Wine travel scene-oriented intelligent non-forgetting content generation method and system

Abstract

The invention discloses a method and a system for intelligently generating non-abandoned content for wine travel scenes, and relates to the technical field of intelligent content generation. Comprising the steps that identity recognition information of a target consumer is acquired, the identity recognition information comprises native place information and current residence place information, and identity information items are obtained; and based on the identity information item, creating a first feelings calculation formula, respectively calculating a native place feelings index and a current habitat feelings index of the target consumer, and obtaining a native place feelings item and a current habitat feelings item. According to the method, identity recognition information, including native places, residence places and the like, of target consumers is obtained, the dialect use frequency, residence duration, age and other factors are combined to calculate the feelings indexes, the preference feelings indexes are calculated according to consumption data, and the feelings indexes are sorted and stored in a database. The non-missing data which the consumers are most interested in can be accurately positioned as content recommendation items, and the propagation effect and the positive response of the non-missing data in the wine travel scene are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of content intelligent generation, in particular to a non-heritage content intelligent generation method and system for a tourism scene. BACKGROUND

[0002] Non-heritage is a short form of intangible cultural heritage, which refers to cultural performances, expression methods, knowledge systems and skills that have important cultural value and cannot be used for material form expression. The non-heritage for the tourism scene mainly refers to those intangible cultural heritage related to cultural heritage in the tourism industry. Such non-heritage not only shows rich traditional culture, but also adds uniqueness and attractiveness to the tourism experience. In the tourism industry, in order to increase the publicity effect of non-heritage, non-heritage content is usually generated and recommended according to the information of tourists.

[0003] The patent with publication number CN111738414A discloses a recommendation model generation method, a content recommendation method, a device, equipment and a medium. The training target of the low-rank graph convolution network is constructed by using a non-convex low-rank term which can be decomposed into a first low-rank matrix and a second low-rank matrix. Based on the non-convex low-rank term, the fitting accuracy of the two low-rank matrices decomposed by the low-rank graph convolution network to the original weight matrix is guaranteed, which greatly improves the fitting effect of the low-rank GCN to the original GCN, while maintaining the characteristics of small weight scale, small required data volume and fast operation speed of the low-rank GCN.

[0004] The above-mentioned and similar technical solutions cannot completely meet the interests of consumers when generating non-heritage content because the types of non-heritage are various and distributed in different regions, and the interests of different consumers in non-heritage projects are different due to factors such as different hometowns, different current residences, and even different moods on the same day. When the interest preference degree of consumers cannot be calculated, the non-heritage content generated by the conventional recommendation method cannot completely meet the interests of consumers, which may result in poor positive response effect of the generated content. SUMMARY

[0005] The present application aims to provide a non-heritage content intelligent generation method and system for a tourism scene to solve the problems in the background art.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solution: a non-heritage content intelligent generation method for a tourism scene, comprising:

[0007] Obtaining the identity information of the target consumer, the identity information including hometown information and current residence information, and obtaining the identity information item;

[0008] Based on the identity information item, a first sentiment calculation formula is created to calculate the target consumer's native place sentiment index and current residence sentiment index respectively, thereby obtaining the native place sentiment item and the current residence sentiment item;

[0009] Obtain the consumption data of target consumers, create a second sentiment calculation formula based on the consumption data, calculate the target consumer's preference sentiment index, and obtain the preference sentiment item;

[0010] Sort the hometown sentiment items, current residence sentiment items, and preference sentiment items, obtain the sentiment data that ranks first, obtain the target sentiment item, obtain the intangible cultural heritage data corresponding to the target sentiment item, and obtain the content recommendation item;

[0011] Create an intangible cultural heritage database and split it to obtain visual and olfactory datasets;

[0012] Splitting the content recommendation items, which include visual content items and olfactory content items, and obtaining matching intangible cultural heritage content in the intangible cultural heritage database based on the visual content items and the olfactory content items to obtain visual recommendation items and olfactory recommendation items;

[0013] The olfactory dataset is split into combined essential oil modules, and a modular essential oil library is created. Based on olfactory recommendations, the release is regulated through the modular essential oil library, and based on visual recommendations, it is displayed through multimedia display equipment, thus realizing the combined and rapid generation of intangible cultural heritage content.

