Digital cultural tourism management system based on multi-source data analysis

Abstract

The invention relates to the technical field of cultural tourism management, and discloses a digital cultural tourism management system based on multi-source data analysis, which comprises a data acquisition module, a data storage module, a data processing module, a data analysis module, an application module, a user management module, an interface module, a safety protection module, a visualization module and a function module. Wherein the data acquisition module is used for collecting data from multiple sources of scenic spot sensors, social media and tourist mobile equipment, providing original data support for system operation, and meeting the characteristics of the system for multi-source data requirements. According to the digital cultural tourism management system based on multi-source data analysis, a plurality of modules of data acquisition, storage, processing, analysis and the like are comprehensively integrated, so that multi-source data of scenic spot sensors, social media, tourist mobile equipment and the like can be effectively fused; the method comprises the steps of accurate data source acquisition, potential value mining after data processing, and diversified service providing for different user groups.

Description

Technical Field

[0001] The present invention relates to the technical field of cultural tourism management, and specifically provides a digital cultural tourism management system based on multi-source data analysis. Background Art

[0002] Digitalization refers to the transformation of traditional physical forms, processes, or information into digital forms for easy storage, processing, transmission, and utilization. The development of digitalization is closely related to the rapid progress of information technology, and it is changing and influencing various fields, including business, education, healthcare, entertainment, and communication. Digitalization makes data collection and analysis more convenient and efficient. Enterprises and organizations can obtain valuable insights through data analysis and mining and make more informed decisions based on these insights.

[0003] Cultural tourism refers to a form of tourism that takes culture as the main destination and tourism experience, emphasizing tourists' understanding, appreciation, and experience of the culture, history, art, customs, and traditions of the destination. The purpose of cultural tourism is to promote cultural exchange, cultural heritage protection, cultural inheritance, and sustainable tourism development through tourism activities.

[0004] With the rapid development of the tourism industry, traditional tourism management methods are difficult to meet the increasingly diverse needs of tourists. At present, although there are some digital cultural tourism management systems based on multi-source data analysis, they have problems such as single functions and insufficient data integration. For example, existing systems cannot accurately combine tourists' real-time locations, historical preferences, and real-time scenic area conditions to provide personalized tourism recommendations, resulting in poor tourist experiences, low scenic area operation efficiency, and restricted development of the tourism industry. Therefore, a digital cultural tourism management system based on multi-source data analysis is proposed to solve the above-mentioned problems. Summary of the Invention

[0005] (1) Technical Problems to be Solved

[0006] In view of the deficiencies of the prior art, the present invention provides a digital cultural tourism management system based on multi-source data analysis, which has the advantages of rich and personalized functions and multi-source data collection and integration, and solves the problems in traditional tourism management that it is difficult for tourists to obtain comprehensive and real-time scenic area information, and it is also difficult for scenic area managers to understand tourists' needs and feedback. Through multi-source data collection and analysis, this system breaks the information barrier, enabling tourists to obtain personalized tourism suggestions and real-time scenic area information, and allowing scenic area managers to deeply understand tourists' needs and scenic area operation conditions.

[0007] (2) Technical Solutions

[0008] In order to achieve the above-mentioned purpose of rich functions and personalization and multi-source data collection and integration, the present invention provides the following technical solutions: a digital cultural tourism management system based on multi-source data analysis, including a data collection module, a data storage module, a data processing module, a data analysis module, an application module, a user management module, an interface module, a security protection module, a visualization module and a functional module; wherein,

[0009] Data collection module: used to collect data from multiple sources such as scenic spot sensors, social media and tourists' mobile devices, providing raw data support for system operation, which meets the characteristics of the system's demand for multi-source data;

[0010] Data storage module: used to store various types of original and analyzed data, ensuring data security and scalability, and is an indispensable part of the system;

[0011] Data processing module: used to clean, convert and store collected data in preparation for subsequent analysis. It is a key step in converting data from its original state to a usable state.

[0012] Data analysis module: used to mine data value using machine learning technology, and is the core link for realizing intelligent decision-making and personalized recommendation functions of the system;

[0013] Application module: used to provide services for tourists, scenic area managers and tourism practitioners. It is a direct reflection of the value of the system and allows different user groups to use the system functions.

