A method and system for linking exhibition and consumption in cultural tourism complexes based on immersive interaction.

Abstract

This invention discloses a method and system for linking exhibition and consumption in cultural tourism complexes based on immersive interaction, relating to the field of cultural tourism exhibition technology. The key technical solutions include the following steps: collecting multi-dimensional data of target users within the cultural tourism complex; constructing a dynamic user profile based on the multi-dimensional data; extracting users' attention and consumption tendencies towards various exhibition contents based on the dynamic user profile; determining the correlation points between attention and consumption tendencies based on the user's location within the exhibition area to form a correlation matching result; obtaining consumption recommendation information based on the transmission relationship and transmission path; pushing consumption recommendation information related to the currently visited exhibition content to users through immersive interactive channels; collecting user feedback data on the consumption recommendation information; and optimizing the exhibition design of the cultural tourism complex based on the feedback data, achieving a seamless integration of recommendation information and user exhibition experience.

Description

Technical Field

[0001] The present invention relates to the technical field of cultural tourism exhibition, and more specifically, it relates to a method and system for linking exhibition and consumption in a cultural tourism complex based on immersive interaction. Background Art

[0002] The current cultural tourism industry is in the stage of digital transformation, and the cultural tourism complex, as a carrier integrating cultural display and commercial consumption, has become a development trend. There is an obvious gap between the exhibition experience and the commercial consumption link, which cannot effectively guide users to transform into the consumption scenario, resulting in a large amount of exhibition traffic being difficult to be transformed into commercial value. There are generally problems such as single data dimension and lagging update in the construction of user portraits. Most systems only rely on user registration information or historical order data, and cannot capture the real-time behavior and interest changes of users during the exhibition process, resulting in insufficient accuracy of subsequent consumption recommendations and difficulty in meeting the real needs of users. It is impossible to dynamically optimize the exhibition content, narrative logic and movement route layout according to the real interaction and consumption behavior of users, resulting in the disconnection between the exhibition content and user needs, which not only restricts the commercial conversion efficiency of the cultural tourism complex, but also is difficult to meet the current users' needs for immersive cultural tourism experiences. <, Summary of the Invention

[0003] Aiming at the deficiencies of the existing technology, the purpose of the present invention is to provide a method and system for linking exhibition and consumption in a cultural tourism complex based on immersive interaction.

[0004] To achieve the above purpose, the present invention provides the following technical solutions: A method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction, comprising the following steps: Collect multi-dimensional data of target users in the cultural tourism complex, and construct a dynamic user portrait based on the multi-dimensional data; Extract the attention tendency and consumption tendency of users for various exhibition contents based on the dynamic user portrait, and judge the correlation points between the attention tendency and the consumption tendency according to the exhibition area where the user is located to form a correlation matching result; Screen out consumption information that extends the exhibition experience and fits the consumption tendency of users according to the correlation matching result; Determine the conduction relationship between the user's attention tendency and consumption tendency according to the correlation matching result, obtain the conduction path from the exhibition experience to the consumption scenario according to the matching relationship of the correlation matching result, and obtain consumption recommendation information according to the conduction relationship and the conduction path; Push consumption recommendation information related to the currently visited exhibition content to users through immersive interaction channels; Collect feedback data of users on the consumption recommendation information, and optimize the exhibition design of the cultural tourism complex according to the feedback data.

[0005] Preferably, the collection of multi-dimensional data on target users within the cultural and tourism complex includes the following steps: The sensor acquisition unit captures the user's characteristic information when entering the venue, and generates the user's identification identifier based on the characteristic information. Based on the identification tags, the scene sensing module captures the user's interaction actions with the exhibition content to obtain exhibition interaction data; wherein, the number of user exhibition interactions includes interaction frequency and interaction duration; The system captures environmental adaptation feedback information of the user's location through an environmental sensing unit, and generates scene adaptation data based on the environmental adaptation feedback information and exhibition interaction data. Historical consumption data is obtained by integrating user consumption preferences and habits. By linking and integrating identification labels, exhibition interaction data, scene adaptation data, and historical consumption data, multi-dimensional data is obtained.

[0006] Preferably, constructing a dynamic user profile based on multi-dimensional data specifically includes the following steps: Based on the identification tags, the exhibition interaction data is sorted layer by layer to obtain user exhibition preference characteristics; Based on scenario adaptation data, the user's adaptation status to different exhibition environments is determined to obtain user scenario acceptance characteristics; By combining historical consumption data, we can determine the characteristics of user consumption needs regarding user consumption preferences and consumption habits. Dynamic user profiles are constructed by considering exhibition preference characteristics, scene acceptance characteristics, and consumption demand characteristics.

[0007] Preferably, the user's attention and consumption tendencies for various exhibition contents are extracted based on dynamic user profiles, specifically including the following steps: Based on dynamic user profiles, the behavioral trajectory and interactive feedback of users in the exhibition area of ​​the cultural and tourism complex are extracted, and the user's attention tendency for the exhibition content is determined based on the behavioral trajectory and interactive feedback. Based on user attention preferences, analyze the target interaction content of different exhibition contents; Based on the target interactive content, we can mine users' consumption preference-related behaviors and determine the corresponding relationship between display attention and consumption preferences based on these behaviors. The user's consumption tendency can be obtained based on the corresponding relationships.