[0014] Furthermore, the method for creating the first sentiment calculation formula includes a native place formula and a current residence formula, and the native place formula is:

[0015]

[0016] The formula for current residence is:

[0017]

[0018] Among them, Cnative Place is the sentiment index of native place, Ccurrent Residence is the sentiment index of current residence, w1 is the dialect frequency weight, F is the frequency of using the native dialect, F1 is the frequency of using the current dialect, w2 is the residence time weight, T1 is the residence time of native place, T2 is the residence time of current residence, Tmax is the preset maximum residence time, w3 is the age weight, and f(A) is the age influence function.

[0019] Furthermore, the age impact function includes:

[0020] Obtain the nonlinear relationship between age and sentiment and create an age-based piecewise function:

[0021]

[0022] Where A is age.

[0023] Furthermore, the consumption data includes leaked data, and the method for obtaining the consumption data items includes:

[0024] Acquire the target consumer's leaked product information through a camera component to obtain product information items;

[0025] Based on the commodity information item, the intangible cultural heritage corresponding information and the value corresponding information of the commodity information item are obtained to obtain the intangible cultural heritage quantity item and the intangible cultural heritage value item.

[0026] Furthermore, the method for creating the second sentiment calculation formula includes:

[0027]

[0028] Among them, C preference is the preference sentiment index, w4 is the weight of the number of purchased items, N is the number of intangible cultural heritage items, and N max is the preset maximum item purchase quantity, w5 is the purchase item value weight, V is the intangible cultural heritage value item, and Vmax is the preset maximum item purchase value.

[0029] Furthermore, the method for obtaining the visual dataset and the olfactory dataset includes:

[0030] Based on the intangible cultural heritage database, the intangible cultural heritage data in the intangible cultural heritage database are divided into categories to obtain at least two intangible cultural heritage category items, where the intangible cultural heritage category items are intangible cultural heritage content of a specific category;

[0031] Based on the intangible cultural heritage category items, determine whether the corresponding intangible cultural heritage content presentation form includes visual presentation and olfactory presentation, store the intangible cultural heritage content of visual presentation and olfactory presentation separately, and correspond them to the intangible cultural heritage category items, thereby obtaining a visual data set and an olfactory data set.

[0032] Furthermore, the method for obtaining the content recommendation item includes:

[0033] Determine the corresponding category of the target sentiment item. When the target sentiment item is a native place sentiment item or a current residence sentiment item, obtain intangible cultural heritage category information of the sentiment item corresponding to the target sentiment item, and obtain a content recommendation set. The content recommendation set includes intangible cultural heritage content of at least one region, and the content recommendation set is used as the content recommendation item.

[0034] When the target sentiment item is a preference sentiment item, the intangible cultural heritage content corresponding to the target sentiment item is obtained to obtain a content target item, and the content target item is used as a content recommendation item.

[0035] Furthermore, the method for regulating the release of the olfactory recommendation item includes:

[0036] Based on the modular essential oil library, the category information of the olfactory data set is obtained, an olfactory category item is obtained, core flavor splitting is performed based on the olfactory category item, and a category splitting set is obtained, the category splitting set at least including two categories of essential oil modules and essential oil proportion data, and essential oil addition is performed based on the category splitting set;

[0037] Based on the olfactory recommendation item, target essential oil modules and target proportion data corresponding to the category splitting set are obtained, and a blending result item is obtained;

[0038] Based on the blending result item, release is performed through an olfactory perception device.

[0039] Further, the identity information item acquisition method includes scanning acquisition and inquiry acquisition:

[0040] The hometown information of the target consumer is obtained through a camera component, and a first information item is obtained;

[0041] The present residence information, the hometown residence length information and the present residence length information of the target consumer are obtained through inquiry, and a second information item is obtained;

[0042] The first information item and the second information item are combined to obtain the identity information item.

