Intelligent Cultural Tourism Integrated Service System and Methodology for Foreign Tourists Based on Cross-Cultural Cognition
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- UNIV OF SCI & TECH OF CHINA
- Filing Date
- 2026-02-10
- Publication Date
- 2026-05-26
Smart Images
Figure CN122089518A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of cross-cultural tourism service technology, and more specifically, to an intelligent integrated cultural tourism service system and method for foreign tourists based on cross-cultural cognition. Background Technology
[0002] With the increasing frequency of global cultural exchanges and the rapid development of the tourism market, attracting foreign tourists and providing them with in-depth Chinese cultural experiences has become crucial for enhancing a nation's soft power and tourism competitiveness. However, existing inbound tourism service platforms and technologies mainly focus on basic language translation, transportation and accommodation booking, and popular attraction recommendations, showing significant shortcomings in achieving in-depth, personalized cross-cultural communication and cultural experiences. Foreign tourists often find it difficult to understand and appreciate the essence of Chinese culture due to cultural differences and cognitive barriers, resulting in tourism experiences that remain at the sightseeing level and limited cultural dissemination effects. Therefore, it is necessary to design an intelligent integrated cultural tourism service system and methodology for foreign tourists based on cross-cultural cognition.
[0003] The existing technology has the following shortcomings, specifically:
[0004] 1. Lack of in-depth cultural understanding: Existing systems (such as general translation tools like Google Translate and international online travel platforms) can only provide literal language conversion or recommendations based on general tags. They cannot deeply analyze tourists' cultural background, values, and ways of thinking, resulting in services that remain superficial and failing to achieve effective communication and resonance at the cultural level.
[0005] 2. High degree of homogenization in recommended content: Recommendation algorithms are mostly based on popularity or general preference models, failing to generate differentiated content based on tourists' unique cultural cognition characteristics. This results in monotonous recommendation results that cannot meet tourists' needs for personalized and in-depth cultural experiences.
[0006] 3. Limited service methods and lack of cross-cultural adaptability: The existing customer service and content presentation methods are standardized and do not take into account the differences in communication styles, emotional expression, and information reception habits among different cultures, resulting in insufficient service friendliness and effectiveness.
[0007] 4. Inability to build effective cultural understanding bridges: Existing technologies make it difficult to systematically establish cognitive connections between foreign tourists' native culture and Chinese culture, resulting in stiff cultural explanations, a lack of immersion in experiential activities, and superficial cultural dissemination, which fails to foster deep cultural understanding and emotional identification. Summary of the Invention
[0008] The purpose of this invention is to provide an intelligent cultural tourism integrated service system and method for foreign tourists based on cross-cultural cognition, so as to solve the problems mentioned in the background art.
[0009] To achieve the above objectives, the present invention aims to provide an intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition, including: a cross-cultural cognition engine module, used to construct and dynamically update personalized cultural cognition profiles of tourists.
[0010] The cultural bridge building module is used to calculate and output the connection points between Chinese and foreign cultural elements in a pre-built cross-cultural mapping knowledge graph based on the cultural cognition profile.
[0011] The dynamic cultural experience generation module is used to dynamically generate personalized cultural experience solutions based on the associated points and cultural cognition profiles.
[0012] The intelligent language and culture adaptation module is used to deeply adapt the content provided to tourists to the cultural context.
[0013] The cross-cultural intelligent customer service module is used to provide personalized service responses and interactive support based on the cultural background of tourists.
[0014] The intelligent travel record generation module is used to automatically generate personalized records that conform to the cultural expression habits of tourists based on the profile.
[0015] The cross-cultural social sharing optimization module is used to optimize the personalized records to suit the target social culture.
[0016] As a further improvement to this technical solution, the specific method for constructing and dynamically updating the personalized cultural cognition profile of tourists is as follows: obtain the nationality and basic information of tourists; based on the nationality and basic information of tourists, map them to a preset multi-dimensional cultural feature model to generate an initial cultural feature vector; and dynamically adjust the weights of each dimension of the feature vector by continuously collecting and analyzing the real-time behavioral data and interactive feedback of tourists to obtain the personalized cultural cognition profile of tourists.
[0017] As a further improvement to this technical solution, the specific implementation method for calculating and outputting the correlation points between Chinese and foreign cultural elements is as follows: based on the tourist's personalized cultural cognition profile, the weight of each cultural dimension is determined, and foreign cultural elements related to the tourist's cultural background are retrieved from the pre-constructed cross-cultural mapping knowledge graph. For each foreign cultural element, semantically related Chinese cultural content is searched in the knowledge graph to form candidate cultural pairs. The correlation degree of each candidate cultural pair is calculated, and candidate cultural pairs with correlation degrees exceeding a preset threshold are selected and output as the correlation points, along with an explanation of the correlation generated based on the knowledge graph path.
