CN117135380A - Travel product live broadcast marketing system based on AIGC technology - Google Patents
Travel product live broadcast marketing system based on AIGC technology Download PDFInfo
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Abstract
The invention provides an AIGC technology-based live broadcast marketing system for a travel product, which comprises an analysis module, a live broadcast content generation module, a live broadcast interface, an interaction module, a audience information collection module and a database, wherein the analysis module is used for analyzing the live broadcast content; the analysis module is used for analyzing preference products of audience in the living broadcast room and stock travel products to obtain movable marketing sequences of the travel products in the living broadcast room; the live broadcast content generation module comprises a live broadcast document generation unit, wherein the live broadcast document generation unit is used for generating a marketing document of a travel product which needs to be marketed in the live broadcast based on an AIGC learning model and the movable marketing sequence. According to the method, the temporary marketing sequence is obtained through calculation, the related live broadcast content is generated through the AIGC technology, and the temporary marketing sequence is replaced through the movable marketing sequence generated in real time, so that the live broadcast content is more matched with the preference degree of viewers in a live broadcast room, the marketing effect of live broadcast marketing is improved, and the manpower resource consumption is reduced.
Description
Technical Field
The invention relates to the field of live broadcast marketing, in particular to an AIGC technology-based live broadcast marketing system for travel products.
Background
Live marketing refers to a marketing mode of simultaneously making and broadcasting programs along with the occurrence and development processes of events on site, and the marketing activity takes a live platform as a carrier so as to achieve the purposes of improving brands or increasing sales volume of enterprises.
The prior art of CN115760277a discloses an electronic commerce marketing system based on live broadcast technology, which comprises a live broadcast system and a marketing system, wherein the live broadcast system is connected with a platform server, the marketing system is directly connected with factory sales, the factory sales obtains commodity demands counted in the marketing system to carry out commodity allocation, the commodity allocation comprises logistics transportation and production processing, commodity associated video delivery comprises commodity evaluation and advertisement announcement, commodity sales links comprise commodity propaganda links and commodity information recommendation links, and final data of the commodity sales links are integrated by commodity information records.
Another exemplary network marketing video live broadcast display system disclosed in the prior art of CN109194963a includes an image acquisition module with image capturing, a video processing module capable of performing compression and decompression in real time, a PC end display module for presenting a live video picture, a sound input module with sound effects, a sound module for performing digital analysis processing on audio, an earphone output module for listening to audio signals, an indication module for real-time display status of an LED lamp, and a control module using a single-chip microcomputer as a processing core.
Looking again at a system and method for e-commerce and delivering related products as disclosed in the prior art of US20020019978 A1. The system and method provide for the delivery of auxiliary content to a user via a computer network in relation to video by synchronizing the auxiliary content with the video. And provides a user database and a business database for determining in real-time auxiliary information to be displayed for individual users of the system.
The current live marketing is generally carried out by a host in a live broadcasting room according to a written live broadcasting manuscript, the live broadcasting marketing mode consumes large manpower, marketing products and marketing strategies are relatively fixed, and the marketing products and the marketing strategies cannot be changed in time according to the preference of users in the live broadcasting room, so that the invention aims to solve the common problems in the field.
Disclosure of Invention
The invention aims to provide an AIGC technology-based living broadcast marketing system for a travel product, aiming at the defects existing at present.
In order to overcome the defects in the prior art, the invention adopts the following technical scheme:
a travel product live broadcast marketing system based on AIGC technology comprises an analysis module, a live broadcast content generation module, a live broadcast interface, an interaction module, a audience information collection module and a database; the analysis module is used for analyzing preference products of audience in the living broadcast room and stock travel products to obtain movable marketing sequences of the travel products in the living broadcast room; the live broadcast content generation module comprises a live broadcast document generation unit, a live broadcast video generation unit and a live broadcast voice generation unit, wherein the live broadcast document generation unit is used for generating a marketing document of a travel product which needs to be marketed at the time of live broadcast based on an AIGC learning model and the movable marketing sequence, the live broadcast video generation unit is used for generating a marketing video according to the marketing document and pictures of the marketing product, and the live broadcast voice generation unit is used for generating a marketing video containing AI dubbing for the marketing video according to the marketing document; the live broadcast interface is used for displaying the interaction module and the marketing video of the AI dubbing; the interaction module is used for realizing a man-machine interaction function; the audience information collection module is used for collecting relevant shopping information of the audience in the current live broadcasting room; the database is used for storing the related information of the travel products and marketing records of each living broadcast room.