[0043] Further, the non-heritage content intelligent generation system for the wine and travel scene uses the non-heritage content intelligent generation method for the wine and travel scene, which includes:

[0044] An acquisition module: acquiring the identity information of the target consumer, the identity information including hometown information and present residence information, and obtaining an identity information item;

[0045] An analysis module: based on the identity information item, a first emotion calculation formula is created, and the hometown emotion index and the present residence emotion index of the target consumer are calculated respectively, obtaining a hometown emotion item and a present residence emotion item; the consumption data of the target consumer is obtained, a second emotion calculation formula is created based on the consumption data, and the favorite emotion index of the target consumer is calculated, obtaining a favorite emotion item; the hometown emotion item, the present residence emotion item and the favorite emotion item are sorted, the first emotion data is obtained, and the target emotion item is obtained; the non-heritage data corresponding to the target emotion item is obtained, and a content recommendation item is obtained;

[0046] A creation module: creating a non-heritage database, splitting the non-heritage database to obtain a visual data set and an olfactory data set; the content recommendation item is split, the content recommendation item including a visual content item and an olfactory content item, and the matching non-heritage content in the non-heritage database is obtained based on the visual content item and the olfactory content item, obtaining a visual recommendation item and an olfactory recommendation item;

[0047] Display module: split the olfactory dataset into combined essential oil modules, and create a modular essential oil library, adjust and release based on olfactory recommendations through the modular essential oil library, and display based on visual recommendations through multimedia display equipment.

[0048] Compared with the prior art, the beneficial effects of the present application are:

[0049] The wine and travel scene-oriented intangible cultural heritage content intelligent generation method and system can accurately locate the intangible cultural heritage data that consumers are most interested in as content recommendation items by obtaining the identity information of target consumers, including native place and current residence, calculating the emotional index in combination with factors such as dialect usage frequency, residence length, and age, and calculating the favorite emotional index according to consumption data. This precise matching avoids the deviation of traditional recommendation methods, so that the generated intangible cultural heritage content is more in line with the actual needs of consumers, thereby improving the dissemination effect and positive response of intangible cultural heritage in the wine and travel scene.

[0050] At the same time, the intangible cultural heritage database is split to obtain a visual dataset and an olfactory dataset, and according to the presentation form of intangible cultural heritage content, the intangible cultural heritage content of visual presentation and olfactory presentation is stored and corresponds to the intangible cultural heritage category item, after obtaining the content recommendation item, the visual content item and the olfactory content item are further split, and the corresponding intangible cultural heritage content is matched from the database, which makes the intangible cultural heritage content can be personalized from multiple dimensions such as vision and olfaction, and brings consumers a more rich and stereoscopic intangible cultural heritage experience, and the multimedia display device displays the visual recommendation item, and the olfactory perception device releases the blended olfactory recommendation item, so that consumers can experience the charm of intangible cultural heritage in all directions during the wine and travel process. BRIEF DESCRIPTION OF DRAWINGS

[0051] Figure 1 It is a schematic diagram of the overall process of the present application;

[0052] Figure 2 It is a schematic diagram of the identity information item acquisition process of the present application;

[0053] Figure 3 It is a schematic diagram of the first emotional calculation formula structure of the present application;

[0054] Figure 4 It is a schematic diagram of the visual dataset and olfactory dataset acquisition process of the present application;

[0055] Figure 5 It is a schematic diagram of the visual recommendation item and olfactory recommendation item acquisition process of the present application. DETAILED DESCRIPTION

