Trout big data evaluation system and method

Abstract

The invention, which relates to the technical field of travel big data evaluation, discloses a travel big data evaluation system comprising a tourist attraction supporting facility evaluation module, a social media big data evaluation module, a miraculous degree module and a comprehensive scoring module. The invention also discloses a travel big data evaluation method. The method comprises the following steps: collecting scenic spot data; cleaning and standardizing the collected data, and performing hierarchical scoring; analyzing the processed data to generate a comprehensive score; and the generated score and analysis result are fed back to the scenic spot and the travel management department, and optimization suggestions and improvement schemes are provided. According to the invention, on the basis of social media data, the service quality, environmental protection and tourist experience of tourist attractions and cultural projects can be monitored in real time, dynamic feedback is provided through a scientific evaluation system and a big data analysis model, the tourist service quality is improved, the international competitiveness of cultural tourist resources is enhanced, and support is provided for the development of the cultural industry.

Description

Technical Field

[0001] The present invention relates to the technical field of cultural tourism big data evaluation, and in particular to a cultural tourism big data evaluation system and method. Background Art

[0002] In recent years, the cultural tourism industry has flourished globally, especially in China, where tourism market demand has continued to grow. National and local governments have introduced policies to promote the high-quality development of the cultural tourism industry. Against this background, how to scientifically and systematically evaluate and improve the service level, cultural value and comprehensive attractiveness of tourist attractions has become an important issue for cultural and tourism management departments. As a major tourist province with rich historical and cultural resources, Shaanxi Province urgently needs to establish a cultural and tourism big data evaluation system that adapts to modern tourism needs, so as to enhance the competitiveness of its cultural and tourism resources and brand influence in domestic and foreign markets.

[0003] Traditional tourism evaluation systems mostly rely on policy indicators and manual surveys. The conventional data collection channels and evaluation methods are relatively simple, resulting in a lack of real-time and comprehensive evaluation results. It is difficult to fully and accurately reflect tourists' real-time feedback and service experience on scenic spots. At the same time, due to the failure to effectively introduce multi-source data such as social media data, online platform ratings and tourists' dynamic feedback, the traditional system has obvious deficiencies in tourist satisfaction, the degree of refinement of scenic spot evaluation and data objectivity, and it is difficult to adapt to the current rapidly changing tourism market demand and changes in tourist behavior. Summary of the invention

[0004] In order to solve the above technical problems, a cultural tourism big data evaluation system and method are provided. This technical solution solves the above problems.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is: A cultural tourism big data evaluation system, comprising: Tourist attractions supporting facilities evaluation module: used to evaluate the supporting facilities indicators of tourist attractions, including transportation, safety, guide information, sanitation, communication and tourist services; Social media big data evaluation module: The social media big data evaluation module is electrically connected to the tourist scenic spot supporting facilities evaluation module, and the social media big data evaluation module is used to analyze tourists' satisfaction with each scenic spot, including ticket purchase channels, shopping venue construction, popularity and OTA ratings; Spectacle degree module: the spectacle degree module is electrically connected to the social media big data evaluation module, and the spectacle degree module is used to quantitatively analyze the spectacle degree of the scenic spot from the aspects of historical and cultural value, scientific and educational value, aesthetic value, natural resource value and leisure and entertainment value; Comprehensive scoring module: The comprehensive scoring module is electrically connected to the spectacle degree module. The comprehensive scoring module is used to generate a comprehensive score based on the evaluation results of the above modules to provide a decision-making basis for scenic spots and management departments.