Further, the analysis module comprises an information searching unit, an analysis unit and a comparison unit; the information searching unit is used for extracting information from the database; the analysis unit is used for analyzing preference products of audience in the living broadcast room and travel products suitable for marketing in the living broadcast; the comparison unit is used for executing a data comparison function.
Still further, the analysis unit includes a tentative marketing sequence generation unit, a preference product analysis unit, a movable marketing sequence generation unit, and a parameter adjustment unit, where the tentative marketing sequence generation unit is configured to generate a tentative marketing sequence; the preference product analysis unit is used for analyzing preference products of audience in the living broadcasting room; the movable marketing sequence generating unit is used for generating a movable marketing sequence; the parameter adjusting unit is used for adjusting each parameter in the analysis unit.
Further, the live marketing system of the travel product comprises the following working steps:
s1, the information searching unit extracts the online marketing, offline marketing and past marketing conditions of the living broadcast room of all inventory travel products from a database, wherein the online marketing is the online past marketing outside the living broadcast room;
s2, the analysis unit selects the tentative marketing products of the live broadcast from the inventory travel products according to the search result of the information search unit and generates a tentative marketing sequence;
s3, the live content generation module generates a plurality of segments of marketing videos according to the tentative marketing sequence and combines the segments of marketing videos into a live video;
s4, starting live broadcasting and playing live broadcasting video, wherein the audience information collection module collects past browsing information and past purchasing information of audience in a live broadcasting room in real time;
s5, the analysis unit analyzes preference products of the current live broadcasting room audience according to the content collected by the audience information collection module;
s6, the analysis unit generates a movable marketing sequence according to the preferred products and sends the movable marketing sequence to the live broadcast content generation module;
and S7, the live content generation module generates a new live video according to the movable marketing sequence, and plays the new live video after the current marketing video is finished.
Further, the analyzing unit selects the tentative marketing product of the live broadcast and generates the tentative marketing sequence includes the steps of:
s21, the analysis unit analyzes the information extracted from the database by the information search unit, and generates favorite values of each inventory travel product according to the following formula:
；
wherein,is a favorites value for category A inventory travel products,/->Is the offline marketing weight coefficient of inventory travel products of category A, +.>Is the on-line marketing weight coefficient of inventory travel products of class A outside the local living broadcast room, </i >>Is the local living broadcast room marketing weight coefficient of inventory travel products of category A, and +.>Is the off-line total sales of inventory travel products of category a,inventory travel product of category A is marketing total sales outside the local living room on line, < >>Is the rate of departure of category A inventory travel products in online marketing outside the local living room, +.>The total sales of the inventory travel products of the category A in the ith live broadcast of the live broadcast room are obtained, and N is the total live broadcast times of the inventory travel products of the category A in the live broadcast room after the live broadcast; />Is the total sales of inventory travel products of category A in all live broadcast of the live broadcast room, and TIME is the total live broadcast TIMEs of the live broadcast room, and +.>Is the number of out-stops of stock travel products of category A in the local living broadcast room,/the user is allowed to select->Is the total number of audience in the living broadcast room in the ith living broadcast of the stock travel product of the living broadcast room type A, and the audience is added>Is the number of times the audience clicks 'buy' the inventory travel products belonging to the category A in the ith live broadcast of the inventory travel products of the category A in the live broadcast room, and +.>The number of times that the audience in the live broadcasting room clicks the inventory travel products belonging to the category A to be added into the shopping cart in the ith live broadcasting of the inventory travel products of the category A in the live broadcasting room;
s22, ranking the travel products of all kinds according to the favorite values;
s23, according to the number X of types of the travel products required to be marketed by the live broadcast, selecting the top X inventory travel products with the favorite value ranking from high to low as temporary marketing products of the live broadcast, and selecting the unselected inventory travel products as candidate marketing products, and generating a temporary marketing sequence of the temporary marketing products according to the favorite value ranking from high to low based on the temporary marketing products.