[0008] Preferably, the correlation between the user's attention tendency and consumption tendency is determined based on the display area where the user is located, forming a correlation matching result, specifically including the following steps: Obtain the exhibition layout and content hierarchy of the exhibition area where the user is located, and determine the cultural extension direction corresponding to the exhibition content in that area based on the exhibition layout and content hierarchy; Determine users' extended experience needs for different content levels within the current exhibition area by combining their attention preferences; By comparing user consumption patterns with consumption types and preferences that satisfy the need for extended experiences, the correlation and fit between the direction of cultural extension and consumption types can be determined based on consumption types and preferences. The association matching results are obtained by associating the focus of attention corresponding to the relevance with the consumption type.

[0009] Preferably, the process of filtering out extended exhibition experiences and consumer information that aligns with user consumption preferences based on the correlation matching results includes the following steps: Based on the association matching results, determine the core elements of the exhibition content corresponding to the user's attention tendency and the core characteristics of the consumer category corresponding to the consumption tendency. By filtering the core elements of the exhibition content and the core characteristics of consumer product categories, we can obtain consumer information that extends the exhibition experience and aligns with users' consumption preferences.

[0010] Preferably, obtaining consumer recommendation information based on the transmission relationship and transmission path specifically includes the following steps: Determine the compatibility between consumer information and the transmission path based on the transmission relationship; Consumer recommendation information is obtained by arranging the appropriate consumer information in an orderly manner according to the connection order of the transmission path.

[0011] Preferably, by pushing consumption recommendations related to the currently viewed exhibition content to users through immersive interactive channels, the following steps are included: Construct information delivery paths based on immersive interactive channels; This allows consumer recommendation information to be displayed and interacted with through information delivery paths.

[0012] Preferably, optimizing the exhibition design of the cultural and tourism complex based on feedback data includes the following steps: The feedback data is differentiated to obtain effective feedback content; Based on the effective feedback, determine the degree of alignment between the exhibition content and consumer recommendations, and re-plan the exhibition narrative accordingly. The exhibition design of the cultural and tourism complex should be based on the narrative of the exhibition.

[0013] An immersive interactive system for linking exhibitions and consumption in cultural and tourism complexes, comprising: Data collection and construction module: Collects multi-dimensional data of target users within the cultural and tourism complex, and constructs dynamic user profiles based on the multi-dimensional data; Processing module: Based on dynamic user profiles, extract users' attention and consumption tendencies for various exhibition contents, and determine the correlation points between attention and consumption tendencies based on the exhibition area where the user is located to form a correlation matching result; Filtering module: Based on the correlation matching results, filter to obtain consumption information that extends the display experience and fits the user's consumption preferences; Analysis module: Determines the transmission relationship between user attention tendency and consumption tendency based on the association matching results, obtains the transmission path from the exhibition experience to the consumption scenario based on the matching relationship of the association matching results, and obtains consumption recommendation information based on the transmission relationship and transmission path; Push module: Pushes consumption recommendations related to the currently viewed exhibition content to users through immersive interactive channels; Optimization module: Collects user feedback data on consumption recommendation information and optimizes the exhibition design of cultural and tourism complexes based on the feedback data.

[0014] Compared with the prior art, the present invention has the following beneficial effects: This invention, through multi-dimensional data collection and dynamic user profiling, captures users' behavioral patterns, interactive feedback, and consumption preferences within cultural and tourism complexes. It achieves unified integration of user behavior and consumption data, effectively improving the accuracy and real-time nature of user analysis. Based on the correlation matching and transmission path analysis of dynamic user profiles, it achieves a deep correlation between exhibition attention and consumption tendencies. This allows for the uncovering of the inherent logic behind the transformation of user exhibition interests into consumption behavior, filtering consumption information that aligns with user needs and generating consumption recommendations. This not only extends the user's exhibition cultural experience but also matches their consumption preferences, effectively improving the conversion rate and user acceptance of consumption recommendations. By pushing consumption recommendations through immersive interactive channels, it achieves seamless integration of recommendation information with the user's exhibition experience, avoiding the interference of rigid information pushes on the user experience. Users naturally receive consumption guidance within the immersive exhibition experience, significantly enhancing the overall user experience and engagement. Attached Figure Description

[0015] Figure 1 This is a schematic diagram illustrating the steps of a method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction, as provided in an embodiment of the present invention. Figure 2 This invention provides a schematic diagram of a module for an immersive interactive cultural tourism complex exhibition and consumption linkage system. Detailed Implementation

[0016] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0017] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0018] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single embodiment or an embodiment selectively excluded from other embodiments.

[0019] Reference Figures 1-2 As shown.

[0020] The embodiments further illustrate the present invention's proposed method and system for linking exhibition and consumption in cultural and tourism complexes based on immersive interaction.

[0021] A method for linking exhibitions and consumption in cultural and tourism complexes based on immersive interaction includes the following steps: Collect multi-dimensional data of target users within cultural and tourism complexes, and construct dynamic user profiles based on the multi-dimensional data; Based on dynamic user profiles, we extract users’ attention and consumption tendencies toward various exhibition contents, and determine the correlation points between attention and consumption tendencies based on the exhibition area where users are located to form a correlation matching result. Based on the correlation matching results, we can filter out consumption information that extends the exhibition experience and aligns with users' consumption preferences; Based on the association matching results, the transmission relationship between user attention tendency and consumption tendency is determined. Based on the matching relationship of the association matching results, the transmission path of the exhibition experience to the consumption scenario is obtained. Based on the transmission relationship and transmission path, consumption recommendation information is obtained. Push relevant consumption recommendations to users through immersive interactive channels; Collect user feedback data on consumption recommendations and optimize the exhibition design of cultural and tourism complexes based on the feedback data.