[0014] User management module: used to register, log in, authenticate, and assign permissions to different types of users, ensuring system security and user data privacy, and meeting system management requirements;

[0015] Interface module: used to connect with external third-party platforms, expand the scope of services, improve the convenience of tourism services, and meet the comprehensive service needs of the tourism industry;

[0016] Security protection module: It is used to ensure network and data security by adopting various security measures, and prevent attacks and data leakage, which is crucial to the stable operation of the system;

[0017] Visualization module: used to present the analysis results in an intuitive form, making it easier for users to understand the data, assisting scenic area managers in making decisions, and improving user experience;

[0018] Functional module: used to enhance tourists' experience, help scenic spots improve services, and promote the development of tourism.

[0019] Preferably, the functional modules include a personalized recommendation module, an intelligent ticket management module, a scenic spot resource real-time monitoring module and a tourist interaction and feedback module; wherein,

[0020] Personalized Recommendation Module: Based on the historical behavior data of tourists, real-time location, real-time tourist flow in the scenic area, and weather information, provide tourists with personalized travel routes, scenic spot recommendations, and activity recommendations;

[0021] Intelligent Ticketing Management Module: Implement dynamic pricing, adjust ticket prices according to the real-time tourist flow in the scenic area and off-peak / peak season factors. At the same time, support the integration of multiple ticketing sales channels to facilitate tourists to purchase tickets;

[0022] Scenic Area Resource Real-time Monitoring Module: Real-time collect environmental data and facility status data in the scenic area through sensors. Once abnormal situations are detected, such as excessive tourist flow at scenic spots or facility failures, promptly notify the management for handling;

[0023] Tourist Interaction and Feedback Module: Tourists can share their travel experiences, give suggestions and complaints in the system. The system analyzes these feedbacks to provide a basis for the scenic area to improve its services.

[0024] Preferably, the data collection module deploys sensors at key positions in the scenic area, uses infrared induction or image recognition technology to monitor the number of tourists in real-time, regularly collects environmental temperature and humidity data, and at the same time obtains scenic area-related content published by tourists from social media through API interfaces, and guides tourists to download a dedicated application to collect their GPS positioning behavior data.

[0025] Preferably, the data storage module selects a distributed file system, such as Ceph, classifies and stores the original data according to the data source and collection time dimension, uses a relational database MySQL or a NoSQL database MongoDB to store the cleaned and analyzed data, sets the storage policy according to the data importance and access frequency, and performs regular off-site backups.

[0026] Preferably, the interface module is connected to the transportation reservation platforms (Ctrip, Fliggy) through standardized API interfaces to enable tourists to reserve transportation services; connects to the hotel reservation system (Qunar, eLong established) to support tourists to reserve hotels around the scenic area; and is connected to the supervision system of the government tourism management department to regularly upload operation data and tourist flow information.

[0027] Preferably, the security protection module deploys a firewall at the network boundary, uses an intrusion detection system (IDS) and an intrusion prevention system (IPS) to monitor network traffic in real-time, uses the SSL / TLS encryption protocol for data transmission, uses the AES encryption algorithm for storing data, and regularly performs security vulnerability scans and repairs.

[0028] Preferably, an intelligent customer service subsystem is added to the tourist interaction and feedback module in the function module. This system uses natural language processing (NLP) and machine learning technologies to achieve text or voice interaction with tourists, can automatically answer common questions, guide tourists to complete operations, collect tourists' opinions and suggestions, and transfer to human customer service when necessary, improving the tourist service experience.

[0029] Preferably, the data analysis module further includes a predictive analysis sub-module. This sub-module uses time series analysis, regression analysis statistical methods, combined with machine learning algorithms, to predict key indicators such as tourist flow, income, and weather changes in the scenic area, providing decision-making support for scenic area managers.

[0030] Preferably, the predictive analysis sub-module not only predicts the operation data within the scenic area, but also combines external factors such as macroeconomic data, policy changes, and holiday arrangements to build a more comprehensive prediction model.

[0031] (III) Beneficial Effects

[0032] Compared with the prior art, the present invention provides a digital cultural tourism management system based on multi-source data analysis, having the following beneficial effects:

[0033] 1. The digital cultural tourism management system based on multi-source data analysis can effectively integrate multi-source data such as scenic area sensors, social media, and tourists' mobile devices by comprehensively integrating multiple modules such as data collection, storage, processing, and analysis; from the accurate collection of data at the source, to the excavation of its potential value after data processing, and then to providing diverse services for different user groups, realizing various functions of digital cultural tourism management; this not only improves the convenience and experience of tourists during the tourism process, but also significantly improves the operation efficiency of the scenic area, providing strong support for the sustainable development of the tourism industry.