Still further, the analyzing unit analyzes preference products of the current live broadcasting room audience according to the content collected by the audience information collecting module, comprising the following steps:
s51, acquiring the purchase quantity and the label of various travel products purchased by the audience of the current living broadcast room through a living broadcast or shopping website in 5 years;
s52, sorting various travel products purchased by the audience of the current living broadcast room through the living broadcast or shopping website in 5 years according to the order of the purchase quantity from more to less, wherein the more the purchase quantity of the travel products, the earlier the sorting is;
s53, taking the ordered first Y travel products as preference products of the audience in the current living broadcast room, obtaining a sequence SEQ of the preference products, wherein Y is the category number of candidate marketing products of the current living broadcast.
Still further, the analysis unit generating the movable marketing sequence from the preferred product comprises the steps of:
s61, calculating the similarity value of each preference product and candidate marketing products;
s62, sending the similar value to a comparison unit, comparing the similar value with a set threshold value by the comparison unit, and returning a comparison result;
s63, the comparison unit judges whether the similarity value of each preferred product and the candidate marketing products is larger than a set threshold value, if the similarity value of the current preferred product is larger than the set threshold value, the current preferred product is a qualified preferred product, otherwise, the current preferred product is a disqualified preferred product;
s64, rejecting unqualified preference products in SEQ according to the original arrangement sequence to obtain an updated preference product sequence NSEQ;
s65, replacing the last Z tentative marketing products in the tentative marketing sequence which does not broadcast the live video yet based on the category number Z of the candidate marketing products corresponding to the preference products in the NSEQ, thereby obtaining the movable marketing sequence.
Further, the similarity value of each preferred product to each candidate marketing product is calculated by:
Sim（X,Z）=；Sim（/>）=/>*/>；
wherein, sim is%) Is of the kind->Similarity value of the preferred product of (c) and the candidate marketing product of category Z,/v>Is of the kindThe number of preferred products contained in the preferred products of (2) is Sim (X, Z) of the kind +.>The similarity value of the X-th preferred product and the candidate marketing product of the type Z is contained in the preferred product, X is the number of labels contained in the preferred product, and Z is the number of labels contained in the candidate marketing product of the type Z; />Similarity coefficient for the mth tag of the preferred product and the nth tag of the candidate marketing product of category Z, if the two tags are identical +.>=1, vice versa->=0。
The invention has the beneficial effects that: the temporary marketing sequence is obtained through calculation, related live broadcast content is generated through an AIGC technology, the temporary marketing sequence is replaced through the real-time generation of the movable marketing sequence, and meanwhile, the movable marketing sequence can be changed in real time according to audience in a live broadcasting room, so that the live broadcast content is more matched with the preference degree of audience in the live broadcasting room, the real-time change of the movable marketing sequence improves the automation degree of live broadcast marketing and the accuracy of the live broadcast content, the marketing effect of the live broadcast marketing is improved, and the manpower resource consumption is reduced.
Drawings
The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the embodiments. Like reference numerals designate like parts in the different views.
Fig. 1 is a schematic structural view of the present invention.
Fig. 2 is a flowchart of the travel product live marketing method based on the AIGC technology of the present invention.
Fig. 3 is a flow chart of the present invention for analyzing the preference products of a current live room viewer.
FIG. 4 is a flow chart of the present invention for generating a mobile marketing sequence.
Detailed Description
The following embodiments of the present invention are described in terms of specific examples, and those skilled in the art will appreciate the advantages and effects of the present invention from the disclosure herein. The invention is capable of other and different embodiments and its several details are capable of modification and variation in various respects, all without departing from the spirit of the present invention. The drawings of the present invention are merely schematic illustrations, and are not intended to be drawn to actual dimensions. The following embodiments will further illustrate the related art content of the present invention in detail, but the disclosure is not intended to limit the scope of the present invention.