[0006] Preferably, the tourist attraction supporting facilities evaluation module specifically includes: Transportation facilities assessment unit: assess the degree of connection between the main transportation routes around the scenic area and the scenic area, check the convenience, frequency and time of public transportation to the scenic area, assess the capacity and convenience of transportation hubs around the scenic area, and evaluate the distance between the scenic area and major cities and the required travel time; In-park traffic assessment unit: assess the traffic facilities within the scenic area, including the availability and comfort of electric cars, sightseeing cars, trails and cable cars, check the clarity and orientation of traffic signs within the park, and check the safety and operation and maintenance of traffic facilities; Traffic safety assessment unit: Check the safety facilities of traffic facilities, assess whether the traffic safety management and emergency response mechanism of the scenic area are complete, check whether the scenic area is equipped with closed-circuit television monitoring, alarm system and emergency call equipment, and assess the coverage and real-time performance of the monitoring equipment; Health Facility Assessment Unit: Assess the number, distribution and sanitary conditions of public health facilities in the scenic area, including the cleanliness and completeness of public toilets, restrooms and toilets; check the number, distribution and frequency of garbage bins in the scenic area; and assess whether the scenic area has adopted environmental protection measures, including garbage classification and green environmental protection policies; Catering hygiene and cleanliness: Evaluate the hygiene standards of catering service points in scenic areas, including food safety, dining environment and food hygiene management; Tourist service facilities assessment unit: assess the number, location and service quality of tourist reception centers and tourist service desks in the scenic area, and check whether there are staff at the tourist reception desk to provide consultation, answers and emergency assistance services; Analysis result display unit: The scores of each dimension are combined to obtain the overall safety score of the supporting facilities of the tourist attraction.

[0007] Preferably, the social media big data evaluation module specifically includes: Ticket purchasing system evaluation unit: evaluates whether the scenic spot's ticket purchasing and admission system is complete based on the scenic spot's ticket purchasing channels, time-sharing reservation functions, and ticket types; Shopping Places Evaluation Unit: Evaluate the shopping facilities in the scenic area in terms of layout, aesthetics and management level of the shopping places; Tourist Satisfaction Evaluation Unit: Conduct satisfaction evaluation on scenic spots based on OTA platform ratings and tourist feedback; Analysis result display unit: The scores of each dimension are combined to obtain the total score of social media big data evaluation.

[0008] Preferably, the spectacle degree module specifically includes: Data collection and collation unit: collect historical documents, sites, cultural heritage, historical events and personal information related to the scenic spot, and obtain the historical and cultural background of the scenic spot through the research results of historians and archaeologists, local chronicles and cultural heritage data sources; Collect data on popular science education resources, scientific research facilities, natural phenomena and scientific research activities in the scenic area, and collect information on natural landscapes, architectural styles, artworks and cultural and creative products, sculptures and landscape designs in the scenic area; Collect information on the natural resources of the scenic area, including geology, landforms, climate, plant and animal diversity, and water resources; Collect data on natural resources of scenic spots through environmental protection departments and ecological research institutions, as well as data on recreational facilities, leisure activities and visitor participation provided by scenic spots; Index system design unit: According to the characteristics of the scenic spot and the needs of the target tourist groups, determine the evaluation indicators of each dimension, set weights for each dimension, weight them according to the characteristics of the scenic spot, design qualitative indicators for each dimension, set standardized evaluation standards, and use numerical methods to quantify the scores of each indicator; Analysis result display unit: The scores of each dimension are combined to obtain a spectacle score.

[0009] Preferably, the comprehensive scoring module specifically includes: Data collection and integration unit: collects scoring data from each evaluation module, cleans the data, removes duplicates, fills in missing values, and integrates the data of all evaluation modules into a unified format; Standardization processing unit: standardize the score values ​​of different modules to make them within a unified score range. The standardization formula is:

[0010] In the formula, is the original score, and The minimum and maximum values ​​for the module score. is the value after standardization; Weight allocation unit: Assign weights to each module according to its importance, and weight the scores of each module to obtain a comprehensive score. Determine the weight of each module based on the expert opinions and the scoring results analyzed from historical data. Multiply the standardized score of each module by its weight to obtain a weighted score. The weighted score calculation formula is:

[0011] In the formula, is the weighted score, For the Standardized scoring for each module, For the The weight of each module, is the total number of assessment modules; Analysis and presentation of scoring results: Scenic spots are divided into different levels according to the comprehensive scores, and the scoring range is set, including high scores of 90 to 100 points for excellent scenic spots, medium and high scores of 70 to 89 points for good scenic spots, medium scores of 50 to 69 points for general scenic spots, and low scores of 0 to 49 points for scenic spots that need improvement; Use charts to present each assessment module and the overall score.