[0034] 2. The digital cultural tourism management system based on multi-source data analysis forms an organic whole through the mutual cooperation and close coordination of each module; during the operation of the system, each module performs its own duties and is interrelated; at the same time, the system has a self-optimization mechanism, collecting tourist feedback information through the tourist interaction and feedback module to evaluate and optimize the system functions and services; the data analysis module will also continuously adjust and optimize the analysis model according to new data and feedback, thereby continuously improving the performance and accuracy of the system, ensuring that the system can always adapt to the changing needs of the tourism market. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] Figure 1 It is a framework diagram of the digital cultural tourism management system based on multi-source data analysis of the present invention;

[0036] Figure 2Schematic diagram of module relationships of the digital cultural tourism management system based on multi-source data analysis according to the present invention;

[0037] Figure 3 Schematic diagram of the relationships between sub-modules within the functional modules in the digital cultural tourism management system based on multi-source data analysis according to the present invention. Detailed implementation manners

[0038] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0039] Please refer to Figures 1-3 , a digital cultural tourism management system based on multi-source data analysis, including a data collection module, a data storage module, a data processing module, a data analysis module, an application module, a user management module, an interface module, a security protection module, a visualization module, and a function module; wherein,

[0040] Data collection module: used to collect data from multiple sources such as scenic area sensors, social media, and tourists' mobile devices, providing raw data support for the operation of the system, and conforming to the characteristics of the system's multi-source data requirements;

[0041] Data storage module: used to store various types of raw and analyzed data, ensuring data security and scalability, and being an essential part of the system;

[0042] Data processing module: used to clean, transform, and store the collected data, preparing it for subsequent analysis, and being a key step for the data to transition from the original state to a usable state;

[0043] Data analysis module: used to utilize machine learning technology to mine the value of data, and being the core link for realizing the intelligent decision-making and personalized recommendation functions of the system;

[0044] Application module: used to provide services for tourists, scenic area managers, and tourism practitioners, being a direct manifestation of the system's value, enabling different user groups to use the system functions;

[0045] User management module: used to register, authenticate logins, and allocate permissions for different types of users, ensuring system security and user data privacy, and conforming to the system management requirements;

[0046] Interface module: used to interface with external third-party platforms, broaden the service scope, enhance the convenience of tourism services, and meet the comprehensive service requirements of the tourism industry;

[0047] Security protection module: It is used to ensure network and data security by adopting various security measures, and prevent attacks and data leakage, which is crucial to the stable operation of the system;

[0048] Visualization module: used to present the analysis results in an intuitive form, making it easier for users to understand the data, assisting scenic area managers in making decisions, and improving user experience;

[0049] Functional module: used to enhance tourists' experience, help scenic spots improve services, and promote the development of tourism.

[0050] It should be noted that this system is mainly composed of data acquisition module, data storage module, data processing module, data analysis module, application module, user management module, interface module, security protection module, visualization module and functional module; each module cooperates with each other to jointly realize the various functions of digital cultural tourism management.

[0051] Specifically, the data acquisition module is the key part of the system to obtain raw data, and collects data from different data sources in a variety of ways;

[0052] Scenic area sensor deployment: Infrared sensors and image recognition equipment are deployed at key locations in scenic areas, such as scenic spot entrances, popular areas, and around facilities. Infrared sensors are used to monitor the number of tourists entering and leaving in real time, and image recognition equipment can identify and analyze tourists' behaviors and movements. At the same time, it regularly collects environmental temperature and humidity data in the scenic area to provide a basis for the scenic area's environmental management and tourist comfort assessment.

[0053] Social media data acquisition: With the help of API interfaces, we can connect with major social media platforms to obtain the content related to the scenic spot posted by tourists in real time, including photos, text descriptions, and comments. These data can reflect tourists' real-time feelings and feedback on the scenic spot, which helps the scenic spot to understand tourists' needs and opinions in a timely manner;

[0054] Collection of data from tourists’ mobile devices: By guiding tourists to download exclusive applications, their GPS location information, browsing history, and dwell time behavior data are collected. These data can be used to analyze tourists’ travel routes and interest preferences, providing strong support for personalized recommendations.

[0055] Specifically, the data storage module is responsible for storing various types of raw and analyzed data to ensure data security and scalability;

[0056] Raw data storage: Use the distributed file system Ceph to classify and store raw data according to the data source and collection time dimensions. This storage method can improve data storage efficiency and reliability, and facilitate subsequent data retrieval and management.