[0018] As a further improvement to this technical solution, the method for dynamically generating personalized cultural experience solutions is as follows: From the associated points, select the associated point with the highest matching degree with the interest preference dimension in the cultural cognition profile as the core cultural resonance point. Around the core cultural resonance point, call the preset activity material library to design specific activity units that include cultural education explanations, practical interaction links and emotional guidance points. Use a scene arrangement algorithm to connect multiple activity units in a preset logical order to form a coherent experience flow, output a complete experience solution, and use the experience personalization index to evaluate the solution.
[0019] As a further improvement to this technical solution, the method for deeply adapting the content provided to tourists to cultural context is as follows: based on the cultural cognitive profile, match the target culture's preset writing style template, analyze the semantic logic of the original text to be adapted, and reconstruct it according to the narrative habits of the target culture style. Based on the emotional expression preference dimension in the cultural cognitive profile, adjust the emotional concentration and rhetorical devices of the output text. For unique concepts and historical allusions in the source culture, output them in a "translation and interpretation combination" manner.
[0020] As a further improvement to this technical solution, the provision of personalized service responses and interactive support based on tourists' cultural background is specifically implemented as follows: real-time reception of tourists' text, voice, and image interaction data, extraction of emotional feature signals, combination with the cultural cognition profile, invocation of the corresponding cultural emotional expression rule library, cultural context calibration of the intensity and intent of the original emotional signals, matching communication patterns and solutions from the cultural adaptation strategy library according to the calibrated emotional intent and the current service scenario, generating specific response content based on the matched strategy, and simultaneously adjusting the tone, wording, and non-textual elements of the response text to adapt it to the tourists' cultural communication preferences and emotional state.
[0021] As a further improvement to this technical solution, the method of automatically generating personalized records of tourists' travel data in accordance with their cultural expression habits is as follows: Step 1: Adaptation of cultural narrative style and structure: Based on the cultural cognition profile, match the target culture's preset writing style and narrative structure template.
[0022] Step 2: Multimodal Data Fusion and Semantic Enhancement: Content analysis is performed on tourists' media data. Visual cultural elements are extracted through image recognition technology, and natural language processing technology is used to analyze the associated text metadata to generate intelligent tags rich in cultural interpretation for each piece of media data.
[0023] Step 3: Personalized Content Generation and Emotional Injection: Based on the style and structure determined in Step 1, and using the intelligent tags generated in Step 2 as key nodes, language is automatically organized to generate a coherent travel narrative text. In the narrative, the intensity and manner of emotional expression are adjusted according to the cultural profile.
[0024] As a further improvement to this technical solution, the optimization processing of the personalized record to adapt to the target social culture is specifically implemented as follows: Based on the tourist's cultural cognition profile, the mainstream social platforms of their region are determined, and the rules and style knowledge base of the platform is called to obtain data on content format, best posting time, popular tag types and user group cultural preferences. Based on the parsed rules and preferences, the personalized record is adjusted in dimensions, and a complete content package including adapted visual materials, optimized copy and recommended posting tags is output, and suggestions on posting timing are provided.
[0025] The second aspect of the present invention provides a method for a smart cultural tourism integrated service system for foreign tourists based on cross-cultural cognition, comprising: Step 1: analyzing the cultural background information of tourists and constructing a multi-dimensional cultural cognition profile.
[0026] Step 2: Identify the connection points between foreign cultures and Chinese culture through cultural relevance calculation.
[0027] Step 3: Based on the cultural cognition profile, dynamically generate personalized cultural experience solutions.
[0028] Step 4: Provide cross-cultural adapted intelligent customer service and content generation services.
[0029] Step 5: Automatically generate travel records and sharing content that match the tourist's cultural background.
[0030] Step 6: Continuously optimize the cultural awareness model and service quality based on tourist feedback.
[0031] As a further improvement to this technical solution, the formula for calculating cultural relevance in step 2 is as follows:
[0032] ;
[0033] in, Indicating foreign cultural elements, Representing Chinese cultural content, This indicates the degree of cultural relevance between foreign cultural elements and Chinese cultural content. Indicates the first The weight of each cultural dimension The first foreign cultural element Feature values of each cultural dimension The content of Chinese culture Feature values of each cultural dimension Represents the dimensional similarity function. The number representing the cultural dimension. This represents the total number of cultural dimensions.
[0034] Compared with the prior art, the beneficial effects of the present invention are as follows:
[0035] 1. Achieved in-depth understanding and accurate matching of foreign tourists' cultural backgrounds: By constructing dynamically updated personalized cultural profiles through a cross-cultural cognitive engine, the service has been elevated from basic language translation to a deeper cognitive adaptation, significantly improving the relevance and quality of the cultural experience.
[0036] 2. An effective bridge for cultural understanding between China and foreign countries has been built: By using the cultural bridge building module, the inherent connections between Chinese and foreign cultural elements are quantified and explained, making cultural communication easier for tourists from different backgrounds to understand and accept, and enhancing the educational significance and depth of cultural experience.
[0037] 3. It provides a full-process, end-to-end personalized service ecosystem: The system covers the entire chain from cultural understanding, experience generation, real-time interaction to recording and sharing. Each module works collaboratively based on a unified cultural cognition profile, forming a complete and highly personalized cross-cultural smart service closed loop.