[0012] Specifically, the wonder degree module integrates the cultural, historical and natural attributes of various cultural and tourism resources, and is evaluated specifically through popularity (10%), honors received (5%), scarcity of scenic spots (10%), and value of scenic spots (75%). The popularity module is quantified by comparing sample scenic spots. For example, the Terracotta Warriors and Horses Scenic Spot has a popularity score of 100 points, while the Mausoleum of the Yellow Emperor and Mount Hua have a popularity score of 90 points. The honors received module is measured by breakthroughability. If it can be broken through, it will be 100 points, and if it cannot be broken through, it will be 200 points. If it is a world heritage site, 20 points will be added. The scenic spot value module first divides the scenic spot into 7 major categories. The detailed weights of each category of scenic spots are different. They are quantified through historical and cultural value, scientific and educational value, aesthetic value, natural resource value, and leisure and entertainment value to form a quantitative analysis model of wonder characteristics suitable for different types of scenic spots.

[0013] A cultural tourism big data evaluation method, comprising: S1: Collect evaluation data about scenic spots from tourism-related social media platforms, including tourist feedback and rating data; S2: Clean and standardize the collected data, and stratify and score them according to supporting facilities, visitor satisfaction and spectacle indicators; S3: Analyze the processed data based on various indicator models in the cultural tourism big data evaluation system to generate a comprehensive score; S4: Feedback the generated scoring and analysis results to scenic spots and cultural tourism management departments to provide optimization suggestions and improvement plans.

[0014] Preferably, the S1 specifically includes: Identify data sources, including social media, travel review websites, and tourism bureau statistics, and define collection objectives; Collect data based on API interface, set collection time period, update regularly, deduplicate data, filter spam information, analyze sentiment, store and manage data.

[0015] Preferably, the S2 specifically includes: Delete duplicate comments and ratings, and use the mean filling method to fill in missing ratings and comments; Unify the rating systems used by different platforms, use natural language processing technology for sentiment analysis, convert text comments into a unified sentiment score, and ensure that all data has a unified timestamp format; Scenic spots are graded in different levels based on different evaluation dimensions and indicators, including supporting facilities scores, visitor satisfaction scores, spectacular scores, service quality scores, and environment and cleanliness scores.

[0016] Preferably, the S3 specifically includes: Assign weights to each dimension and indicator, perform weighted aggregation based on the weights and scoring results of each indicator, and generate a comprehensive score for each scenic spot; According to the comprehensive scoring results, scenic spots are usually divided into different levels: excellent, good, medium and poor; Sort all scenic spots by comprehensive scores to form a ranking, and visualize the analysis results in the form of charts; Comprehensive analysis report: Generate a detailed analysis report, summarizing the comprehensive score of each scenic spot, the analysis results of each dimension, and the summary of advantages and disadvantages.

[0017] Preferably, the S4 specifically includes: According to the scoring results, specific improvement suggestions are customized for each scenic spot, including: Suggestions at the dimension level: Based on the performance of different dimensions, optimization measures are proposed respectively: Improve service quality: optimize staff training, strengthen visitor reception process, and improve service attitude; Facility improvement: update scenic area facilities, add barrier-free facilities and improve sanitary facilities; Improve visitor experience: increase interactive projects, enrich cultural activities and improve scenic area guide system; Environmental protection: Strengthen environmental protection measures in scenic areas, increase environmental protection facilities and improve greening levels; Transportation and safety: Improve transportation convenience, increase parking spaces, optimize public transportation connections, strengthen safety guarantees, and increase security personnel.