[0022] Collecting multi-dimensional data on target users within cultural and tourism complexes includes the following steps: The sensor acquisition unit captures the user's characteristic information when entering the venue, and generates the user's identification identifier based on the characteristic information. Based on the identification tags, the scene sensing module captures the user's interaction with the exhibition content to obtain exhibition interaction data; among which, the number of user exhibition interactions includes the interaction frequency and interaction duration; The system captures environmental adaptation feedback information of the user's location through an environmental sensing unit, and generates scene adaptation data based on the environmental adaptation feedback information and exhibition interaction data. Historical consumption data is obtained by integrating user consumption preferences and habits. By linking and integrating identification labels, exhibition interaction data, scene adaptation data, and historical consumption data, multi-dimensional data is obtained.

[0023] The system captures user characteristics upon entry via a sensing unit, generating a unique identifier that serves as the user's sole credential within the cultural and tourism complex, ensuring data consistency across different scenarios. Based on this identifier, a scene sensing module captures user interactions with exhibits, recording the frequency and duration of these interactions. This generates interactive data; for example, a user lingering for 3 minutes and touching a cultural relic twice is recorded as an interaction frequency of 2 and a duration of 3 minutes. An environmental sensing unit captures environmental adaptation feedback, including user preferences and behaviors in different temperatures, brightness levels, and atmospheres. This data, combined with the interactive data, generates scene adaptation data: Scene adaptation data = Environmental adaptation feedback × Adaptation weight + Interactive data × Interaction weight. The adaptation and interaction weights are dynamically adjusted based on the complex's operational needs. For instance, users interact more frequently in brightly lit areas showcasing intangible cultural heritage crafts, reinforcing the user's preference for bright, interactive environments. Historical consumption data is generated by integrating users' past consumption preferences and habits, including the types of cultural and creative products purchased, the amount spent, and the preferred consumption scenarios. User identification data, exhibition interaction data, scenario adaptation data, and historical consumption data are then correlated and integrated to obtain multi-dimensional data covering user identity, exhibition interaction scenario preferences, and consumption behavior.

[0024] Building dynamic user profiles based on multi-dimensional data includes the following steps: Based on the identification tags, the exhibition interaction data is sorted layer by layer to obtain user exhibition preference characteristics; Based on scenario adaptation data, the user's adaptation status to different exhibition environments is determined to obtain user scenario acceptance characteristics; By combining historical consumption data, we can determine the characteristics of user consumption needs regarding user consumption preferences and consumption habits. Dynamic user profiles are constructed by considering exhibition preference characteristics, scene acceptance characteristics, and consumption demand characteristics.

[0025] Based on the identification tags, the frequency and duration of user interactions with various exhibition contents within the cultural and tourism complex are statistically analyzed. By calculating the interaction weight of users for different exhibition types, user preferences are quantified. For example, if a user's cumulative interaction time in the intangible cultural heritage skills exhibition area is 20 minutes and in the cultural relics display exhibition area is 5 minutes, the exhibition preference characteristic is calculated as: exhibition type interaction time ÷ total user interaction time × 100. Thus, the user's preference percentage for intangible cultural heritage skills exhibitions is calculated to be 80%, and the preference percentage for cultural relics display exhibitions is calculated to be 20%, thereby clarifying the user's exhibition interest tendencies. Based on scene adaptation data, the user's adaptation status to different exhibition environments is determined, thus obtaining the user's scene acceptance characteristics. Scene adaptation data includes the duration of user stay and interaction feedback in exhibition environments with different brightness, temperature, or interactive atmospheres. By calculating the scene adaptation degree of users in various environments, the acceptance characteristics are determined. Scene adaptation degree = effective interaction time of user in the environment ÷ total stay time of user in the environment × 100. For example, if a user's effective interaction time in a bright, interactive, open exhibition environment is 15 minutes and the total stay time is 16 minutes, the scene adaptation degree is 93.75. However, if the effective interaction time in a dim, quiet, immersive exhibition environment is 3 minutes and the total stay time is 10 minutes, the scene adaptation degree is 30. This indicates that users prefer open, interactive exhibition environments. Scene acceptance characteristics simultaneously record the fluctuations in users' adaptation to environmental changes, ensuring that the characteristic data can truly reflect users' environmental preferences. By combining historical consumption data, we can determine the characteristics of user consumption needs. This historical data includes users' past consumption categories, spending amounts, and preferred consumption scenarios. By statistically analyzing users' consumption frequency and proportion, we can clarify their consumption preferences. For example, if users' past spending on intangible cultural heritage handicrafts accounted for 70% of their spending and food and beverage spending accounted for 30%, this consumption demand characteristic indicates a high consumption tendency towards intangible cultural heritage handicrafts. We also record users' consumption habits, such as whether they prefer immediate or pre-booked consumption. By integrating users' exhibition preferences, scene acceptance characteristics, and consumption demand characteristics, we can construct a dynamic user profile. This dynamic user profile is continuously updated based on users' real-time interactive behavior within the cultural and tourism complex. For example, if users increase their interaction time in the cultural relic exhibition area, their exhibition preferences are adjusted accordingly, and their consumption demand characteristics are updated based on new user consumption behaviors, ensuring that the user profile always reflects the user's current interests and needs.