Embodiment one: according to fig. 1, 2, 3 and 4, the embodiment provides an AIGC technology-based live broadcast marketing system for a travel product, which comprises an analysis module, a live broadcast content generation module, a live broadcast interface, an interaction module, a audience information collection module and a database; the analysis module is used for analyzing preference products of audience in the living broadcast room and stock travel products to obtain movable marketing sequences of the travel products in the living broadcast room; the live broadcast content generation module comprises a live broadcast document generation unit, a live broadcast video generation unit and a live broadcast voice generation unit, wherein the live broadcast document generation unit is used for generating a marketing document of a travel product which needs to be marketed at the time of live broadcast based on an AIGC learning model and the movable marketing sequence, the live broadcast video generation unit is used for generating a marketing video according to the marketing document and pictures of the marketing product, and the live broadcast voice generation unit is used for generating a marketing video containing AI dubbing for the marketing video according to the marketing document; the live broadcast interface is used for displaying the interaction module and the marketing video of the AI dubbing; the interaction module is used for realizing a man-machine interaction function; the audience information collection module is used for collecting relevant shopping information of the audience in the current live broadcasting room; the database is used for storing the related information of the travel products and marketing records of each living broadcast room.
Specifically, the AIGC learning model used by the live document generation unit adopts a deep learning technique, and generates a countermeasure network, a circulating neural network, and the like by preferable sampling, and generates a new marketing document based on the marketing document simulation of the travel product history marketing live video in the movable marketing sequence. The AIGC learning model can generate marketing content that matches current travel products from a given historical marketing document. In the generation process, the AIGC learning model may consider context to generate content having syntax and semantics. The AIGC learning model is continuously evaluated and adjusted to continuously improve the quality of the generated content. The intelligent degree and the automation degree are greatly improved by generating marketing videos by utilizing the AIGC module, and labor force is saved.
Specifically, the live interface is provided with links of 'purchase' and 'joining shopping cart'.
Further, the analysis module comprises an information searching unit, an analysis unit and a comparison unit; the information searching unit is used for extracting information from the database; the analysis unit is used for analyzing preference products of audience in the living broadcast room and travel products suitable for marketing in the living broadcast; the comparison unit is used for executing a data comparison function.
Specifically, when the favorite value of the live broadcasting room for a certain travel product is lower than the video replacement threshold, the live broadcasting video is not required to be replaced for the travel product.
Still further, the analysis unit includes a tentative marketing sequence generation unit, a preference product analysis unit, a movable marketing sequence generation unit, and a parameter adjustment unit, where the tentative marketing sequence generation unit is configured to generate a tentative marketing sequence; the preference product analysis unit is used for analyzing preference products of audience in the living broadcasting room; the movable marketing sequence generating unit is used for generating a movable marketing sequence; the parameter adjusting unit is used for adjusting each parameter in the analysis unit.
Further, the live marketing system of the travel product comprises the following working steps:
s1, the information searching unit extracts the online marketing, offline marketing and past marketing conditions of the living broadcast room of all inventory travel products from a database, wherein the online marketing is the online past marketing outside the living broadcast room;
s2, the analysis unit selects the tentative marketing products of the live broadcast from the inventory travel products according to the search result of the information search unit and generates a tentative marketing sequence;
s3, the live content generation module generates a plurality of segments of marketing videos according to the tentative marketing sequence and combines the segments of marketing videos into a live video;
specifically, a plurality of tentative marketing products are arranged, each tentative marketing product comprises one or more tentative marketing products, and each tentative marketing product corresponds to a section of marketing video;
s4, starting live broadcasting and playing live broadcasting video, wherein the audience information collection module collects past browsing information and past purchasing information of audience in a live broadcasting room in real time;
s5, the analysis unit analyzes preference products of the current live broadcasting room audience according to the content collected by the audience information collection module;
s6, the analysis unit generates a movable marketing sequence according to the preferred products and sends the movable marketing sequence to the live broadcast content generation module;
and S7, the live content generation module generates a new live video according to the movable marketing sequence, and plays the new live video after the current marketing video is finished.