[0056] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described below, obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0057] The complexity of intangible cultural heritage resources constitutes a significant obstacle. The project covers folk literature, traditional music, traditional dance, traditional drama, traditional arts, traditional sports and acrobatics, traditional arts and crafts, traditional medicine and folk customs, etc. Each field contains numerous sub-items. For example, in the traditional arts and crafts field, ceramic making alone presents a variety of forms due to regional, school, and craft differences. This diversity makes it extremely difficult to precisely match each consumer's interest in intangible cultural heritage projects. Secondly, the individualization and dynamism of consumer interest further exacerbate this challenge. Consumer interest preferences are not static but are influenced by various factors. Hometown is an important cultural background factor that often determines a consumer's natural affinity for specific regional intangible cultural heritage projects. The influence of the current residence cannot be ignored. Consumers who have lived in a foreign place for a long time may develop new interests in local intangible cultural heritage projects, even exceeding their interest in intangible cultural heritage projects in their hometown. There are numerous intangible cultural heritage projects with wide geographical distribution. In addition, consumers are influenced by factors such as hometown, residence, and even daily mood, making their interest in intangible cultural heritage projects highly individualized and dynamic. When it is impossible to accurately calculate the degree of consumer interest in a specific intangible cultural heritage project, traditional recommendation methods often fail to work, resulting in a deviation between the generated content and the actual needs of consumers, which further affects the dissemination effect and positive response. The intangible cultural heritage content intelligent generation method for the wine and travel scene provided in the present application can precisely locate the most interesting intangible cultural heritage data for consumers as content recommendation items by obtaining the identity recognition information of target consumers, including hometown and current residence, calculating the sentiment index in combination with factors such as dialect usage frequency, residence length, and age, and calculating the favorite sentiment index according to consumption data. This precise matching avoids the deviation of traditional recommendation methods, making the generated intangible cultural heritage content more in line with the actual needs of consumers, thereby improving the dissemination effect and positive response of intangible cultural heritage in the wine and travel scene. Figure 1 As shown in the figure, the method comprises steps S100-S600.

[0058] Step S100: Obtain the identity recognition information of the target consumer to obtain the identity information item.

[0059] It should be noted that, as Figure 2As shown, the identity identification information includes native place information and current residence information, and the method of obtaining the identity information item includes scanning acquisition and inquiry acquisition: the native place information of the target consumer is obtained through the camera component to obtain the first information item; the current residence information, the length of residence information of the native place and the length of residence information of the current residence of the target consumer are obtained through inquiry to obtain the second information item; the first information item and the second information item are combined to obtain the identity information item.

[0060] Specifically, when a consumer enters a hotel to check in, he or she will need to submit his or her ID card. At this time, the camera component can scan and obtain the target consumer's place of origin information, and list it as the first information item. At the same time, the hotel staff can obtain the target consumer's current residence information, length of residence in the place of origin, and length of residence in the current residence through chatting and inquiries, and list it as the second information item, thereby obtaining the target consumer's identity information item, which is convenient for the subsequent calculation of various indexes of the target consumer.

[0061] Step S200: Create a first sentiment calculation formula to calculate the target consumer's hometown sentiment index and current residence sentiment index respectively.

[0062] It should be noted that, based on the acquired target consumer's identity information, the target consumer's sentiment index is calculated to obtain the native place sentiment item and the current residence sentiment item. The method for creating the first sentiment calculation formula includes the native place formula and the current residence formula. The native place formula is:

[0063]

[0064] The formula for current residence is:

[0065]

[0066] Where C is the sentiment index of the place of origin, C is the sentiment index of the current place of residence, w1 is the dialect frequency weight, F is the frequency of using the dialect of the place of origin, F1 is the frequency of using the dialect of the current place of residence, w2 is the residence time weight, T1 is the residence time of the place of origin, T2 is the residence time of the current place of residence, Tmax is the preset maximum residence time, w3 is the age weight, and f(A) is the age influence function;

[0067] Age impact functions include:

[0068] Obtain the nonlinear relationship between age and sentiment and create an age-based piecewise function:

[0069]

[0070] Where A is age.

[0071] Specifically, w1 is the dialect frequency weight, w2 is the residence length weight, w3 is the age weight, the initial value of the weight is set, w1, w2 and w3 are set as 3:4:3, that is, w1 is 30%, w2 is 30%, and w3 is 30%, and when the target consumer checks in, the frequency of using dialects in the language used in communication can be obtained, that is, F and F1 can be obtained, and the preset maximum residence length is set as 50 years, that is, Tmax is 50.