[0026] Based on dynamic user profiles, we extract users' attention and consumption tendencies towards various exhibition contents, specifically including the following steps: Based on dynamic user profiles, the behavioral trajectory and interactive feedback of users in the exhibition area of ​​the cultural and tourism complex are extracted, and the user's attention tendency for the exhibition content is determined based on the behavioral trajectory and interactive feedback. Based on user attention preferences, analyze the target interaction content of different exhibition contents; Based on the target interactive content, we can mine users' consumption preference-related behaviors and determine the corresponding relationship between display attention and consumption preferences based on these behaviors. The user's consumption tendency can be obtained based on the corresponding relationships.

[0027] The behavioral trajectory includes the user's movement path, dwell nodes, and dwell time in each exhibition area. The interaction feedback includes the frequency, duration, and type of interaction between the user and the exhibition content. Through quantitative calculation, the user's attention tendency is identified. For example, the formula for calculating the attention tendency score is: Attention Tendency Score = Number of Interactions × Interaction Weight + Dwell Time × Dwell Weight. The interaction weight and dwell weight are set to 0.6 and 0.4 respectively, based on the operational needs of the cultural tourism complex. If a user stays for 15 minutes and interacts 5 times in the intangible cultural heritage pottery exhibition area, the attention tendency score for that area is 5 × 0.6 + 15 × 0.4 = 9 points. If a user stays for 5 minutes and interacts once in the cultural relics exhibition area, the corresponding score is 1 × 0.6 + 5 × 0.4 = 2.6 points. By comparing the scores of different exhibition areas, it is determined that the user's attention tendency is towards intangible cultural heritage pottery exhibition content.

[0028] Based on users' attention preferences, we analyze the target interaction content for different exhibition content. When users' attention preferences are for intangible cultural heritage ceramics exhibition content, we extract specific interactive behaviors related to this type of exhibition from user interaction feedback. For example, users repeatedly watch the ceramic making process, demonstration videos, participate in ceramic making interactions, and ask the exhibition guides questions about ceramic techniques during the experience session. These interactive behaviors that are directly related to the user's core focus content are the user's target interaction content. Target interaction content can reflect the user's interest in the exhibition content, rather than just general areas of interest.

[0029] By mining user-related consumption preferences based on the user's target interaction content, the correlation between exhibition attention and consumption preferences is determined. Combining historical consumption data with real-time consumption behavior within the cultural and tourism complex, potential related consumption behaviors are identified. For example, if the user's target interaction content is a pottery-making interactive experience, querying the user's historical consumption data reveals records of purchasing handmade cultural and creative products, participating in paid experience courses, or viewing consumption information at pottery experience stores within the cultural and tourism complex. This indicates a related consumption preference. The correlation score is quantified using the formula: Correlation Score = Target Interaction Content Matching Degree × Interaction Weight + Consumption Behavior. The relevance score is calculated as follows: Matching Degree × Consumption Weight. The matching degree of the target interactive content is the degree to which the user's interactive behavior matches the exhibition theme, ranging from 0 to 1. The matching degree of the consumption behavior is the degree to which the user's past consumption behavior matches the corresponding consumption type, also ranging from 0 to 1. Both the interaction weight and the consumption weight are set to 0.5. If the user's target interactive content matching degree is 0.9 and the consumption behavior matching degree is 0.7, substituting these values ​​into the formula yields a relevance score of 0.9 × 0.5 + 0.7 × 0.5 = 0.8. When the relevance score exceeds the set threshold of 0.6, it is determined that there is a strong correlation between the exhibition's focus and the corresponding consumption preference; that is, there is a strong correlation between the focus on ceramic art exhibitions and the consumption of handmade cultural and creative products and experiential courses.

[0030] Based on the correlation between exhibition attention and consumption preferences, we can obtain users' consumption tendencies. Based on the strong correlation, we can clarify that users' consumption tendencies are: a preference for handmade creative products related to intangible cultural heritage pottery, and a preference for participating in pottery-making experience consumption projects. We can further refine consumption tendencies by combining users' historical consumption data. For example, the unit price of the creative products that users have purchased in the past is concentrated in the range of 50 to 200 yuan, and the experience courses they have participated in are mostly light experience projects of less than 1 hour. We can integrate these characteristics into consumption tendencies and finally form users' consumption tendencies that include preferences for consumption categories, consumption amount ranges, and consumption forms.

[0031] Based on the user's location within the exhibition area, correlation matching results are generated by determining the connection points between their attention and consumption tendencies. This process includes the following steps: Obtain the exhibition layout and content hierarchy of the exhibition area where the user is located, and determine the cultural extension direction corresponding to the exhibition content in that area based on the exhibition layout and content hierarchy; Determine users' extended experience needs for different content levels within the current exhibition area by combining their attention preferences; By comparing user consumption patterns with consumption types and preferences that satisfy the need for extended experiences, the correlation and fit between the direction of cultural extension and consumption types can be determined based on consumption types and preferences. The association matching results are obtained by linking the user's focus of attention corresponding to the correlation fit with the consumption type. For example, the focus of attention can be linked to pottery experience courses and pottery-themed cultural and creative products, while retaining the corresponding correlation fit value. The association matching results clearly show the correspondence and degree of fit between the user's exhibition focus and the matching consumption type.