[0038] 4. Leveraging artificial intelligence to significantly improve service efficiency and content quality: AI technology automatically generates highly tailored cultural experience plans, personalized travel records, and optimized sharing content, reducing the cost of manual customization while ensuring the professionalism, cultural accuracy, and attractiveness of the content.
[0039] 5. It has effectively promoted the international dissemination of Chinese culture: by providing in-depth, positive and personalized cultural experiences, it has enhanced foreign tourists' awareness, emotional identification and willingness to share Chinese culture, thereby increasing the international influence and attractiveness of Chinese culture on a wider scale. Attached Figure Description
[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0041] Figure 1 This is a schematic diagram of the system structure connection of the present invention.
[0042] Figure 2 This is a schematic diagram of the implementation steps of the method of the present invention. Detailed Implementation
[0043] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0044] Example: Please refer to Figure 1 As shown, a smart cultural tourism integrated service system for foreign tourists based on cross-cultural cognition is provided, including: a cross-cultural cognition engine module, which is used to build and dynamically update the personalized cultural cognition profile of tourists.
[0045] The cross-cultural cognitive engine includes a cultural feature vector encoding submodule, which transforms abstract cultural traits into computable digital representations.
[0046] In one specific embodiment, the method for constructing and dynamically updating the personalized cultural awareness profile of tourists is as follows: obtaining the nationality and basic information of tourists; mapping the nationality and basic information of tourists to a preset multi-dimensional cultural feature model to generate an initial cultural feature vector; and dynamically adjusting the weights of each dimension of the feature vector by continuously collecting and analyzing the real-time behavioral data and interactive feedback of tourists to obtain the personalized cultural awareness profile of tourists.
[0047] Example 1: Implementation of a Cross-Cultural Cognition Engine
[0048] Cultural Feature Extraction Subsystem: Establishes a multi-dimensional cultural feature model encompassing value dimensions, thinking patterns, communication styles, and aesthetic preferences. For French tourists, it extracts cultural traits such as romanticism, individualism, and artistic pursuits; for German tourists, it identifies characteristics such as rigor, logic, and efficiency orientation.
[0049] Cultural Awareness Profile Construction: Utilizing deep learning technology, and combining tourists' basic information, behavioral data, and interactive feedback, a personalized cultural awareness profile is constructed. The profile includes a cultural background weight vector. ,in Indicates the first The weight value of each cultural feature.
[0050] Dynamic update mechanism: Cultural awareness profiles are dynamically updated based on real-time tourist feedback and behavioral data to improve matching accuracy. An incremental learning algorithm is employed. ,in For learning rate, This represents the change in new cultural characteristics.
[0051] Example 2: Construction and updating of a personalized cultural perception profile for French tourist Sophie
[0052] 1. Initial profile construction (cold start)
[0053] Input: Sophie's basic information: nationality (France), language (French), age (30-40 years old).
[0054] Model mapping: The system calls a preset multi-dimensional cultural feature model to extract typical feature vectors of French culture as its initial profile. .
[0055] Initial vector generation: =[Individualism: 0.90, Art and Aesthetic Sensitivity: 0.85, Low Power Distance (Preferring Equal Communication): 0.88, Uncertainty Avoidance (Preferring Planning): 0.60, ...]
[0056] Interpretation: At this point, the system's understanding of Sophie is based solely on the statistical characteristics of her nationality, suggesting that she is likely to have a high degree of individualism and artistic appreciation.
[0057] 2. Real-time data collection and behavior analysis (in the "Huangshan-Hongcun" digital itinerary)
[0058] Sophie started using the app to browse her schedule.
[0059] Behavioral data flow:
[0060] I spent 12 minutes on the "Huangshan Scenic Photography Guide" page and saved 3 photos of misty, uniquely shaped pines.
[0061] Quickly scroll through the text-only introduction page on the "History of Huizhou Wood Carving" (stay for <30 seconds).
[0062] On the introduction page for the "Making Huizhou Ink by Hand" experience activity, I watched all the videos and clicked "Add to Wishlist".
[0063] In the customer service chat, I asked: "Are there any more pristine ancient villages with fewer tourists that I can explore?"
[0064] 3. Dynamic profile update (incremental learning)
[0065] The system analyzes the above behaviors and calculates the changes in cultural characteristics. And update the portrait.
[0066] calculate :
[0067] The "Art and Aesthetic Sensitivity" dimension (+0.08) is a strong indicator of this characteristic: appreciating and collecting landscape photographs of high aesthetic value over a long period of time.
[0068] The "Practice and Experience Orientation" dimension (+0.10) showed a strong interest in hands-on experiences such as "making Huizhou ink by hand," which was significantly higher than the interest in static historical introductions.
[0069] "Adventure and Uniqueness Preference" dimension (+0.07): Actively seeking pristine, off-the-beaten-path travel destinations.
[0070] The "uncertainty aversion" dimension (-0.05) indicates a lack of interest in highly structured historical narratives, suggesting she may prefer a more flexible, discovery-based experience than the typical French tourist.