The live broadcast content generation module generates a new live broadcast video according to the movable marketing sequence, which is beneficial to updating the live broadcast video in real time, thereby ensuring that the live broadcast content always accords with the preference of audience in a live broadcast room, improving the integral intelligent degree and reducing the loss probability of the audience in the live broadcast room.
Further, the analyzing unit selects the tentative marketing product of the live broadcast and generates the tentative marketing sequence includes the steps of:
s21, the analysis unit analyzes the information extracted from the database by the information search unit, and generates favorite values of each inventory travel product according to the following formula:
；
wherein,is a favorites value for category A inventory travel products,/->Is the offline marketing weight coefficient of inventory travel products of category A, +.>Is the on-line marketing weight coefficient of inventory travel products of class A outside the local living broadcast room, </i >>Is the local living broadcast room marketing weight coefficient of inventory travel products of category A, and +.>Is the off-line total sales of inventory travel products of category a,inventory travel product of category A is marketing total sales outside the local living room on line, < >>Is the rate of departure of category A inventory travel products in online marketing outside the local living room, +.>The total sales of the inventory travel products of the category A in the ith live broadcast of the live broadcast room are obtained, and N is the total live broadcast times of the inventory travel products of the category A in the live broadcast room after the live broadcast; />Is the total sales of inventory travel products of category A in all live broadcast of the live broadcast room, and TIME is the total live broadcast TIMEs of the live broadcast room, and +.>Is the number of out-stops of stock travel products of category A in the local living broadcast room,/the user is allowed to select->Is the total number of audience in the living broadcast room in the ith living broadcast of the stock travel product of the living broadcast room type A, and the audience is added>Is the number of times the audience clicks 'buy' the inventory travel products belonging to the category A in the ith live broadcast of the inventory travel products of the category A in the live broadcast room, and +.>The number of times that the audience in the live broadcasting room clicks the inventory travel products belonging to the category A to be added into the shopping cart in the ith live broadcasting of the inventory travel products of the category A in the live broadcasting room;
specifically, the data are obtained from the past data at the end, the favorite value calculation method of each stock travel product is the same, and is not described in detail,the initial value of the program is randomly set by a parameter adjusting unit according to the relation of the three, and is adjusted after each live broadcast is finished.
S22, ranking the travel products of all kinds according to the favorite values;
s23, according to the number X of types of the travel products required to be marketed by the live broadcast, selecting the top X inventory travel products with the favorite value ranking from high to low as temporary marketing products of the live broadcast, and selecting the unselected inventory travel products as candidate marketing products, and generating a temporary marketing sequence of the temporary marketing products according to the favorite value ranking from high to low based on the temporary marketing products.
Specifically, the number of types of candidate marketing products is smaller than the number of types of tentative marketing products.
Still further, the analyzing unit analyzes preference products of the current live broadcasting room audience according to the content collected by the audience information collecting module, comprising the following steps:
s51, acquiring the purchase quantity and the label of various travel products purchased by the audience of the current living broadcast room through a living broadcast or shopping website in 5 years;
s52, sorting various travel products purchased by the audience of the current living broadcast room through the living broadcast or shopping website in 5 years according to the order of the purchase quantity from more to less, wherein the more the purchase quantity of the travel products, the earlier the sorting is;
s53, taking the ordered first Y travel products as preference products of the audience in the current living broadcast room, obtaining a sequence SEQ of the preference products, wherein Y is the category number of candidate marketing products of the current living broadcast.
Still further, the analysis unit generating the movable marketing sequence from the preferred product comprises the steps of:
s61, calculating the similarity value of each preference product and candidate marketing products;
s62, sending the similar value to a comparison unit, comparing the similar value with a set threshold value by the comparison unit, and returning a comparison result;
specifically, each preferred product will produce a similar value to a plurality of candidate marketing products, only the maximum of which is sent to the comparison unit, the threshold being set by the staff.