[0032] The exhibition's narrative structure refers to the overall storytelling logic of the exhibition area. For example, the narrative structure of the intangible cultural heritage ceramics exhibition area is set from the origin of ancient pottery-making techniques to the inheritance of traditional craftsmanship, and then to the innovative application of contemporary ceramics. The content levels correspond to different narrative depths, divided into a basic understanding layer, a craft demonstration layer, and an interactive creation layer. Based on the narrative direction of the exhibition structure, each content level is matched with a corresponding cultural extension direction. For example, the basic understanding layer corresponds to the popularization of ceramic culture, the craft demonstration layer corresponds to the inheritance of intangible cultural heritage techniques, and the interactive creation layer corresponds to the creation of handmade ceramics and its application in daily life aesthetics. This clarifies the boundaries of the cultural themes that can be extended from the exhibition content.

[0033] By combining user attention patterns, we can determine the user's extended experience needs at different content levels within the current exhibition area. User attention patterns directly reflect their focus on the exhibition content. By quantifying user interaction data at different content levels, we can clarify the intensity of users' extended experience needs. The intensity of extended experience needs is calculated as: Interaction time at each content level ÷ Total user dwell time in that area × Interaction frequency, where interaction frequency is the number of times the user interacts with the content at that level. For example, if a user's interaction time at the craft demonstration level is 12 minutes, their total dwell time in that area is 22 minutes, and their interaction frequency is 3 times, the intensity of extended experience needs at that level is approximately 1.64. Similarly, if a user's interaction time at the basic knowledge level is 2 minutes and their interaction frequency is 1 time, the calculated intensity is approximately 0.09. This indicates that users' extended experience needs are primarily concentrated in the craft demonstration and interactive creation levels, rather than the popular science content at the basic knowledge level.

[0034] By comparing user consumption tendencies, we can filter consumption types and preferences that can meet the extended needs of user experience. Based on these consumption types and preferences, we determine the degree of correlation and fit between the cultural extension direction and the consumption type. We match the cultural extension direction corresponding to the extended user experience needs, and then select corresponding matching consumption types from the consumption formats of the cultural tourism complex. For example, if the user's extended experience needs correspond to the cultural extension direction of intangible cultural heritage skills inheritance and handmade pottery creation, then the matching consumption types include pottery experience courses, pottery-themed cultural and creative products, and pottery DIY material kits. The degree of matching between the two is quantified using the correlation and fit calculation formula: Correlation and Fit = Cultural Extension Direction Matching Degree × 0.6 + Consumption Preference Matching Degree × 0.4. Here, the cultural extension direction matching degree represents the degree of fit between the consumption type and the cultural extension direction, ranging from 0 to 1, and the consumption preference matching degree represents the degree of fit between the consumption type and the user's consumption tendency, also ranging from 0 to 1. Taking pottery experience courses as an example, their matching degree with the direction of cultural extension of intangible cultural heritage is 0.9, and their matching degree with the consumer tendency of light experience and low unit price consumption is 0.8. Substituting into the formula, the correlation fit is calculated to be 0.9×0.6+0.8×0.4=0.86. Similarly, the correlation fit of pottery-themed cultural and creative products is calculated to be 0.84, and the correlation fit of pottery DIY material kits is 0.7. This completes the fit assessment of different consumption types.

[0035] Based on the correlation matching results, we filter and obtain consumption information that extends the exhibition experience and aligns with users' consumption preferences. This includes the following steps: Based on the association matching results, determine the core elements of the exhibition content corresponding to the user's attention tendency and the core characteristics of the consumer category corresponding to the consumption tendency. By filtering the core elements of the exhibition content and the core characteristics of consumer product categories, we can obtain consumer information that extends the exhibition experience and aligns with users' consumption preferences.

[0036] The correlation matching results clearly identify the correspondence between user focus and matching consumption types. Based on this, the user's focus is broken down into elements, extracting the core elements of the exhibition content that best represent the user's interests. For example, if a user's focus in the intangible cultural heritage pottery exhibition area is on the demonstration of handmade pottery techniques, the corresponding core elements of the exhibition content can be broken down into traditional wheel-throwing techniques, the characteristics of clay, and the use of hand tools. Based on the correlation matching results, the consumption type is broken down into the core characteristics of the corresponding consumption category. For example, the core characteristics of the consumption category corresponding to the pottery experience course can be broken down into a teaching content of about 1 hour of hands-on practice and a price of less than 100 yuan for a basic wheel-throwing experience course.

[0037] The system matches and filters the core elements of the exhibition content with the core characteristics of consumer product categories to obtain consumer information that can extend the exhibition experience and align with users' consumption preferences. During the filtering process, the system quantifies the degree of fit between the two using a matching degree calculation formula: Consumer Information Matching Degree = Exhibition Element Matching Degree × 0.6 + Consumer Feature Matching Degree × 0.4. Here, the exhibition element matching degree represents the degree of fit between the consumer product category and the core elements of the exhibition content, ranging from 0 to 1, while the consumer feature matching degree represents the degree of fit between the consumer product category and the user's consumption preferences, also ranging from 0 to 1. Taking pottery experience courses as an example, their matching degree with core exhibition elements such as traditional wheel-throwing techniques and the characteristics of clay is 0.9, and their matching degree with users' preference for low-priced, short-term experiences within one hour is 0.8. Substituting these values ​​into the formula, the matching degree of consumption information is calculated to be 0.9 × 0.6 + 0.8 × 0.4 = 0.86. For pottery-themed cultural and creative products, the matching degree of exhibition elements is 0.7, and the matching degree of consumption characteristics is also 0.7, resulting in a matching degree of 0.7 × 0.6 + 0.7 × 0.4 = 0.7. The system sets a matching degree threshold of 0.8, only including consumption information with a matching degree higher than the threshold in the final recommendation pool. This ensures that the selected consumption information not only continues the user's interest and experience during the exhibition but also perfectly matches the user's consumption preferences, providing a high-quality content foundation for generating accurate consumption recommendations later.