[0018] Compared with the prior art, the present invention has the following beneficial effects: The present invention proposes to utilize the collaborative work of multiple modules. Through detailed evaluation and comprehensive scoring of various aspects of the scenic spot, it can provide accurate data support for scenic spot managers, help scenic spots improve service quality, optimize resource allocation, and enhance the overall satisfaction of tourists. In addition, the system also provides a strong decision-making basis for cultural and tourism management departments, promotes the healthy development of the industry, and realizes the refinement and sustainability of scenic spot management. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 It is a system framework diagram of the present invention; Figure 2 It is a flow chart of the steps of the present invention. DETAILED DESCRIPTION

[0020] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0021] Reference Figure 1 As shown, a cultural tourism big data evaluation system includes: Evaluation module of supporting facilities in tourist attractions: Transportation facilities assessment unit: assess the degree of connection between the main transportation routes around the scenic area and the scenic area, check the convenience, frequency and time of public transportation to the scenic area, assess the capacity and convenience of transportation hubs around the scenic area, and evaluate the distance between the scenic area and major cities and the required travel time; In-park traffic assessment unit: assess the traffic facilities within the scenic area, including the availability and comfort of electric cars, sightseeing cars, trails and cable cars, check the clarity and orientation of traffic signs within the park, and check the safety and operation and maintenance of traffic facilities; Traffic safety assessment unit: Check the safety facilities of traffic facilities, assess whether the traffic safety management and emergency response mechanism of the scenic area are complete, check whether the scenic area is equipped with closed-circuit television monitoring, alarm system and emergency call equipment, and assess the coverage and real-time performance of the monitoring equipment; Health Facility Assessment Unit: Assess the number, distribution and sanitary conditions of public health facilities in the scenic area, including the cleanliness and completeness of public toilets, restrooms and toilets; check the number, distribution and frequency of garbage bins in the scenic area; and assess whether the scenic area has adopted environmental protection measures, including garbage classification and green environmental protection policies; Catering hygiene and cleanliness: Evaluate the hygiene standards of catering service points in scenic areas, including food safety, dining environment and food hygiene management; Tourist service facilities assessment unit: assess the number, location and service quality of tourist reception centers and tourist service desks in the scenic area, and check whether there are staff at the tourist reception desk to provide consultation, answers and emergency assistance services; Analysis result display unit: The scores of each dimension are combined to obtain the overall safety score of the supporting facilities of the tourist attraction.

[0022] Social media big data evaluation module: Ticket purchasing system evaluation unit: evaluates whether the scenic spot's ticket purchasing and admission system is complete based on the scenic spot's ticket purchasing channels, time-sharing reservation functions, and ticket types; Shopping Places Evaluation Unit: Evaluate the shopping facilities in the scenic area in terms of layout, aesthetics and management level of the shopping places; Tourist Satisfaction Evaluation Unit: Conduct satisfaction evaluation on scenic spots based on OTA platform ratings and tourist feedback; Analysis result display unit: The scores of each dimension are combined to obtain the total score of social media big data evaluation.

[0023] Wonder degree module: Data collection and collation unit: collect historical documents, sites, cultural heritage, historical events and personal information related to the scenic spot, and obtain the historical and cultural background of the scenic spot through the research results of historians and archaeologists, local chronicles and cultural heritage data sources; Collect data on popular science education resources, scientific research facilities, natural phenomena and scientific research activities in the scenic area, and collect information on natural landscapes, architectural styles, artworks and cultural and creative products, sculptures and landscape designs in the scenic area; Collect information on the natural resources of the scenic area, including geology, landforms, climate, plant and animal diversity, and water resources; Collect data on natural resources of scenic spots through environmental protection departments and ecological research institutions, as well as data on recreational facilities, leisure activities and visitor participation provided by scenic spots; Index system design unit: According to the characteristics of the scenic spot and the needs of the target tourist groups, determine the evaluation indicators of each dimension, set weights for each dimension, weight them according to the characteristics of the scenic spot, design qualitative indicators for each dimension, set standardized evaluation standards, and use numerical methods to quantify the scores of each indicator; Analysis result display unit: The scores of each dimension are combined to obtain a spectacle score.

[0024] Comprehensive scoring module: Data collection and integration unit: collects scoring data from each evaluation module, cleans the data, removes duplicates, fills in missing values, and integrates the data of all evaluation modules into a unified format; Standardization processing unit: standardize the score values ​​of different modules to make them within a unified score range. The standardization formula is:

[0025] In the formula, is the original score, and The minimum and maximum values ​​for the module score. is the value after standardization; Weight allocation unit: Assign weights to each module according to its importance, and weight the scores of each module to obtain a comprehensive score. Determine the weight of each module based on the expert opinions and the scoring results analyzed from historical data. Multiply the standardized score of each module by its weight to obtain a weighted score. The weighted score calculation formula is:

[0026] In the formula, is the weighted score, For the Standardized scoring for each module, For the The weight of each module, is the total number of assessment modules; The weight of each indicator will be dynamically adjusted according to the evaluation, and the objective evaluation (indicator system) and the user's subjective evaluation will be synchronized.