[0072] In the specific implementation process, as shown in Figure 3 A consumer A checks in a tourist hotel, according to the submitted identity information, it is obtained that the native place of the tourist is B, and the age is 42 years old, at the same time, the staff obtains the present residence information of the target consumer through chat inquiry, which is C city, and the residence length of the native place is 20 years, the residence length of the present residence is 22 years, and the customer uses C city dialect in the communication process, 70% uses C city dialect, and 30% uses standard Chinese, at this time, according to the first emotion calculation formula, the native place emotion index and the present residence emotion index of the consumer A are calculated, according to the age segmentation function:

[0073]

[0074] The age influence function of the consumer A is:

[0075] f(A) = {0.4 + 0.005 (42-20) = 0.51;

[0076] According to the native place formula:

[0077]

[0078] It is obtained that the native place emotion index of the consumer A is 0.313, and the native place emotion item is obtained.

[0079] The present residence formula is:

[0080]

[0081] It is obtained that the present residence emotion index of the consumer A is 0.539.

[0082] Step S300: obtaining the consumption data of the target consumer, creating a second emotion calculation formula, and calculating the favorite emotion index of the target consumer.

[0083] It should be noted that the consumption data includes the leakage data, the acquisition method of the consumption data item includes: obtaining the leakage commodity information of the target consumer through the camera component to obtain the commodity information item; based on the commodity information item, obtaining the non-heritage corresponding information and the value corresponding information of the commodity information item to obtain the non-heritage quantity item and the non-heritage value item, obtaining the favorite feeling item according to the favorite feeling index of the target consumer, the creation method of the second feeling calculation formula includes:

[0084]

[0085] Wherein C favorite is the favorite feeling index, w4 is the purchase item quantity weight, N is the non-heritage quantity item, N max is the preset maximum item purchase quantity, w5 is the purchase item value weight, V is the non-heritage value item, and Vmax is the preset maximum item purchase value.

[0086] Specifically, the purchase item quantity weight and the purchase item value weight are set to 50%, the preset maximum item purchase quantity is 20, and the preset maximum item purchase value is 10000 yuan.

[0087] In the specific implementation process, the consumer A handles the check-in in the tourist hotel, obtains 8 pieces of non-heritage information about D city held by the consumer through the camera component, and the total value is 4500 yuan. At this time, according to the second feeling calculation formula:

[0088]

[0089] The favorite feeling index of the consumer A is 0.425, and the favorite feeling item is obtained.

[0090] Step S400: Sort the hometown feeling item, the present residence feeling item and the favorite feeling item, and obtain the first feeling data and the corresponding non-heritage data in the order.

[0091] It should be noted that the first feeling data is obtained, the target feeling item is obtained, the non-heritage data corresponding to the target feeling item is obtained, the content recommendation item is obtained, after the hometown feeling item, the present residence feeling item and the favorite feeling item of the target consumer are calculated, the index is sorted according to the height, the first feeling index in the order is obtained, that is, the highest index is taken as the target feeling item, and the corresponding non-heritage data is taken as the content recommendation item, the acquisition method of the content recommendation item includes: judging the corresponding category of the target feeling item, when the target feeling item is the hometown feeling item and the present residence feeling item, obtaining the non-heritage category information of the corresponding feeling item of the target feeling item to obtain the content recommendation set, the content recommendation set includes at least one region of non-heritage content, and the content recommendation set is taken as the content recommendation item; when the target feeling item is the favorite feeling item, the non-heritage content corresponding to the target feeling item is obtained to obtain the content target item, and the content target item is taken as the content recommendation item.

[0092] In the specific implementation process, the consumer A checks in at a tourist hotel, the tourist's hometown is B, the age is 42 years old, the consumer A's present residence information is C city, and the length of residence in the hometown is 20 years, the length of residence in the present residence is 22 years, 70% uses C city dialect, 30% uses standard Chinese, and a total of 8 pieces of non-heritage information about D city are held, with a total value of 4500 yuan. At this time, according to the first emotion calculation formula and the second emotion calculation formula, the hometown emotion index, the residence emotion index and the favorite emotion index of the consumer A are respectively calculated as:

[0093]

[0094] And the results are sorted, and the sorting results are:

[0095] C present residence > C favorite > C hometown;

[0096] Therefore, C present residence is the target emotion item, and the non-heritage data corresponding to the target emotion item is C city. The non-heritage category information of C city is obtained, the content recommendation set is obtained, and the content recommendation item is obtained.