[0038] Based on the transmission relationship and transmission path, consumer recommendation information is obtained, specifically including the following steps: Determine the compatibility between consumer information and the transmission path based on the transmission relationship; Consumer recommendation information is obtained by arranging the appropriate consumer information in an orderly manner according to the connection order of the transmission path.

[0039] The transmission relationship refers to the inherent logic of how user attention to an exhibition transforms into a consumption tendency. For example, if a user focuses on a demonstration of the wheel-throwing technique in intangible cultural heritage pottery, the transmission relationship manifests as an interest in pottery techniques extending to a willingness to participate in the pottery-making experience, and further extending to the consumption behavior of purchasing pottery-related cultural and creative products. The transmission path is the sequence of scenes connecting the exhibition to consumption in this transformation process, such as a wheel-throwing demonstration exhibit, a pottery experience classroom, and a pottery cultural and creative store. The degree of matching between consumption information and the transmission path is quantified by the fit degree calculation formula: Path Fit Degree = Transmission Relationship Matching Degree × 0.7 + Scene Connection Matching Degree × 0.3. Here, the transmission relationship matching degree represents the degree of fit between consumption information and the logic of user interest transformation, with a value ranging from 0 to 1, and the scene connection matching degree represents the degree of fit between the consumption scene corresponding to the consumption information and the scene sequence in the transmission path, with a value ranging from 0 to 1.

[0040] Taking pottery experience courses as an example, the matching degree between the course and the user's interest in wheel throwing extending to hands-on experience is 0.9. Furthermore, the pottery experience classroom is located at the second node of the transmission path, with a scene connection matching degree of 1.0. Substituting these values ​​into the formula, the path fit is 0.9 × 0.7 + 1.0 × 0.3 = 0.93. On the other hand, the cultural and creative shops corresponding to pottery cultural and creative products are located at the third node of the transmission path. Their matching degree with the user's interest extending to purchasing finished products is 0.8, with a scene connection matching degree of 1.0. The path fit is 0.8 × 0.7 + 1.0 × 0.3 = 0.86. Setting a path fit threshold of 0.8, only consumption information with a fit higher than the threshold will be included in subsequent scheduling stages.

[0041] The appropriate consumption information is arranged sequentially according to the scene sequence in the transmission path. For example, the experience classroom corresponding to the pottery experience course is located at the second node of the transmission path, and the cultural and creative product store corresponding to pottery cultural and creative products is located at the third node. Therefore, the recommendation order is to first push consumption information for the pottery experience course, and then push consumption information for pottery cultural and creative products. This arrangement can fit the user's visit path and the rhythm of interest conversion, allowing the recommendation information to be naturally integrated into the user's exhibition experience. Finally, the consumption recommendation information not only includes appropriate consumption content, but also clearly defines the order of recommendations, ensuring that users receive the consumption guidance most relevant to their current interest state at the appropriate scene node, achieving a seamless connection between the exhibition experience and consumption behavior.

[0042] Pushing consumption recommendations related to the currently viewed exhibition content to users through immersive interactive channels, specifically including the following steps: Construct information delivery paths based on immersive interactive channels; This allows consumer recommendation information to be displayed and interacted with through information delivery paths.

[0043] Immersive interactive channels encompass various interactive carriers directly perceived by users, such as AR guide devices, interactive projection devices, smart terminal mini-programs, and on-site voice explanation systems. Based on the user's current exhibition environment and interaction habits, suitable interactive channels are selected to construct information delivery paths. The optimal delivery path is determined using the path adaptability calculation formula: Path Adaptability = Channel Coverage × 0.5 + User Interaction Preference × 0.5. Here, channel coverage represents the signal or device coverage of the interactive channel at the user's current location, ranging from 0 to 1, and user interaction preference represents the user's past acceptance and usage tendencies towards different interactive channels, also ranging from 0 to 1.

[0044] For example, if a user is holding an AR guide device in the intangible cultural heritage pottery exhibition area and has received exhibition information through the device multiple times in the past, the channel coverage of the AR guide device is 1.0, and the user interaction preference is 0.9. Substituting these values ​​into the formula, the path fit is calculated to be 1.0×0.5+0.9×0.5=0.95. In contrast, the channel coverage of the on-site voice explanation system is 0.8, and the user interaction preference is 0.6, corresponding to a path fit of 0.7. Therefore, the AR guide device with the higher path fit is prioritized as the main channel for information transmission, and the corresponding information transmission path is constructed.