[0027] Analysis and presentation of scoring results: Scenic spots are divided into different levels according to the comprehensive scores, and the scoring range is set, including high scores of 90 to 100 points for excellent scenic spots, medium and high scores of 70 to 89 points for good scenic spots, medium scores of 50 to 69 points for general scenic spots, and low scores of 0 to 49 points for scenic spots that need improvement; Use charts to present each assessment module and the overall score.

[0028] Reference Figure 2 As shown, a cultural tourism big data evaluation method includes: S1: Identify data sources, including social media, travel review websites, and tourism bureau statistics, and define collection objectives; Collect data based on API interface, set collection time period, update regularly, deduplicate data, filter spam information, analyze sentiment, store and manage data.

[0029] S2: Delete duplicate comments and ratings, and use the mean filling method to fill in missing ratings and comments; Unify the rating systems used by different platforms, use natural language processing technology for sentiment analysis, convert text comments into a unified sentiment score, and ensure that all data has a unified timestamp format; Scenic spots are graded in different levels based on different evaluation dimensions and indicators, including supporting facilities scores, visitor satisfaction scores, spectacular scores, service quality scores, and environment and cleanliness scores.

[0030] S3: Assign weights to each dimension and indicator, perform weighted aggregation based on the weights and scoring results of each indicator, and generate a comprehensive score for each scenic spot; According to the comprehensive scoring results, scenic spots are usually divided into different levels: excellent, good, medium and poor; Sort all scenic spots by comprehensive scores to form a ranking, and visualize the analysis results in the form of charts; Comprehensive analysis report: Generate a detailed analysis report, summarizing the comprehensive score of each scenic spot, the analysis results of each dimension, and the summary of advantages and disadvantages.

[0031] S4: According to the scoring results, specific improvement suggestions are customized for each scenic spot, including: Suggestions at the dimension level: Based on the performance of different dimensions, optimization measures are proposed respectively: Improve service quality: optimize staff training, strengthen visitor reception process, and improve service attitude; Facility improvement: update scenic area facilities, add barrier-free facilities and improve sanitary facilities; Improve visitor experience: increase interactive projects, enrich cultural activities and improve scenic area guide system; Environmental protection: Strengthen environmental protection measures in scenic areas, increase environmental protection facilities and improve greening levels; Transportation and safety: Improve transportation convenience, increase parking spaces, optimize public transportation connections, strengthen safety guarantees, and increase security personnel.

[0032] In summary, the advantages of the present invention are: Through big data and intelligent analysis, the system can accurately and objectively evaluate the services and facilities of scenic spots, help scenic spot managers identify existing problems, and propose effective improvement measures. The multi-dimensional evaluation system provides comprehensive operational data support for scenic spots, avoids one-sided evaluation of a single dimension, and improves the scientific nature of decision-making; Through in-depth analysis of tourist feedback, scenic spots can understand tourists’ needs and dissatisfaction in real time, adjust and optimize services in a timely manner, and ensure tourists’ overall satisfaction; By optimizing supporting facilities, transportation convenience, sanitary conditions and other aspects, scenic spots can provide a more comfortable and safer tourism experience; Quantitative analysis of the degree of wonder can help scenic spots to rationally utilize and protect historical culture, natural landscape and other resources, and promote the sustainable development of cultural and ecological tourism; The optimization suggestions provided by the system can not only improve the service quality of scenic spots, but also promote the active efforts of scenic spots in environmental protection, resource conservation, etc. Scenic spots and cultural tourism management departments can formulate optimization strategies based on comprehensive scores and analysis results of various dimensions, so that resource allocation is more scientific and reasonable; Through the visualization of data, managers can see the scores of scenic spots at a glance and take quick action; Through the evaluation and ranking of multiple scenic spots, the cultural and tourism management department can identify the advantages and disadvantages of scenic spots in the industry, promote the improvement of industry standards and the creation of regional tourism brands, provide industry trend analysis, help scenic spots grasp changes in market demand and tourist preferences, and make strategic plans for future development; The comprehensive analysis report generated by the system provides scientific and objective evaluation data for cultural and tourism management departments, supports policy formulation and industry supervision, and promotes the healthy development of the cultural and tourism industry.