[0057] Processed data storage: Use a relational database MySQL or a NoSQL database MongoDB to store the cleaned and analyzed data. Set different storage strategies according to the importance and access frequency of the data. For frequently accessed data, it can be stored in high-speed storage devices to improve the data reading speed. At the same time, perform off-site backups regularly to prevent data loss and damage.

[0058] Specifically, the data processing module is a key step in converting raw data into usable data, mainly including data cleaning, transformation, and storage.

[0059] Data cleaning: Use data cleaning tools to perform deduplication, error correction, and filling of missing values on the collected data. For example, for abnormal data collected by sensors, compare and analyze it with historical data to correct or eliminate it; for text data on social media, remove noise and useless information to improve the data quality.

[0060] Data transformation: Transform data in different formats and types to meet the requirements of subsequent analysis. For example, convert unstructured text data into structured data for data analysis and mining; standardize data with different units and scales to eliminate differences between data.

[0061] Data storage: Store the processed data in the corresponding database to provide support for subsequent data analysis.

[0062] Specifically, the data analysis module is the core part of the system. It uses machine learning techniques to mine data value and realizes intelligent decision-making and personalized recommendation functions.

[0063] Predictive analysis sub-module: Use time series analysis, regression analysis, and other statistical methods, combined with machine learning algorithms, to predict key indicators such as scenic spot tourist flow, income, and weather changes; not only consider the internal operation data of the scenic spot, but also combine external factors such as macroeconomic data, policy changes, and holiday arrangements to build a more comprehensive prediction model; for example, by analyzing historical tourist flow data and holiday information, predict the tourist flow during future holidays to provide decision-making support for the resource allocation and operation management of the scenic spot.

[0064] Personalized recommendation analysis: According to the historical behavior data, real-time location of tourists, and the real-time tourist flow and weather information of the scenic spot, use collaborative filtering algorithms and content recommendation algorithms to provide tourists with personalized travel routes, scenic spot recommendations, and activity recommendations; for example, for tourists who like natural scenery, recommend natural landscape scenic spots and related outdoor activities in the scenic spot; for tourists who like culture and history, recommend historical sites and cultural exhibitions.

[0065] Specifically, the application module is a direct manifestation of the system's value, providing different services for tourists, scenic area managers, and tourism practitioners;

[0066] Tourist services: Provide personalized travel recommendations, ticket reservations, transportation and hotel reservations, and real-time navigation services for tourists. Tourists can conveniently obtain these services through the exclusive application, improving the convenience and experience of travel;

[0067] Scenic area manager services: Provide statistical analysis of scenic area operation data, tourist flow prediction, and facility maintenance management services for scenic area managers; Scenic area managers can understand the operation status of the scenic area in real time through the visual interface and make scientific decisions;

[0068] Tourism practitioner services: Provide tourism product promotion, market analysis, and customer relationship management services for tourism practitioners.

[0069] Specifically, the user management module is responsible for registering, authenticating logins, and assigning permissions to different types of users, ensuring the security of the system and the privacy of user data;

[0070] User registration and login: Support tourists, scenic area managers, and tourism practitioners to register and log in via mobile phone numbers and email; Adopt SMS verification codes and password encryption technology to ensure the security of user logins;

[0071] Permission assignment: Assign different permissions according to the type and role of the user; For example, tourists can only view and use services related to their own travel; Scenic area managers can manage and analyze the operation data of the scenic area; Tourism practitioners can publish and manage tourism product information.

[0072] Specifically, the interface module realizes the docking with external third-party platforms, expands the service scope, and improves the convenience of tourism services;

[0073] Docking with transportation reservation platforms: Docking with transportation reservation platforms such as Ctrip and Fliggy through standardized API interfaces to enable tourists to directly book transportation services within this system, such as air tickets, train tickets, and bus tickets;

[0074] Docking with hotel reservation systems: Establish connections with hotel reservation systems such as Qunar and eLong to support tourists to book hotels near scenic areas, providing more accommodation options;

[0075] Docking with the government tourism management department's supervision system: Regularly upload the operation data of scenic areas and tourist flow information to the government tourism management department's supervision system to accept the supervision and guidance of government departments.