[0045] Consumer recommendations are pushed to users through a constructed information delivery path, enabling interactive engagement with the exhibition. The presentation of information is adjusted based on the user's current interaction status, ensuring seamless integration of recommendations with the user's experience. For example, if a user is viewing a pottery-throwing demonstration on an AR guided tour device, the screen can overlay booking information for a pottery experience course with scene navigation, accompanied by guiding audio. This immersive approach integrates consumer recommendations into the user's interaction, rather than a rigid pop-up notification. The timing of these pushes is synchronized with the user's interaction rhythm. When a user spends more than a set amount of time on a demonstration exhibit, their interest is considered high, and corresponding consumer recommendations are pushed, increasing user acceptance and conversion rates. This immersive interactive information delivery method allows consumer recommendations to naturally embed into the user's exhibition experience, extending their cultural experience and guiding them from exhibition interest to consumption, creating a closed loop between exhibition and consumption.

[0046] Optimize the exhibition design of cultural and tourism complexes based on feedback data, specifically including the following steps: The feedback data is differentiated to obtain effective feedback content; Based on the effective feedback, determine the degree of alignment between the exhibition content and consumer recommendations, and re-plan the exhibition narrative accordingly. The exhibition design of the cultural and tourism complex should be based on the narrative of the exhibition.

[0047] Feedback data includes various types of user interactions, such as clicks on consumer recommendations, purchase reviews, and interactive feedback. Invalid data, such as meaningless clicks due to accidental touches or abnormal feedback caused by system malfunctions, is eliminated through validity criteria. Only feedback information related to the user's true intentions is retained. For example, a user's active click on a pottery experience course recommendation link and subsequent booking is considered valid feedback, while accidental clicks with a user's attention span of less than one second are filtered out.

[0048] The degree of alignment between exhibition content and consumer recommendations is determined based on valid feedback, and the exhibition narrative is then restructured accordingly. The alignment degree is quantified using the formula: Alignment Degree = Conversion Success Rate × 0.6 + User Satisfaction × 0.4. Here, conversion success rate represents the percentage of users who complete a corresponding purchase after receiving the recommendation, and user satisfaction represents the percentage of users who give positive feedback on the recommendation; both values ​​range from 0 to 100. For example, the pottery experience course recommendation in the intangible cultural heritage pottery exhibition area has a conversion success rate of 35% and a user satisfaction rate of 80%, resulting in an alignment degree of 35 × 0.6 + 80 × 0.4 = 53. Conversely, the pottery cultural and creative product recommendation has a conversion success rate of 15% and a user satisfaction rate of 60%, resulting in an alignment degree of 15 × 0.6 + 60 × 0.4 = 33. When the alignment degree falls below a preset threshold, the current exhibition narrative and consumer recommendations are considered to have poor alignment, requiring a restructuring of the exhibition narrative.

[0049] The exhibition design of the cultural and tourism complex was optimized and adjusted according to the re-planned exhibition narrative. This included adjusting the layout of the exhibition content, the content hierarchy, and the interactive forms. For example, the entrance to the pottery experience classroom was placed at the exit of the wheel-throwing demonstration exhibit, shortening the distance for users from the exhibition experience to the consumption scene. Alternatively, the display of finished pottery pieces was added to the exhibition content to strengthen the connection between the exhibition and cultural and creative products, thereby improving the effect of subsequent exhibition and consumption linkage and achieving continuous optimization and upgrading of the exhibition design of the cultural and tourism complex.

[0050] An immersive interactive system for linking exhibitions and consumption in cultural and tourism complexes, comprising: Data collection and construction module: Collects multi-dimensional data of target users within the cultural and tourism complex, and constructs dynamic user profiles based on the multi-dimensional data; Processing module: Based on dynamic user profiles, extract users' attention and consumption tendencies for various exhibition contents, and determine the correlation points between attention and consumption tendencies based on the exhibition area where the user is located to form a correlation matching result; Filtering module: Based on the correlation matching results, filter to obtain consumption information that extends the display experience and fits the user's consumption preferences; Analysis module: Determines the transmission relationship between user attention tendency and consumption tendency based on the association matching results, obtains the transmission path from the exhibition experience to the consumption scenario based on the matching relationship of the association matching results, and obtains consumption recommendation information based on the transmission relationship and transmission path; Push module: Pushes consumption recommendations related to the currently viewed exhibition content to users through immersive interactive channels; Optimization module: Collects user feedback data on consumption recommendation information and optimizes the exhibition design of cultural and tourism complexes based on the feedback data.

[0051] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0052] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for linking exhibition and consumption in cultural tourism complexes based on immersive interaction, characterized in that, Includes the following steps: Collect multi-dimensional data of target users within cultural and tourism complexes, and construct dynamic user profiles based on the multi-dimensional data; Based on dynamic user profiles, we extract users’ attention and consumption tendencies toward various exhibition contents, and determine the correlation points between attention and consumption tendencies based on the exhibition area where users are located to form a correlation matching result. Based on the correlation matching results, we can filter out consumption information that extends the exhibition experience and aligns with users' consumption preferences; Based on the association matching results, the transmission relationship between user attention tendency and consumption tendency is determined. Based on the matching relationship of the association matching results, the transmission path of the exhibition experience to the consumption scenario is obtained. Based on the transmission relationship and transmission path, consumption recommendation information is obtained. Push relevant consumption recommendations to users through immersive interactive channels; Collect user feedback data on consumption recommendations and optimize the exhibition design of cultural and tourism complexes based on the feedback data.