S63, the comparison unit judges whether the similarity value of each preferred product and the candidate marketing products is larger than a set threshold value, if the similarity value of the current preferred product is larger than the set threshold value, the current preferred product is a qualified preferred product, otherwise, the current preferred product is a disqualified preferred product;
specifically, by dividing the preferred products into qualified preferred products and unqualified preferred products, the matching degree of the preferred products and audience in a living broadcast room is improved, the replacement of the marketing products in the tentative marketing sequence by the preferred products with lower matching degree can be avoided, and the reliability of the movable marketing sequence is improved;
s64, rejecting unqualified preference products in SEQ according to the original arrangement sequence to obtain an updated preference product sequence NSEQ;
s65, replacing the last Z tentative marketing products in the tentative marketing sequence which does not broadcast the live video yet based on the category number Z of the candidate marketing products corresponding to the preference products in the NSEQ, thereby obtaining the movable marketing sequence.
Specifically, the last Z tentative marketing products are Z types from the last forward in the tentative marketing sequence, namely Z types of reciprocal, and when the number Z of types of preferred products in NSEQ is greater than or equal to the number of types of tentative marketing products which do not broadcast live video, the movable marketing sequence is not generated any more.
Further, the similarity value of each preferred product to each candidate marketing product is calculated by:
Sim（X,Z）=；Sim（/>）=/>*/>；
wherein, sim is%) Is of the kind->Similarity value of the preferred product of (c) and the candidate marketing product of category Z,/v>Is of the kindThe number of preferred products contained in the preferred products of (2) is Sim (X, Z) of the kind +.>The similarity value of the X-th preferred product and the candidate marketing product of the type Z is contained in the preferred product, X is the number of labels contained in the preferred product, and Z is the number of labels contained in the candidate marketing product of the type Z; />Similarity coefficient for the mth tag of the preferred product and the nth tag of the candidate marketing product of category Z, if the two tags are identical +.>=1, vice versa->=0。
The beneficial effects of this embodiment are: the temporary marketing sequence is obtained through calculation, related live broadcast content is generated through an AIGC technology, the temporary marketing sequence is replaced through the real-time generation of the movable marketing sequence, and meanwhile, the movable marketing sequence can be changed in real time according to audience in a live broadcasting room, so that the live broadcast content is more matched with the preference degree of audience in the live broadcasting room, the real-time change of the movable marketing sequence improves the automation degree of live broadcast marketing and the accuracy of the live broadcast content, the marketing effect of the live broadcast marketing is improved, and the manpower resource consumption is reduced.
Embodiment two: this embodiment should be understood to include all the features of any one of the foregoing embodiments and be further modified in accordance therewith, the parameter adjustment unit being configured to adjust the parameter of the object according to the following formulaAnd (3) adjusting:
Δ=kp (current error+kd error rate);
Δ=-2Δ/>；
-Δ/>;
=Δ/>+/>;
=Δ/>+/>;
wherein delta isIs->Parameter adjustment of (a),>is->Parameter adjustment amount,/-for (2)>Is>Value of->Is>Value of->Is>And Kp and Kd are adaptive parameters, the current error is the difference between the total sales and the predicted sales of the current live broadcast marketing, and the error change rate is the ratio of the current error to the current error when parameter adjustment is performed last time.
Specifically, when the secondary parameter adjustment is the primary parameter adjustment, the error rate is 0.
Specifically, the adjustment formula of the adaptive parameter is as follows:
Kp = Kp0 + ΔKp；Kd= Kd0 + ΔKd；
wherein Kp0 and Kd0 are initial parameters preset by a person skilled in the art according to experience, and ΔKp and ΔKd are adaptive parameter correction amounts calculated according to error indexes;
the error index is obtained according to the following formula:
e (t) =current error+e (t 0) (current error- Δkp(0) ) *；
Where e (t) is an error index, e (t 0) is an error index at the time of last adjustment of the adaptive parameter, Δkp (0) is Δkp at the time of last parameter adjustment, and Δt is the number of days between two adjustments.
Specifically, when the current adaptive parameter is adjusted to be the initial adjustment, e (t) =1.
The adaptive parameter correction can be calculated from the error index:
ΔKp= γp * e(t)； ΔKd= γd * de(t)/dt；
where γp and γd are empirically derived initial gain parameters adjusted by the adaptive parameters by those skilled in the art for controlling the magnitude of the adaptive parameter correction.