[0097] Step S500: Create a non-heritage database, and split the non-heritage database.

[0098] It should be noted that, as shown in Figure 4 After splitting the non-heritage database, the visual data set and the olfactory data set are obtained. The method for obtaining the visual data set and the olfactory data set includes: based on the non-heritage database, the non-heritage data in the non-heritage database is classified and split to obtain at least two non-heritage category items, and the non-heritage category item is a specific category of non-heritage content; based on the non-heritage category item, it is judged whether the corresponding non-heritage content presentation form includes visual presentation and olfactory presentation, the non-heritage content with visual presentation and olfactory presentation is stored respectively, and is corresponding to the non-heritage category item, and then the visual data set and the olfactory data set are obtained.

[0099] Specifically, the non-heritage database stores various forms of non-heritage culture, including folk literature, traditional music, traditional dance, traditional drama, traditional arts, traditional sports and acrobatics, traditional arts, traditional medicine and folk customs, etc., and each field contains numerous sub-items, for example, in the traditional arts field, only ceramics making shows a variety of forms due to different regions, schools and techniques, so the non-heritage data in the non-heritage database is classified according to different categories, and it is judged whether the presentation form of the classified non-heritage content includes world presentation and olfactory presentation, for example, when the classified category is wine making, the presentation form of the non-heritage content includes visual presentation and olfactory presentation, including the process of wine making and the aroma of the finished product, so the non-heritage content with visual presentation and olfactory presentation is stored separately and corresponds to the non-heritage category item, and then the visual data set and the olfactory data set are obtained.

[0100] Step S600: split the content recommendation item to obtain matching non-heritage content in the non-heritage database.

[0101] It should be noted that, as shown in Figure 5 The content recommendation item includes visual content and olfactory content, and the matching non-heritage content in the non-heritage database is obtained based on the visual content and olfactory content, and the visual recommendation item and the olfactory recommendation item are obtained. When the non-heritage data corresponding to the target emotion item of the target consumer is obtained, since the non-heritage data forms are various and contain many branches, the visual content and olfactory content can be split after the content recommendation item is split, and the non-heritage content is matched from the non-heritage database according to the visual content and olfactory content.

[0102] Step S700: split the olfactory data set into a combination of essential oil modules, and create a modular essential oil library, and adjust and release through the modular essential oil library based on the olfactory recommendation item.

[0103] It should be noted that, based on the olfactory recommendation item, the modular essential oil library is adjusted and released at the same time, and based on the visual recommendation item, the multimedia display device is displayed, so that the combination of non-heritage content is quickly generated.

[0104] It should be noted that the adjustment and release method of the olfactory recommendation item includes: based on the modular essential oil library, obtaining the category information of the olfactory dataset to obtain the olfactory category item, based on the olfactory category item, performing core flavor splitting to obtain a category splitting set, such as Huizhou chrysanthemum honey, Sichuan-Chongqing pepper spice, etc., the core flavor is split into combinable essential oil modules, including sweetness, acidity, spiciness, etc., the category splitting set at least includes essential oil modules of two categories and essential oil proportion data, after splitting into combinable essential oil modules, the specific proportion data is also included, blending according to the proportion data, adding essential oil based on the category splitting set; based on the olfactory recommendation item, obtaining the target essential oil module and the target proportion data corresponding to the category splitting set to obtain the blending result item; based on the blending result item, releasing through the olfactory perception device, the olfactory perception device is integrated with the multimedia display device, and the blended olfactory data is spread through the connection of the hotel fresh air system and the modular essential oil library.