[0033] The above shows and describes 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 above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A cultural tourism big data evaluation system, characterized in that: include: Tourist attractions supporting facilities evaluation module: used to evaluate the supporting facilities indicators of tourist attractions, including transportation, safety, guide information, sanitation, communication and tourist services; Social media big data evaluation module: The social media big data evaluation module is electrically connected to the tourist scenic spot supporting facilities evaluation module, and the social media big data evaluation module is used to analyze tourists' satisfaction with each scenic spot, including ticket purchase channels, shopping venue construction, popularity and OTA ratings; Spectacle degree module: the spectacle degree module is electrically connected to the social media big data evaluation module, and the spectacle degree module is used to quantitatively analyze the spectacle degree of the scenic spot from the aspects of historical and cultural value, scientific and educational value, aesthetic value, natural resource value and leisure and entertainment value; Comprehensive scoring module: The comprehensive scoring module is electrically connected to the spectacle degree module. The comprehensive scoring module is used to generate a comprehensive score based on the evaluation results of the above modules to provide a decision-making basis for scenic spots and management departments.

2. A cultural tourism big data evaluation system according to claim 1, characterized in that: The tourist attraction supporting facilities evaluation module specifically includes: Transportation facilities assessment unit: assess the degree of connection between the main transportation routes around the scenic area and the scenic area, check the convenience, frequency and time of public transportation to the scenic area, assess the capacity and convenience of transportation hubs around the scenic area, and evaluate the distance between the scenic area and major cities and the required travel time; In-park traffic assessment unit: assess the traffic facilities within the scenic area, check the clarity and orientation of the traffic signs within the park, and check the safety and operation and maintenance of the traffic facilities; Traffic safety assessment unit: inspect the safety facilities of traffic facilities and assess whether the traffic safety management and emergency response mechanism of the scenic area are complete; Sanitation Facility Assessment Unit: Assess the number, distribution and sanitary conditions of public health facilities in the scenic area, check the number, distribution and frequency of garbage removal of garbage bins in the scenic area, and assess whether the scenic area has adopted environmental protection measures, including garbage classification and green environmental protection policies; Tourist service facilities assessment unit: assess the number, location and service quality of tourist reception centers and tourist service desks in the scenic area, and check whether there are staff at the tourist reception desk to provide consultation, answers and emergency assistance services; Analysis result display unit: The scores of each dimension are combined to obtain the overall safety score of the supporting facilities of the tourist attraction.

3. A cultural tourism big data evaluation system according to claim 2, characterized in that: The social media big data evaluation module specifically includes: Ticket purchasing system evaluation unit: evaluates whether the scenic spot's ticket purchasing and admission system is complete based on the scenic spot's ticket purchasing channels, time-sharing reservation functions, and ticket types; Shopping Places Evaluation Unit: Evaluate the shopping facilities in the scenic area in terms of layout, aesthetics and management level of the shopping places; Tourist Satisfaction Evaluation Unit: Conduct satisfaction evaluation on scenic spots based on OTA platform ratings and tourist feedback; Analysis result display unit: The scores of each dimension are combined to obtain the total score of social media big data evaluation.