[0076] Specifically, the security protection module uses a variety of security means to ensure the security of the network and data, preventing attacks and data leaks;

[0077] Network security protection: Deploy a firewall at the network boundary to prevent external illegal access; use an Intrusion Detection System (IDS) and an Intrusion Prevention System (IPS) to monitor network traffic in real time, and detect and prevent network attack behaviors in a timely manner;

[0078] Data encrypted transmission: During the data transmission process, use the SSL / TLS encryption protocol to encrypt the data to ensure the security and integrity of the data during transmission;

[0079] Data encrypted storage: Use the AES encryption algorithm to encrypt the stored data to prevent the data from being stolen and tampered with during storage; at the same time, conduct security vulnerability scans and repairs regularly to detect and solve potential security problems in a timely manner.

[0080] Specifically, the visualization module presents the analysis results to the user in an intuitive form, facilitating the user to understand the data and assisting the scenic area manager in making decisions;

[0081] Data visualization display: Use chart, report, and map visualization methods to display the data of the tourist flow, income, and facility usage in the scenic area; for example, display the changes in tourist flow in different time periods through a bar chart, and display the real-time tourist distribution of each scenic spot in the scenic area through a map;

[0082] Decision-making assistance analysis: Provide the scenic area manager with a visual display of the data analysis and prediction results, helping them intuitively understand the operation status and development trend of the scenic area and make scientific decisions; for example, display the tourist flow prediction in a future period through a trend chart, providing a reference for the resource allocation and marketing activities of the scenic area.

[0083] The implementation process includes the following steps:

[0084] Step 1: The data collection module collects data from multiple sources such as scenic area sensors, social media, and tourist mobile devices in the above manner, and transmits the data to the data storage module for storage;

[0085] Step 2: The data processing module obtains the original data from the data storage module, performs cleaning, transformation, and storage, and stores the processed data in the corresponding database;

[0086] Step 3: The data analysis module obtains the processed data from the data storage module, uses machine learning technology for analysis and mining, and generates analysis results and prediction models;

[0087] Step 4: The application module calls the analysis results of the data analysis module and the prediction model according to the needs of different users to provide corresponding services for tourists, scenic area managers, and tourism practitioners. At the same time, the user management module manages user registration, login, and permissions. The interface module realizes the connection with external third-party platforms. The security protection module ensures the secure operation of the system. The visualization module presents the analysis results to users in an intuitive form. The function module enhances the experience of tourists and the service quality of scenic areas.

[0088] Step 5: The tourist interaction and feedback module collects feedback information from tourists to evaluate and optimize the functions and services of the system. At the same time, the data analysis module continuously adjusts and optimizes the analysis model according to new data and feedback information to improve the performance and accuracy of the system.

[0089] Through the above settings, this system can effectively integrate multi-source data, realize various functions of digital cultural tourism management, improve the experience of tourists and the operation efficiency of scenic areas, and promote the sustainable development of the tourism industry.

[0090] In summary, the digital cultural tourism management system based on multi-source data analysis can effectively integrate multi-source data such as scenic area sensors, social media, and tourists' mobile devices by comprehensively integrating multiple modules including data collection, storage, processing, and analysis. From the precise collection of data at the source, to the excavation of its potential value after data processing, and then to the provision of diverse services for different user groups, it realizes various functions of digital cultural tourism management. This not only improves the convenience and experience of tourists during the tourism process but also significantly enhances the operation efficiency of scenic areas, providing strong support for the sustainable development of the tourism industry.

[0091] Moreover, through the mutual cooperation and close coordination of each module, an organic whole is formed. During the operation of the system, each module performs its own duties and is interrelated. At the same time, the system has a self-optimization mechanism. The tourist interaction and feedback module collects tourist feedback information to evaluate and optimize the system functions and services. The data analysis module also adjusts and optimizes the analysis model continuously according to new data and feedback, thereby continuously improving the performance and accuracy of the system to ensure that the system can always adapt to the changing needs of the tourism market.

[0092] It should be noted that, in this document, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprising", "including" or any other variant thereof are intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also includes other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element limited by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the said element.