[0105] The non-heritage content intelligent generation system for the wine and travel scene uses the non-heritage content intelligent generation method for the wine and travel scene, which includes: an acquisition module: acquiring the identity information of a target consumer, the identity information including hometown information and present residence information, to obtain an identity information item; an analysis module: based on the identity information item, creating a first emotion calculation formula, respectively calculating the hometown emotion index and the present residence emotion index of the target consumer, to obtain a hometown emotion item and a present residence emotion item; acquiring the consumption data of the target consumer, based on the consumption data, creating a second emotion calculation formula, calculating the favorite emotion index of the target consumer, to obtain a favorite emotion item; sorting the hometown emotion item, the present residence emotion item and the favorite emotion item, acquiring the first emotion data in the order, to obtain a target emotion item, acquiring the non-heritage data corresponding to the target emotion item, to obtain a content recommendation item; a creation module: creating a non-heritage database, splitting the non-heritage database to obtain a visual dataset and an olfactory dataset; splitting the content recommendation item, the content recommendation item including a visual content item and an olfactory content item, based on the visual content item and the olfactory content item, acquiring the matching non-heritage content in the non-heritage database, to obtain a visual recommendation item and an olfactory recommendation item; a display module: splitting the olfactory dataset into a combination essential oil module, and creating a modular essential oil library, based on the olfactory recommendation item, adjusting and releasing through the modular essential oil library, based on the visual recommendation item, displaying through a multimedia display device.

[0106] Although the embodiments of the present application have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended embodiments and their equivalents.

Claims

1. Intelligent generation method for intangible cultural heritage content for hospitality and tourism scenarios, including: Obtain the target consumer's identity identification information, which includes the place of origin and current residence information, to obtain identity information items; Its characteristics are: Based on the identity information item, a first sentiment calculation formula is created to calculate the target consumer's native place sentiment index and current residence sentiment index respectively, thereby obtaining the native place sentiment item and the current residence sentiment item; Obtain the consumption data of target consumers, create a second sentiment calculation formula based on the consumption data, calculate the target consumer's preference sentiment index, and obtain the preference sentiment item; Sort the hometown sentiment items, current residence sentiment items, and preference sentiment items, obtain the sentiment data that ranks first, obtain the target sentiment item, obtain the intangible cultural heritage data corresponding to the target sentiment item, and obtain the content recommendation item; Create an intangible cultural heritage database and split it to obtain visual and olfactory datasets; Splitting the content recommendation items, which include visual content items and olfactory content items, and obtaining matching intangible cultural heritage content in the intangible cultural heritage database based on the visual content items and the olfactory content items to obtain visual recommendation items and olfactory recommendation items; The olfactory dataset is split into combined essential oil modules, and a modular essential oil library is created. Based on olfactory recommendations, the release is regulated through the modular essential oil library, and based on visual recommendations, it is displayed through multimedia display equipment, thus realizing the combined and rapid generation of intangible cultural heritage content.

2. The method of claim 1, wherein the method is applied to a wine and travel scenario. The method for creating the first sentiment calculation formula includes a native place formula and a current residence formula. The native place formula is: The formula for current residence is: Among them, Cnative Place is the sentiment index of native place, Ccurrent Residence is the sentiment index of current residence, w1 is the dialect frequency weight, F is the frequency of using the native dialect, F1 is the frequency of using the current dialect, w2 is the residence time weight, T1 is the residence time of native place, T2 is the residence time of current residence, Tmax is the preset maximum residence time, w3 is the age weight, and f(A) is the age influence function.

3. The method of claim 1, wherein the method is applied to a wine and travel scenario. The age impact function includes: Obtain the nonlinear relationship between age and sentiment and create an age-based piecewise function: Where A is age.

4. The method of claim 1, wherein the method is applied to a wine and travel scenario. The consumption data includes leaked data, and the method for obtaining the consumption data items includes: Acquire the target consumer's leaked product information through a camera component to obtain product information items; Based on the commodity information item, the intangible cultural heritage corresponding information and the value corresponding information of the commodity information item are obtained to obtain the intangible cultural heritage quantity item and the intangible cultural heritage value item.