[0071] Application update formula: (Assuming learning rate) (This gives high weight to historical data, but new behaviors can lead to clear adjustments.)
[0072] Updated cultural perception profile :
[0073] [Individualism: 0.90, Art and Aesthetic Sensitivity: 0.87, Practice and Experience Orientation: 0.78, Adventure and Uniqueness Preference: 0.72, Low Power Distance: 0.88, Uncertainty Avoidance: 0.58, ...]
[0074] 4. Results and Applications
[0075] The portrait has evolved: Sophie's portrait has rapidly evolved from an "average French tourist" model based on nationality to a more precise model of "personalized travelers who prefer art, in-depth experiences, and unique explorations".
[0076] Drive downstream services: This updated profile takes effect immediately.
[0077] Building cultural bridges: When recommending cultural content to her, the system will give higher weight to linking French art practices (such as painting and handicrafts) with corresponding Chinese techniques.
[0078] Dynamic experience generation: Subsequent generated plans will focus more on "niche sketching locations" and "intangible cultural heritage handicraft workshop experiences" rather than mass tourist routes.
[0079] Content and customer service fit: Customer service responses will be more supportive of exploratory needs, and the language style will be more inclined to encourage creativity and discovery.
[0080] The cultural bridge building module is used to calculate and output the connection points between Chinese and foreign cultural elements in a pre-built cross-cultural mapping knowledge graph based on the cultural cognition profile.
[0081] The cultural bridge construction module uses a cultural relevance calculation algorithm to calculate the similarity between foreign cultural elements and Chinese cultural content.
[0082] In one specific embodiment, the method for calculating and outputting the association points between Chinese and foreign cultural elements is as follows: based on the tourist's personalized cultural cognition profile, the weights of each cultural dimension are determined, and foreign cultural elements associated with the tourist's cultural background are retrieved from a pre-constructed cross-cultural mapping knowledge graph. For each foreign cultural element, semantically related Chinese cultural content is searched in the knowledge graph to form candidate cultural pairs. The correlation degree of each candidate cultural pair is calculated, and candidate cultural pairs with correlation degrees exceeding a preset threshold are selected and output as the association points, along with an explanation of the association generated based on the knowledge graph path.
[0083] The pre-constructed cross-cultural mapping knowledge graph construction method is as follows: A graph pattern is established with "cultural elements" as nodes and "semantic and value relationships" as edges; core cultural concepts, historical figures, artistic symbols, philosophical ideas, and typical practices from authoritative cultural classics, academic research, and verified tourism data are extracted as nodes; and the types of associations between nodes are defined based on cultural comparison theory (such as common themes, similar functions, and comparable values) (such as "similar symbolic meanings," "functional equivalence," and "emotional resonance"); the associations are verified and strengthened through human expert calibration and machine learning, forming a structured knowledge base with rich semantic connections that can be traversed and queried by algorithms.
[0084] The preset threshold setting method is as follows: the system sets a basic relevance threshold (e.g., 0.7) and then fine-tunes this basic threshold based on the weight of specific dimensions such as "cultural openness" or "cognitive complexity" in the tourist's personalized cultural awareness profile. For example, for tourists with high cultural openness, the threshold can be appropriately lowered to provide broader and more inspiring relevance; for tourists seeking in-depth understanding, the threshold is raised to ensure the accuracy and depth of the recommended relevance. This dynamic mechanism ensures that the selection of relevance points meets both universal quality standards and achieves personalized adaptation.
[0085] Take, for example, the connection between the French Enlightenment thinker Voltaire's concept of tolerance and the Chinese story of "Six-Foot Lane":
[0086] Step 1: Extract the core elements of Voltaire's philosophy of tolerance: rationality, inclusiveness, and harmonious coexistence;
[0087] Step 2: Analyze the cultural connotations of the Six-Foot Lane story: courtesy, harmony, and wisdom in resolving conflicts;
[0088] Step 3: Calculate the correlation: tolerance and courtesy (0.85), rationality and wisdom (0.90), harmonious coexistence and neighborly harmony (0.95);
[0089] Step 4: Building Cultural Bridges: Through shared values of rationality and inclusiveness, help French tourists understand the wisdom of courtesy and consideration in Chinese culture.
[0090] The dynamic cultural experience generation module is used to dynamically generate personalized cultural experience solutions based on the associated points and cultural cognition profiles.
[0091] In one specific embodiment, the method for dynamically generating personalized cultural experience solutions is as follows: from the associated points, select the associated point with the highest matching degree with the interest preference dimension in the cultural cognition profile as the core cultural resonance point; around the core cultural resonance point, call the preset activity material library to design specific activity units including cultural education explanation, practical interaction and emotional guidance points; use the scene arrangement algorithm to connect multiple activity units in a preset logical order to form a coherent experience process; output a complete experience solution; and use the experience personalization index to evaluate the solution.