The beneficial effects of this embodiment are: after the multi-time live broadcast is finished, the parameter adjusting unit is used for adjusting the live broadcast according to the live broadcast resultAnd the adjustment is carried out, so that a formula for generating the favorite value is optimized, the fit degree of the tentative marketing sequence and the audience in the living broadcast room is improved, and the sales volume of living broadcast marketing is improved.
The foregoing disclosure is only a preferred embodiment of the present invention and is not intended to limit the scope of the invention, so that all equivalent technical changes made by applying the description of the present invention and the accompanying drawings are included in the scope of the present invention, and in addition, elements in the present invention can be updated as the technology develops.
Claims (8)
1. The utility model provides a travel product live broadcast marketing system based on AIGC technique which characterized in that: the system comprises an analysis module, a live content generation module, a live interface, an interaction module, a audience information collection module and a database; the analysis module is used for analyzing preference products of audience in the living broadcast room and stock travel products to obtain movable marketing sequences of the travel products in the living broadcast room; the live broadcast content generation module comprises a live broadcast document generation unit, a live broadcast video generation unit and a live broadcast voice generation unit, wherein the live broadcast document generation unit is used for generating a marketing document of a travel product which needs to be marketed at the time of live broadcast based on an AIGC learning model and the movable marketing sequence, the live broadcast video generation unit is used for generating a marketing video according to the marketing document and pictures of the marketing product, and the live broadcast voice generation unit is used for generating a marketing video containing AI dubbing for the marketing video according to the marketing document; the live broadcast interface is used for displaying the interaction module and the marketing video of the AI dubbing; the interaction module is used for realizing a man-machine interaction function; the audience information collection module is used for collecting relevant shopping information of the audience in the current live broadcasting room; the database is used for storing the related information of the travel products and marketing records of each living broadcast room.
2. The travel product live marketing system based on AIGC technology of claim 1, wherein: the analysis module comprises an information search unit, an analysis unit and a comparison unit; the information searching unit is used for extracting information from the database; the analysis unit is used for analyzing preference products of audience in the living broadcast room and travel products suitable for marketing in the living broadcast; the comparison unit is used for executing a data comparison function.
3. The travel product live marketing system based on AIGC technology of claim 2, wherein: the analysis unit comprises a tentative marketing sequence generation unit, a preference product analysis unit, a movable marketing sequence generation unit and a parameter adjustment unit, wherein the tentative marketing sequence generation unit is used for generating a tentative marketing sequence; the preference product analysis unit is used for analyzing preference products of audience in the living broadcasting room; the movable marketing sequence generating unit is used for generating a movable marketing sequence; the parameter adjusting unit is used for adjusting each parameter in the analysis unit.
4. The travel product live marketing system based on the AIGC technology according to claim 3, characterized in that it comprises the following working steps:
s1, the information searching unit extracts the online marketing, offline marketing and past marketing conditions of the living broadcast room of all inventory travel products from a database, wherein the online marketing is the online past marketing outside the living broadcast room;
s2, the analysis unit selects the tentative marketing products of the live broadcast from the inventory travel products according to the search result of the information search unit and generates a tentative marketing sequence;
s3, the live content generation module generates a plurality of segments of marketing videos according to the tentative marketing sequence and combines the segments of marketing videos into a live video;
s4, starting live broadcasting and playing live broadcasting video, wherein the audience information collection module collects past browsing information and past purchasing information of audience in a live broadcasting room in real time;
s5, the analysis unit analyzes preference products of the current live broadcasting room audience according to the content collected by the audience information collection module;
s6, the analysis unit generates a movable marketing sequence according to the preferred products and sends the movable marketing sequence to the live broadcast content generation module;
and S7, the live content generation module generates a new live video according to the movable marketing sequence, and plays the new live video after the current marketing video is finished.