2. The method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction as described in claim 1, characterized in that, Collecting multi-dimensional data on target users within cultural and tourism complexes includes the following steps: The sensor acquisition unit captures the user's characteristic information when entering the venue, and generates the user's identification identifier based on the characteristic information. Based on the identification tags, the scene sensing module captures the user's interaction actions with the exhibition content to obtain exhibition interaction data; wherein, the number of user exhibition interactions includes interaction frequency and interaction duration; The system captures environmental adaptation feedback information of the user's location through an environmental sensing unit, and generates scene adaptation data based on the environmental adaptation feedback information and exhibition interaction data. Historical consumption data is obtained by integrating user consumption preferences and habits. By linking and integrating identification labels, exhibition interaction data, scene adaptation data, and historical consumption data, multi-dimensional data is obtained.

3. The method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction as described in claim 2, characterized in that, Building dynamic user profiles based on multi-dimensional data includes the following steps: Based on the identification tags, the exhibition interaction data is sorted layer by layer to obtain user exhibition preference characteristics; Based on scenario adaptation data, the user's adaptation status to different exhibition environments is determined to obtain user scenario acceptance characteristics; By combining historical consumption data, we can determine the characteristics of user consumption needs regarding user consumption preferences and consumption habits. Dynamic user profiles are constructed by considering exhibition preference characteristics, scene acceptance characteristics, and consumption demand characteristics.

4. The method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction as described in claim 1, characterized in that, Based on dynamic user profiles, we extract users' attention and consumption tendencies towards various exhibition contents, specifically including the following steps: Based on dynamic user profiles, the behavioral trajectory and interactive feedback of users in the exhibition area of ​​the cultural and tourism complex are extracted, and the user's attention tendency for the exhibition content is determined based on the behavioral trajectory and interactive feedback. Based on user attention preferences, analyze the target interaction content of different exhibition contents; Based on the target interactive content, we can mine users' consumption preference-related behaviors and determine the corresponding relationship between display attention and consumption preferences based on these behaviors. The user's consumption tendency can be obtained based on the corresponding relationships.

5. The method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction as described in claim 1, characterized in that, Based on the user's location within the exhibition area, correlation matching results are generated by determining the connection points between their attention and consumption tendencies. This process includes the following steps: Obtain the exhibition layout and content hierarchy of the exhibition area where the user is located, and determine the cultural extension direction corresponding to the exhibition content in that area based on the exhibition layout and content hierarchy; Determine users' extended experience needs for different content levels within the current exhibition area by combining their attention preferences; By comparing user consumption patterns with consumption types and preferences that satisfy the need for extended experiences, the correlation and fit between the direction of cultural extension and consumption types can be determined based on consumption types and preferences. The association matching results are obtained by associating the focus of attention corresponding to the relevance with the consumption type.

6. The method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction as described in claim 1, characterized in that, Based on the correlation matching results, we filter and obtain consumption information that extends the exhibition experience and aligns with users' consumption preferences. This includes the following steps: Based on the association matching results, determine the core elements of the exhibition content corresponding to the user's attention tendency and the core characteristics of the consumer category corresponding to the consumption tendency. By filtering the core elements of the exhibition content and the core characteristics of consumer product categories, we can obtain consumer information that extends the exhibition experience and aligns with users' consumption preferences.

7. The method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction, as described in claim 1, obtains consumption recommendation information according to the transmission relationship and transmission path, specifically including the following steps: Determine the compatibility between consumer information and the transmission path based on the transmission relationship; Consumer recommendation information is obtained by arranging the appropriate consumer information in an orderly manner according to the connection order of the transmission path.

8. The method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction as described in claim 1, characterized in that, Pushing consumption recommendations related to the currently viewed exhibition content to users through immersive interactive channels, specifically including the following steps: Construct information delivery paths based on immersive interactive channels; This allows consumer recommendation information to be displayed and interacted with through information delivery paths.

9. A method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction, as described in claim 8, is characterized in that... Optimize the exhibition design of cultural and tourism complexes based on feedback data, specifically including the following steps: The feedback data is differentiated to obtain effective feedback content; Based on the effective feedback, determine the degree of alignment between the exhibition content and consumer recommendations, and re-plan the exhibition narrative accordingly. The exhibition design of the cultural and tourism complex should be based on the narrative of the exhibition.

10. A system for linking exhibition and consumption in a cultural tourism complex based on immersive interaction, applied to the method for linking exhibition and consumption in a cultural tourism complex based on immersive interaction as described in any one of claims 1 to 9, characterized in that, include: Data collection and construction module: Collects multi-dimensional data of target users within the cultural and tourism complex, and constructs dynamic user profiles based on the multi-dimensional data; Processing module: Based on dynamic user profiles, extract users' attention and consumption tendencies for various exhibition contents, and determine the correlation points between attention and consumption tendencies based on the exhibition area where the user is located to form a correlation matching result; Filtering module: Based on the correlation matching results, filter to obtain consumption information that extends the display experience and fits the user's consumption preferences; Analysis module: Determines the transmission relationship between user attention tendency and consumption tendency based on the association matching results, obtains the transmission path from the exhibition experience to the consumption scenario based on the matching relationship of the association matching results, and obtains consumption recommendation information based on the transmission relationship and transmission path; Push module: Pushes consumption recommendations related to the currently viewed exhibition content to users through immersive interactive channels; Optimization module: Collects user feedback data on consumption recommendation information and optimizes the exhibition design of cultural and tourism complexes based on the feedback data.

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