[0092] The pre-built activity resource library is constructed as follows: The system first deconstructs and standardizes a massive amount of cultural experience activities, breaking them down into reusable atomic modules, and storing them according to categories such as "cultural education explanation," "practical interactive activities," and "emotional guidance points." Each module is accompanied by structured attribute tags, including but not limited to required duration, suitable scenarios, associated cultural elements, required skill level, emotional tone, and corresponding cultural cognition dimension weights. The construction of this resource library integrates the domain knowledge of cultural experts with the analysis of historical service data, ensuring the accuracy and feasibility of the content, and can be continuously expanded and optimized through algorithms based on new successful cases.
[0093] The preset logical order is defined by the core rule base of the scene arrangement algorithm, and its basic principle is to follow the experience deepening path of "cognitive construction - practical internalization - emotional sublimation". Specifically, the system defaults to placing "cultural education explanation" units first to establish knowledge background and cognitive framework; then, "practical interaction" is arranged to allow tourists to internalize and transform knowledge through personal participation; finally, "emotional guidance points" are set to guide reflection and resonance, completing the emotional connection. This order is not fixed and the arrangement algorithm will dynamically adjust it according to the tourist's cultural cognition profile (such as a preference for the "practice first, theory later" experience mode) to ensure that the process conforms to the user's cognitive habits and psychological expectations. For example: "cognitive introduction - practical experience - emotional sublimation".
[0094] The scene orchestration algorithm is existing technology.
[0095] Intelligent scheduling of experiential activities:
[0096] Personalized cultural experience plans are dynamically generated for tourists from different cultural backgrounds.
[0097] Sophie, a French tourist, on her trip to Huangshan:
[0098] Identifying points of cultural resonance: the aesthetic commonalities between French and Chinese calligraphy;
[0099] Experiential activity design: Write your French name with a calligraphy brush and experience the fusion of Chinese and French calligraphy art;
[0100] Cultural Interpretation: Interpreting the aesthetic conception of Chinese calligraphy by combining it with the French artistic tradition;
[0101] Emotional connection: Establishing an emotional identification with Chinese culture through the artistic creation process;
[0102] Personalization assessment:
[0103] Personalization Index of Design Experience
[0104] in, The Personalization Index is a comprehensive quantitative indicator used to evaluate the overall personalization level of the generated cultural experience plan. A higher value indicates a greater match between the plan and a specific tourist across the three dimensions of culture, interests, and emotions, resulting in a better expected experience. For cultural matching degree, it represents the first The degree to which each activity unit aligns with the tourist's cultural perception profile is directly derived from the output of the cultural bridge-building module, specifically the relevance score of the "points of connection between Chinese and foreign cultures" upon which that unit relies. Let be the relevance of interest, representing the th The correlation between each activity unit and the visitor's real-time interests and preferences. This value is calculated by analyzing real-time visitor behavior data (such as clicks, dwell time, searches, and historical preferences) and is a dynamic variable. It ensures that the experience content can capture the visitor's current attention. Emotional resonance level, representing the degree of resonance. The intensity of emotional resonance that each activity unit may evoke in visitors. This value is based on an affective computational model, which estimates the activity unit's emotional tone (e.g., pride, tranquility, curiosity) in conjunction with the visitor's emotional expression preferences within their cultural profile. It aims to ensure that the experience touches visitors' emotions. Indicates the scheme unit number. Indicates the total number of scheme units.
[0105] The intelligent language and culture adaptation module is used to deeply adapt the content provided to tourists to the cultural context.
[0106] In one specific embodiment, the cultural context-deep adaptation of the content provided to tourists is implemented as follows: Based on the cultural cognitive profile, a pre-set writing style template of the target culture is matched; the style template includes at least: the direct and personal style corresponding to European and American culture, and the implicit and collective context style corresponding to East Asian culture; the semantic logic of the original text to be adapted is analyzed and reconstructed according to the narrative habits of the target culture; this includes: adjusting the order of argument presentation (e.g., from general to specific or from specific to general), and modifying the method of exemplification (e.g., using personal stories or group data); based on the emotional expression preference dimension in the cultural cognitive profile, the emotional intensity and rhetorical devices of the output text are adjusted; this includes: enhancing or weakening the emotional intensity of adjectives, and replacing metaphors or allusions with equivalent expressions in the target culture; for unique concepts and historical allusions in the source culture, a "translation and interpretation combination" approach is adopted for output. That is, a short explanation based on the target culture background is added after the translation.
[0107] Cross-cultural travel diary generation:
[0108] Based on the tourist's cultural background, travel diaries are automatically generated in accordance with their expression habits.
[0109] Algorithm flow:
[0110] Step 1: Identifying Cultural Writing Styles
[0111] France: Romantic and lyrical, emphasizing the expression of feelings.
[0112] Germany: Clear logic, emphasis on factual description
[0113] Japan: Delicate and subtle, emphasizing the feeling of the seasons.
[0114] Step 2: Content Structure Adaptation
[0115] Adjust the article structure and expression style according to the narrative habits of the target culture.
[0116] Step 3: Adjusting Emotional Tone
[0117] Based on the characteristics of cultural and emotional expression, adjust the emotional intensity and expression method of the content.