[0093] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention, and the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A digital cultural tourism management system based on multi-source data analysis, characterized by: It includes data acquisition module, data storage module, data processing module, data analysis module, application module, user management module, interface module, security protection module, visualization module and functional module; among them, Data collection module: used to collect data from multiple sources such as scenic spot sensors, social media and tourists' mobile devices, providing raw data support for system operation, which meets the characteristics of the system's demand for multi-source data; Data storage module: used to store various types of original and analyzed data, ensuring data security and scalability, and is an indispensable part of the system; Data processing module: used to clean, convert and store collected data in preparation for subsequent analysis. It is a key step in converting data from its original state to a usable state. Data analysis module: used to mine data value using machine learning technology, and is the core link for realizing intelligent decision-making and personalized recommendation functions of the system; Application module: used to provide services for tourists, scenic area managers and tourism practitioners. It is a direct reflection of the value of the system and allows different user groups to use the system functions. User management module: used to register, log in, authenticate, and assign permissions to different types of users, ensuring system security and user data privacy, and meeting system management requirements; Interface module: used to connect with external third-party platforms, expand the scope of services, improve the convenience of tourism services, and meet the comprehensive service needs of the tourism industry; Security protection module: It is used to ensure network and data security by adopting various security measures, and prevent attacks and data leakage, which is crucial to the stable operation of the system; Visualization module: used to present the analysis results in an intuitive form, making it easier for users to understand the data, assisting scenic area managers in making decisions, and improving user experience; Functional module: used to enhance tourists' experience, help scenic spots improve services, and promote the development of tourism.

2. According to claim 1, a digital cultural tourism management system based on multi-source data analysis is characterized by: The functional modules include a personalized recommendation module, an intelligent ticket management module, a scenic spot resource real-time monitoring module, and a tourist interaction and feedback module; Personalized recommendation module: Provides personalized travel routes, scenic spots and activities for tourists based on their historical behavior data, real-time location, and real-time tourist traffic and weather information of scenic spots; Intelligent ticket management module: realizes dynamic pricing, adjusts ticket prices according to the real-time tourist flow of scenic spots and factors such as off-season and peak season, and supports the integration of multiple ticket sales channels to facilitate tourists to purchase tickets; Real-time monitoring module for scenic area resources: collects environmental data and facility status data in the scenic area in real time through sensors. Once an abnormal situation is found, such as excessive flow of visitors to the scenic spot or facility failure, the manager will be notified in time for processing; Visitor interaction and feedback module: Visitors can share their travel experiences, make suggestions and complaints in the system. The system will analyze these feedbacks and provide a basis for scenic spots to improve their services.

3. According to claim 1, a digital cultural tourism management system based on multi-source data analysis is characterized by: The data collection module deploys sensors at key locations in the scenic area, uses infrared sensing or image recognition technology to monitor the number of tourists in real time, collects environmental temperature and humidity data at regular intervals, and uses the API interface to obtain scenic area-related content posted by tourists from social media, guiding tourists to download exclusive applications to collect their GPS positioning behavior data.

4. According to claim 1, a digital cultural tourism management system based on multi-source data analysis is characterized by: The data storage module uses a distributed file system, such as Ceph, to store raw data by data source and collection time, and uses a relational database MySQL or a NoSQL database MongoDB to store cleaned and analyzed data. Storage strategies are set based on data importance and access frequency, and regular off-site backup is performed.

5. According to claim 1, a digital cultural tourism management system based on multi-source data analysis is characterized by: The interface module is connected to the transportation booking platform (Ctrip, Fliggy) through a standardized API interface to enable tourists to book transportation services; it is connected to the hotel reservation system (established by Qunar and eLong) to support tourists to book hotels around scenic spots; and it is connected to the supervision system of the government tourism management department to regularly upload operation data and tourist flow information.

6. According to claim 1, a digital cultural tourism management system based on multi-source data analysis is characterized by: The security protection module deploys a firewall at the network boundary, uses an intrusion detection system (IDS) and an intrusion prevention system (IPS) to monitor network traffic in real time, uses the SSL / TLS encryption protocol for data transmission, uses the AES encryption algorithm for stored data, and regularly scans and repairs security vulnerabilities.

7. According to claim 2, a digital cultural tourism management system based on multi-source data analysis is characterized by: The tourist interaction and feedback module in the functional module has added an intelligent customer service subsystem, which uses natural language processing (NLP) and machine learning technology to achieve text or voice interaction with tourists. It can automatically answer common questions, guide tourists to complete operations, collect tourists' opinions and suggestions, and transfer to manual customer service when necessary, thereby improving the tourist service experience.

8. According to claim 1, a digital cultural tourism management system based on multi-source data analysis is characterized by: The data analysis module further includes a prediction analysis submodule, which uses time series analysis and regression analysis statistical methods combined with machine learning algorithms to predict key indicators of scenic spot tourist flow, income, and weather changes, providing decision support for scenic spot managers.

9. A digital cultural tourism management system based on multi-source data analysis according to claim 8, characterized in that: The forecasting and analysis submodule not only forecasts the internal operational data of the scenic spot, but also combines external factors such as macroeconomic data, policy changes, and holiday arrangements to build a more comprehensive forecasting model.

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