user and interaction form corresponding to each interaction in the process of the exhibition of each effective exhibited product from the exhibition platform corresponding to the exhibition on the appointed line;
matching the interaction forms of the interactions of the observation users with the effect influence factors corresponding to the interactions of the observation users, wherein the effect influence factors correspond to the interactions of the observation users;
and carrying out average value calculation on the effect influence factors of each interaction in each observation user corresponding to each effective exhibited product to obtain the interaction heat corresponding to each observation user in each effective exhibited product.
6. The online digital exhibition service management system based on big data analysis of claim 4, wherein: the key popularization users corresponding to the effective exhibited products are identified, and the method specifically comprises the following steps:
extracting account numbers corresponding to all access users from propaganda attention parameters corresponding to all effective showcases, extracting account numbers corresponding to all the showcases from actual showcases parameters corresponding to all the effective showcases, and matching the account numbers of all the access users in all the effective showcases with the account numbers corresponding to all the showcases, so that access users failing to match are extracted from the access users corresponding to all the effective showcases, and marked as candidate users;
extracting each candidate user from the propaganda attention parameters according to the account numbers corresponding to each candidate user in each effective exhibited productCorresponding watching duration and watching behavior types, and accordingly evaluating the watching interestingness corresponding to each candidate user in each effective exhibited product, wherein the evaluation formula is as followsWherein->Expressed as the viewing interest level corresponding to the d candidate user in the kth valid showpiece, k expressed as the valid showpiece number,/->，/>Z is denoted as the number of active exhibitions and d is denoted as the number of candidate users,/->,/>Y is expressed as the number of candidate users, +.>、Respectively representing the watching duration and the attention effect factor corresponding to the d candidate user in the k effective exhibited products;
comparing the watching interest degree corresponding to each candidate user in each effective exhibited product with the set watching interest degree, and selecting candidate users with watching interest degrees greater than the watching interest degree in each effective exhibited product as basic popularization users;
extracting the corresponding observation duration and interaction heat of each observation user from the actual observation parameters corresponding to each effective observation product, and evaluating the corresponding observation bias of each observation user in each effective observation product according to the observation duration and interaction heatThe evaluation formula of the quality is thatWherein->Expressed as the viewing preference corresponding to the f-th viewing user in the kth effective exhibited product, f expressed as the number of the viewing user,/->X is expressed as the number of viewing users, +.>、/>Respectively expressed as the corresponding exhibition duration, interaction heat degree and the like of the f-th exhibition user in the k-th effective exhibition product>Representing the corresponding exhibition duration of the designated online exhibition, < +.>The weighing factors are expressed as the weighing factors corresponding to the preset observing duration;
and comparing the corresponding observation preference degree of each candidate user in each effective exhibited product with the set required observation preference degree, and selecting the observation users with the observation preference degree larger than the required observation interest degree in each effective exhibited product as advanced popularization users.
7. The online digital exhibition service management system based on big data analysis of claim 6, wherein: the pushing content selection is respectively carried out on the basic popularization users and the advanced popularization users corresponding to each effective exhibited product, and the specific implementation is as follows:
(1) After the exhibition is finished, on-line exhibition videos corresponding to each effective exhibition product are called from an exhibition platform corresponding to the appointed on-line exhibition, key segments are clipped to obtain key exhibition video segments corresponding to each effective exhibition product, purchase channels corresponding to each effective exhibition commodity are obtained, and the key exhibition video segments and the purchase channels corresponding to each effective exhibition product are used as pushing contents of basic popularization users corresponding to each effective exhibition product;
(2) And taking the purchase channels corresponding to the effective showcases as push contents of advanced popularization users corresponding to the effective showcases.
8. The online digital exhibition service management system based on big data analysis of claim 7, wherein: the specific implementation mode of the key fragment clip is as follows:
and extracting explanation fragments and interaction fragments from online exhibition videos corresponding to the effective exhibition products to obtain the explanation videos and interaction videos corresponding to the effective exhibition products, and taking the explanation videos and interaction videos as key exhibition video segments corresponding to the effective exhibition products.
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