[0118] Multimodal content compilation:
[0119] Computer vision technology is used to identify cultural elements in photos, and natural language processing is used to generate cultural interpretation tags.
[0120] Image cultural tag recognition algorithm:
[0121] ;
[0122] in, Output: Cultural labels for the image. This is a text description rich in cultural semantics, used to explain the cultural elements, meanings, or background contained in the image. It is not a simple object recognition result (such as "mountain" or "building"), but a deeper cultural interpretation (such as "the welcoming pine of Huangshan symbolizing resilience" or "the horse-head wall embodying the 'Five Sacred Mountains Facing the Sky' style of Huizhou architecture").
[0123] This refers to cultural feature extraction based on computer vision. It's a convolutional neural network specifically trained to recognize cultural elements. It analyzes image pixels to directly identify visual features, symbols, styles, or scenes associated with a specific culture. For example:
[0124] Identify "calligraphy works" in images and determine their font style.
[0125] Identify specific patterns in "traditional clothing".
[0126] Identify typical landscaping elements in a garden (such as pavilions, artificial hills, and moon gates).
[0127] This represents contextual semantic understanding based on natural language processing. This part does not directly process the image, but rather analyzes the metadata associated with the image, including:
[0128] Shooting location (GPS coordinates or place name, such as "Forbidden City" or "Broken Bridge of West Lake")
[0129] Shooting time (date, season, holiday)
[0130] Visitor-added text notes (such as "the tranquility of the morning")
[0131] The title of the experiential activity (e.g., "Making Jingdezhen Porcelain")
[0132] Through NLP technology, it understands the semantics of these texts and extracts key cultural contextual information.
[0133] The cross-cultural intelligent customer service module is used to provide personalized service responses and interactive support based on the cultural background of tourists.
[0134] The cross-cultural intelligent customer service system includes culturally perceptive emotion computing technology to identify emotional expression patterns in different cultural contexts.
[0135] In one specific embodiment, the method for providing personalized service responses and interactive support based on tourists' cultural background is as follows: Real-time reception of tourists' text, voice, and image interaction data; extraction of emotional feature signals; combining this with the cultural cognitive profile; invoking the corresponding cultural emotional expression rule library; calibrating the intensity and intent of the original emotional signals within the cultural context; and matching communication patterns and solution strategies from a cultural adaptation strategy library based on the calibrated emotional intent and the current service scenario. The strategy library includes at least: a detailed explanation mode for tourists with high uncertainty and a culture of avoidance; and a priority mode for efficient solutions for tourists with direct cultural communication. Based on the matched strategy, specific response content is generated, and the tone, wording, and non-textual elements of the response text (such as emoticons and suggested voice intonation) are adjusted simultaneously to adapt to the tourists' cultural communication preferences and emotional state.
[0136] The intelligent travel record generation module is used to automatically generate personalized records that conform to the cultural expression habits of tourists based on the profile.
[0137] The intelligent travel record generation module uses a cross-cultural content generation algorithm to generate personalized content based on the expression habits and aesthetic preferences of the target culture.
[0138] In one specific embodiment, the automatic generation of personalized records from tourists' travel data in accordance with their cultural expression habits is implemented as follows: Step 1: Adapting cultural narrative style and structure: Based on the cultural cognitive profile, matching the target culture's preset writing style and narrative structure template. For example, adapting a lyrical prose structure dominated by personal feelings to French tourists, and a logical narrative structure based on time / place to German tourists.
[0139] Step Two: Multimodal Data Fusion and Semantic Enhancement: Content analysis is performed on tourists' media data (such as images and videos). Visual cultural elements are extracted using image recognition technology (such as CNN), and natural language processing technology is combined to analyze the associated textual metadata (such as location and time) to generate intelligent tags rich in cultural interpretation for each piece of media data. The generation process follows the algorithm: Cultural Tag = Visual Cultural Feature Recognition (Image) + Contextual Semantic Understanding (Metadata).
[0140] Step 3: Personalized Content Generation and Emotional Infusion: Based on the style and structure determined in Step 1, and using the intelligent tags generated in Step 2 as key nodes, the language is automatically organized to generate a coherent travel narrative text. Within the narrative, the intensity and manner of emotional expression are adjusted according to the cultural profile. For example, exclamations may be enhanced or weakened, and metaphors that align with the aesthetic preferences of the target culture may be selected.
[0141] The cross-cultural social sharing optimization module is used to optimize the personalized records to suit the target social culture.
[0142] In one specific embodiment, the optimization process for adapting the personalized record to the target social culture is implemented as follows: Based on the tourist's cultural perception profile, the mainstream social media platforms of their region are determined, and the rules and style knowledge base of the platform is called to obtain data on content format, optimal posting time, popular tag types, and user group cultural preferences. Based on the parsed rules and preferences, the personalized record is adjusted in dimensions, and a complete content package including adapted visual materials, optimized copy, and recommended posting tags is output, along with suggestions on posting timing.
[0143] Dimensional adjustments include at least:
[0144] Format and presentation optimization: Adjust the aspect ratio of the content, video length, and the proportion of text and visual elements to conform to the technical specifications of the target platform and user browsing habits.