5. The system of claim 4, wherein the analysis unit selects the currently-broadcast tentative marketing product and generates the tentative marketing sequence comprises the steps of:
s21, the analysis unit analyzes the information extracted from the database by the information search unit, and generates favorite values of each inventory travel product according to the following formula:
；
wherein,is a favorites value for category A inventory travel products,/->Is the offline marketing weight coefficient of inventory travel products of category A, +.>Is the on-line marketing weight coefficient of inventory travel products of class A outside the local living broadcast room, </i >>Is the local living broadcast room marketing weight coefficient of inventory travel products of category A, and +.>Is the total sales of inventory travel products of category A, +.>Inventory travel product of category A is marketing total sales outside the local living room on line, < >>Is the rate of departure of category A inventory travel products in online marketing outside the local living room, +.>The total sales of the inventory travel products of the category A in the ith live broadcast of the live broadcast room are obtained, and N is the total live broadcast times of the inventory travel products of the category A in the live broadcast room after the live broadcast; />Is the total sales of inventory travel products of category A in all live broadcast of the live broadcast room, and TIME is the total live broadcast TIMEs of the live broadcast room, and +.>Is the number of out-stops of stock travel products of category A in the local living broadcast room,/the user is allowed to select->Is the total number of audience in the living broadcast room in the ith living broadcast of the stock travel product of the living broadcast room type A, and the audience is added>Is the number of times the audience clicks 'buy' the inventory travel products belonging to the category A in the ith live broadcast of the inventory travel products of the category A in the live broadcast room, and +.>The number of times that the audience in the live broadcasting room clicks the inventory travel products belonging to the category A to be added into the shopping cart in the ith live broadcasting of the inventory travel products of the category A in the live broadcasting room;
s22, ranking the travel products of all kinds according to the favorite values;
s23, according to the number X of types of the travel products required to be marketed by the live broadcast, selecting the top X inventory travel products with the favorite value ranking from high to low as temporary marketing products of the live broadcast, and selecting the unselected inventory travel products as candidate marketing products, and generating a temporary marketing sequence of the temporary marketing products according to the favorite value ranking from high to low based on the temporary marketing products.
6. The system according to claim 5, wherein the analysis unit analyzes preference products of a current living broadcast room audience according to the contents collected by the audience information collecting module, comprising the steps of:
s51, acquiring the purchase quantity and the label of various travel products purchased by the audience of the current living broadcast room through a living broadcast or shopping website in 5 years;
s52, sorting various travel products purchased by the audience of the current living broadcast room through the living broadcast or shopping website in 5 years according to the order of the purchase quantity from more to less, wherein the more the purchase quantity of the travel products, the earlier the sorting is;
s53, taking the ordered first Y travel products as preference products of the audience in the current living broadcast room, obtaining a sequence SEQ of the preference products, wherein Y is the category number of candidate marketing products of the current living broadcast.
7. The system of claim 6, wherein the analysis unit generates the movable marketing sequence according to the preference product comprises the steps of:
s61, calculating the similarity value of each preference product and candidate marketing products;
s62, sending the similar value to a comparison unit, comparing the similar value with a set threshold value by the comparison unit, and returning a comparison result;
s63, the comparison unit judges whether the similarity value of each preferred product and the candidate marketing products is larger than a set threshold value, if the similarity value of the current preferred product is larger than the set threshold value, the current preferred product is a qualified preferred product, otherwise, the current preferred product is a disqualified preferred product;
s64, rejecting unqualified preference products in SEQ according to the original arrangement sequence to obtain an updated preference product sequence NSEQ;
s65, replacing the last Z tentative marketing products in the tentative marketing sequence which does not broadcast the live video yet based on the category number Z of the candidate marketing products corresponding to the preference products in the NSEQ, thereby obtaining the movable marketing sequence.
8. The system of claim 7, wherein the similarity value of each preferred product to each candidate marketing product is calculated by:
Sim（X,Z）=；Sim（/>）=/>*/>；
wherein, sim is%) Is of the kind->Similarity value of the preferred product of (c) and the candidate marketing product of category Z,/v>Is of the kind->The number of preferred products contained in the preferred products of (2) is Sim (X, Z) of the kind +.>The similarity value of the X-th preferred product and the candidate marketing product of the type Z is contained in the preferred product, X is the number of labels contained in the preferred product, and Z is the number of labels contained in the candidate marketing product of the type Z; />Similarity coefficient for the mth tag of the preferred product and the nth tag of the candidate marketing product of category Z, if the two tags are identical +.>=1, vice versa->=0。
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