4. A cultural tourism big data evaluation system according to claim 3, characterized in that: The spectacle degree module specifically includes: Data collection and collation unit: collect historical documents, sites, cultural heritage, historical events and personal information related to the scenic spot, and obtain the historical and cultural background of the scenic spot through the research results of historians and archaeologists, local chronicles and cultural heritage data sources; Collect data on popular science education resources, scientific research facilities, natural phenomena, and scientific research activities in the scenic area; Collect information on the natural resources of the scenic area, including geology, landforms, climate, plant and animal diversity, and water resources; Collect data on natural resources of scenic spots through environmental protection departments and ecological research institutions, as well as data on recreational facilities, leisure activities and visitor participation provided by scenic spots; Index system design unit: According to the characteristics of the scenic spot and the needs of the target tourist groups, determine the evaluation indicators of each dimension, set weights for each dimension, weight them according to the characteristics of the scenic spot, design qualitative indicators for each dimension, set standardized evaluation standards, and use numerical methods to quantify the scores of each indicator; Analysis result display unit: The scores of each dimension are combined to obtain a spectacle score.

5. A cultural tourism big data evaluation system according to claim 4, characterized in that: The comprehensive scoring module specifically includes: Data collection and integration unit: collects scoring data from each evaluation module, cleans the data, removes duplicates, fills in missing values, and integrates the data of all evaluation modules into a unified format; Standardization processing unit: standardize the score values ​​of different modules to make them within a unified score range. The standardization formula is: In the formula, is the original score, and The minimum and maximum values ​​for the module score. is the value after standardization; Weight allocation unit: Assign weights to each module according to its importance, and weight the scores of each module to obtain a comprehensive score. Determine the weight of each module based on the expert opinions and the scoring results analyzed from historical data. Multiply the standardized score of each module by its weight to obtain a weighted score. The weighted score calculation formula is: In the formula, is the weighted score, For the Standardized scoring for each module, For the The weight of each module, is the total number of assessment modules; Analysis and presentation of scoring results: Scenic spots are divided into different levels according to the comprehensive scores, and the scoring range is set, including high scores of 90 to 100 points for excellent scenic spots, medium and high scores of 70 to 89 points for good scenic spots, medium scores of 50 to 69 points for general scenic spots, and low scores of 0 to 49 points for scenic spots that need improvement; Use charts to present each assessment module and the overall score.

6. A cultural tourism big data evaluation method, characterized in that: include: S1: Collect evaluation data about scenic spots from tourism-related social media platforms, including tourist feedback and rating data; S2: Clean and standardize the collected data, and stratify and score them according to supporting facilities, visitor satisfaction and spectacle indicators; S3: Analyze the processed data based on various indicator models in the cultural tourism big data evaluation system to generate a comprehensive score; S4: Feedback the generated scoring and analysis results to scenic spots and cultural tourism management departments to provide optimization suggestions and improvement plans.

7. A cultural tourism big data evaluation method according to claim 6, characterized in that: The S1 specifically includes: Identify data sources, including social media, travel review websites, and tourism bureau statistics, and define collection objectives; Collect data based on the API interface, set the collection time period, update regularly, deduplicate data, filter spam information, and perform sentiment analysis, and store and manage data.

8. A cultural tourism big data evaluation method according to claim 7, characterized in that: The S2 specifically includes: Delete duplicate comments and ratings, and use the mean filling method to fill in missing ratings and comments; Unify the rating systems used by different platforms, use natural language processing technology for sentiment analysis, convert text comments into a unified sentiment score, and ensure that all data has a unified timestamp format; Scenic spots are graded in different levels based on different evaluation dimensions and indicators, including supporting facilities scores, visitor satisfaction scores, spectacular scores, service quality scores, and environment and cleanliness scores.

9. A cultural tourism big data evaluation method according to claim 8, characterized in that: The S3 specifically includes: Assign weights to each dimension and indicator, perform weighted aggregation based on the weights and scoring results of each indicator, and generate a comprehensive score for each scenic spot; According to the comprehensive scoring results, scenic spots are usually divided into different levels: excellent, good, medium and poor; Sort all scenic spots by comprehensive scores to form a ranking, and visualize the analysis results in the form of charts; Comprehensive analysis report: Generate a detailed analysis report, summarizing the comprehensive score of each scenic spot, the analysis results of each dimension, and the summary of advantages and disadvantages.

10. A cultural tourism big data evaluation method according to claim 9, characterized in that: The S4 specifically includes: formulating specific improvement suggestions for each scenic spot according to the scoring results, and ranking the problem solutions according to the severity and impact scope of the problem.

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