[0145] Expression style and copywriting rewriting: Extract or rewrite the narrative text in the original record into language that conforms to the popular style of the target platform (such as short copy that is more interactive, suspenseful or emotionally engaging).
[0146] Tag and Topic Association: Based on the cultural themes recorded in the personalized data, the system intelligently associates the content with current trending topics on the target platform or equivalent conceptual tags in the local culture to increase the likelihood of the content being discovered.
[0147] Social media culture adaptation:
[0148] Optimize content display format for mainstream social media platforms in different countries:
[0149] Facebook (Western): Emphasizes sharing personal feelings and features beautiful pictures.
[0150] Instagram: Emphasizing visual impact, with simple hashtags
[0151] Twitter: Concise and to the point, trending topics linked
[0152] Content propagation optimization algorithm:
[0153] Optimize tag selection and content description based on the social habits of the target culture:
[0154] ;
[0155] Output: Optimized shareable content package. This is a composite object containing the final content fully adapted to a specific target social culture, typically consisting of adapted visual assets, rewritten copy, recommended tags, and publishing suggestions.
[0156] This represents a function for adapting to different cultural styles.
[0157] Input: The original content to be optimized and the cultural perception profile of tourists.
[0158] Processing: Based on the profile, adjust the expression style, emotional intensity, and narrative perspective of the content.
[0159] Output: The core content adapted to the style. For example, transforming emotional expression into rational statements for German tourists; enhancing the enthusiasm and interactivity of the copy for Brazilian tourists.
[0160] This indicates the platform format and specification optimization function.
[0161] Input: Style-adapted content, and the technical and community rule base of the target social platform.
[0162] Processing: Format the content to meet platform requirements and adapt to user browsing habits.
[0163] Output: Content adapted to the correct format. For example, cropping images to square / vertical format for Instagram and optimizing video length; concise text for Twitter to the character limit and extract the core points.
[0164] This represents the propagation enhancement and label optimization function.
[0165] Input: Content adapted to the style and format, and real-time trending topics and dissemination model data.
[0166] Processing: Intelligent generation or recommendation of topic tags, @mentions, related challenges, etc., that can improve content visibility and engagement.
[0167] Output: A package of tags with elements optimized for wider reach. For example, tags related to current travel hotspots in the target country, or tags that evoke cross-cultural resonance (such as #CulturalJourney).
[0168] See Figure 2 As shown, a method for a smart cultural tourism integrated service system for foreign tourists based on cross-cultural cognition is provided, including: Step 1: Analyze the cultural background information of tourists and construct a multi-dimensional cultural cognition profile.
[0169] Step 2: Identify the connection points between foreign cultures and Chinese culture through cultural relevance calculation.
[0170] Step 3: Based on the cultural cognition profile, dynamically generate personalized cultural experience solutions.
[0171] Step 4: Provide cross-cultural adapted intelligent customer service and content generation services.
[0172] Step 5: Automatically generate travel records and sharing content that match the tourist's cultural background.
[0173] Step 6: Continuously optimize the cultural awareness model and service quality based on tourist feedback.
[0174] In one specific embodiment, the formula for calculating cultural relevance in step 2 is:
[0175] ;
[0176] in, Indicating foreign cultural elements, Representing Chinese cultural content, This indicates the degree of cultural relevance between foreign cultural elements and Chinese cultural content. Indicates the first The weight of each cultural dimension The first foreign cultural element Feature values of each cultural dimension The content of Chinese culture Feature values of each cultural dimension Represents the dimensional similarity function. The number representing the cultural dimension. This represents the total number of cultural dimensions.
[0177] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely preferred examples and are not intended to limit the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.
Claims
1. A smart cultural tourism integrated service system for foreign tourists based on cross-cultural cognition, characterized in that: include: The cross-cultural cognition engine module is used to build and dynamically update personalized cultural cognition profiles of tourists; The cultural bridge building module is used to calculate and output the connection points between Chinese and foreign cultural elements in a pre-constructed cross-cultural mapping knowledge graph based on the cultural cognition profile. The dynamic cultural experience generation module is used to dynamically generate personalized cultural experience solutions based on the aforementioned association points and cultural cognition profiles. The intelligent language and culture adaptation module is used to deeply adapt the content provided to tourists to the cultural context. The cross-cultural intelligent customer service module is used to provide personalized service responses and interactive support based on the cultural background of tourists; The intelligent travel record generation module is used to automatically generate personalized records that conform to the cultural expression habits of tourists based on the profile. The cross-cultural social sharing optimization module is used to optimize the personalized records to suit the target social culture.
2. The intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition as described in claim 1, characterized in that: The specific method for constructing and dynamically updating the personalized cultural perception profile of tourists is as follows: The system obtains tourists' nationality and basic information, maps it to a pre-defined multi-dimensional cultural feature model, generates an initial cultural feature vector, and dynamically adjusts the weights of each dimension of the feature vector by continuously collecting and analyzing tourists' real-time behavioral data and interactive feedback, thus obtaining a personalized cultural cognition profile of tourists.