5. The method of claim 4, wherein the method is applied to a wine and travel scenario. The method for creating the second sentiment calculation formula includes: where Cpreference is a preference index, w4 is a purchase item quantity weight, N is a non-heritage quantity item, N max is a preset maximum item purchase quantity, w5 is a purchase item value weight, V is a non-heritage value item, and Vmax is a preset maximum item purchase value.

6. The method of claim 1, wherein the method is applied to a wine and travel scenario. The method for obtaining the visual dataset and the olfactory dataset includes: Based on the intangible cultural heritage database, the intangible cultural heritage data in the intangible cultural heritage database are divided into categories to obtain at least two intangible cultural heritage category items, where the intangible cultural heritage category items are intangible cultural heritage content of a specific category; Based on the intangible cultural heritage category items, determine whether the corresponding intangible cultural heritage content presentation form includes visual presentation and olfactory presentation, store the intangible cultural heritage content of visual presentation and olfactory presentation separately, and correspond them to the intangible cultural heritage category items, thereby obtaining a visual data set and an olfactory data set.

7. The method of claim 1, wherein the method is applied to a wine and travel scenario. The method for obtaining the content recommendation item includes: The corresponding category of the target emotional item is determined, when the target emotional item is a hometown emotional item and a current residence emotional item, non-heritage category information corresponding to the target emotional item is obtained, a content recommendation set is obtained, the content recommendation set includes non-heritage content of at least one region, and the content recommendation set is taken as a content recommendation item; When the target emotional item is a favorite emotional item, non-heritage content corresponding to the target emotional item is obtained, a content target item is obtained, and the content target item is taken as a content recommendation item.

8. The method of claim 1, wherein the method is applied to a wine and travel scenario. The adjusting and releasing method of the olfactory recommendation item includes: Based on the modular essential oil library, the category information of the olfactory data set is obtained, an olfactory category item is obtained, core flavor splitting is performed based on the olfactory category item, a category splitting set is obtained, the category splitting set includes at least two categories of essential oil modules and essential oil proportion data, and essential oil addition is performed based on the category splitting set; Based on the olfactory recommendation item, target essential oil modules and target proportion data corresponding to the category splitting set are obtained, a blending result item is obtained; Based on the blending result item, release is performed through an olfactory perception device.

9. The method of claim 1, wherein the method is applied to a wine and travel scenario. The obtaining method of the identity information item includes scanning and inquiring: The hometown information of the target consumer is obtained through a camera component, and a first information item is obtained; The current residence information, the hometown residence time information and the current residence residence time information of the target consumer are obtained through inquiring, and a second information item is obtained; The first information item and the second information item are combined to obtain the identity information item.

10. The system for intelligent generation of intangible cultural heritage content for a wine and travel scenario, characterized in that: The non-heritage content intelligent generation method for the wine and travel scene includes: An obtaining module is used to obtain the identity information of the target consumer, the identity information including hometown information and current residence information, and obtain an identity information item; An analysis module is used to create a first emotional calculation formula based on the identity information item, calculate the hometown emotional index and the current residence emotional index of the target consumer respectively, obtain a hometown emotional item and a current residence emotional item, obtain the consumption data of the target consumer, create a second emotional calculation formula based on the consumption data, calculate the favorite emotional index of the target consumer, obtain a favorite emotional item, sort the hometown emotional item, the current residence emotional item and the favorite emotional item, obtain the emotional data in the first place, obtain a target emotional item, and obtain the non-heritage data corresponding to the target emotional item to obtain a content recommendation item; A creating module is used to create a non-heritage database, split the non-heritage database to obtain a visual data set and an olfactory data set, split the content recommendation item, the content recommendation item including a visual content item and an olfactory content item, and obtain the matching non-heritage content in the non-heritage database based on the visual content item and the olfactory content item to obtain a visual recommendation item and an olfactory recommendation item; A display module is used to split the olfactory data set into a combined essential oil module, create a modular essential oil library, adjust and release the modular essential oil library based on the olfactory recommendation item, and display the multimedia display device based on the visual recommendation item.

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