3. The intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition as described in claim 2, characterized in that: The specific method for calculating and outputting the correlation points between Chinese and foreign cultural elements is as follows: Based on the tourist's personalized cultural cognition profile, the weights of each cultural dimension are determined, and foreign cultural elements associated with the tourist's cultural background are retrieved from a pre-constructed cross-cultural mapping knowledge graph. For each foreign cultural element, semantically related Chinese cultural content is searched in the knowledge graph to form candidate cultural pairs. The correlation degree of each candidate cultural pair is calculated, and candidate cultural pairs with correlation degrees exceeding a preset threshold are selected and output as the correlation points, along with an explanation of the correlation generated based on the knowledge graph path.
4. The intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition as described in claim 3, characterized in that: The specific method for dynamically generating personalized cultural experience solutions is as follows: From the aforementioned connection points, the connection point with the highest matching degree with the interest preference dimension in the cultural cognition profile is selected as the core cultural resonance point. Around the core cultural resonance point, a preset activity material library is used to design specific activity units that include cultural education explanations, practical interactive sessions, and emotional guidance points. Using a scene arrangement algorithm, multiple activity units are linked together in a preset logical order to form a coherent experience flow, output a complete experience plan, and use an experience personalization index to evaluate the plan.
5. The intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition as described in claim 1, characterized in that: The specific method for deeply adapting the content provided to tourists to cultural context is as follows: Based on the cultural cognitive profile, the target culture's preset writing style template is matched, the semantic logic of the original text to be adapted is analyzed, and it is reconstructed according to the narrative habits of the target culture. Based on the emotional expression preference dimension in the cultural cognitive profile, the emotional intensity and rhetorical devices of the output text are adjusted. For unique concepts and historical allusions in the source culture, a "translation and interpretation combination" approach is adopted for output.
6. The intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition as described in claim 1, characterized in that: The specific implementation method for providing personalized service responses and interactive support based on tourists' cultural background is as follows: The system receives real-time text, voice, and image interaction data from tourists, extracts emotional feature signals, combines them with the cultural cognition profile, calls the corresponding cultural emotional expression rule library, calibrates the intensity and intent of the original emotional signals in the cultural context, matches communication patterns and solutions from the cultural adaptation strategy library based on the calibrated emotional intent and the current service scenario, generates specific response content based on the matched strategy, and simultaneously adjusts the tone, wording, and non-textual elements of the response text.
7. The intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition as described in claim 1, characterized in that: The method for automatically generating personalized records from tourists' travel data in accordance with their cultural expression habits is as follows: Step 1: Adapting Cultural Narrative Style and Structure: Based on the cultural cognitive profile, match the target culture's preset writing style and narrative structure template; Step 2: Multimodal data fusion and semantic enhancement: Content analysis is performed on tourists' media data. Visual cultural elements are extracted through image recognition technology, and natural language processing technology is used to analyze the associated text metadata to generate intelligent tags rich in cultural interpretation for each piece of media data. Step 3: Personalized Content Generation and Emotional Injection: Based on the style and structure determined in Step 1, and using the intelligent tags generated in Step 2 as key nodes, language is automatically organized to generate a coherent travel narrative text. In the narrative, the intensity and manner of emotional expression are adjusted according to the cultural profile.
8. The intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition as described in claim 1, characterized in that: The specific implementation method for optimizing the personalized records to match the target social culture is as follows: Based on the cultural perception profile of tourists, the mainstream social media platforms of their respective regions are identified. The rules and style knowledge base of these platforms are then used to obtain data on content format, optimal posting time, popular tag types, and user group cultural preferences. Based on the analyzed rules and preferences, the personalized records are adjusted in dimensions to output a complete content package that includes adapted visual materials, optimized copy, and recommended posting tags, as well as suggestions on posting timing.
9. A method for implementing the intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition as described in any one of claims 1-8, characterized in that, include: Step 1: Analyze tourists' cultural background information and construct a multi-dimensional cultural cognition profile; Step 2: Identify the connection points between foreign cultures and Chinese culture through cultural relevance calculation; Step 3: Based on cultural perception profiles, dynamically generate personalized cultural experience plans; Step 4: Provide cross-cultural adapted intelligent customer service and content generation services; Step 5: Automatically generate travel records and sharing content that match the tourist's cultural background; Step 6: Continuously optimize the cultural awareness model and service quality based on tourist feedback.
10. The method of the intelligent cultural tourism integrated service system for foreign tourists based on cross-cultural cognition according to claim 9, characterized in that: The formula for calculating cultural affinity in step 2 is as follows: ； in, Indicating foreign cultural elements, Representing Chinese cultural content, This indicates the degree of cultural relevance between foreign cultural elements and Chinese cultural content. Indicates the first The weight of each cultural dimension The first foreign cultural element Feature values of each cultural dimension The content of Chinese culture Feature values of each cultural dimension Represents the dimensional similarity function. The number representing the cultural dimension. This represents the total number of cultural dimensions.