Scene-driven large-model text travel question and answer service system
Through the scenario-driven large-scale cultural and tourism question-and-answer service system, combined with prior knowledge and posterior knowledge system, the problem that users in the cultural and tourism field is difficult to meet is solved, and efficient and accurate intelligent services are achieved.
Patent Information
- Application Number
- CN202411598237.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-11
- Publication Date
- 2025-03-07
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The existing technology is difficult to meet the personalized needs of users in the field of cultural and tourism, especially in complex scenarios, with insufficient intelligent service levels.
A scenario-driven large-scale cultural and tourism question-and-answer service system is adopted, combining a priori knowledge system, a posterior knowledge system, von Neumann thinking architecture and knowledge connection mechanism, and automatically retrieve corresponding knowledge and generate personalized answers based on the specific situation of the user's question.
It has improved the level of intelligent service in the cultural and tourism field, provided users with personalized and accurate information support, improved the speed and accuracy of information retrieval and answer generation, and is suitable for a variety of application scenarios.
Smart Images
Figure CN119576992A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of tourism application technology, and in particular to a scenario-driven large-scale cultural tourism question-and-answer service system. Background Art
[0002] With the rapid development of information technology, especially in the field of culture and tourism, users are faced with great challenges in finding attractions and services that meet their personal needs. At the same time, enterprises are also in urgent need of insight into users' personalized needs in order to provide more attractive and personalized services to achieve business expansion and profit improvement.
[0003] Existing recommendation services mainly rely on traditional economic and statistical methods. Although some progress has been made in some areas, there are still limitations in flexibility and adaptability. With the gradual application of artificial intelligence technology, especially recommendation methods based on deep learning and knowledge graphs, although some results have been achieved, the performance of most methods in complex scenarios still needs to be improved. Therefore, how to build a comprehensive large-scale model solution that can meet the personalized needs of users has become an urgent problem to be solved.
[0004] Based on this, the present invention proposes a scenario-driven large-model cultural and tourism question-and-answer service system to improve the level of intelligence in the cultural and tourism field and meet the diverse needs of users in complex scenarios. Summary of the invention
[0005] The present invention mainly solves the technical problems existing in the above-mentioned prior art and provides a scenario-driven large-scale model cultural tourism question-and-answer service system.
[0006] In order to achieve the above-mentioned objectives, the present invention adopts the following technical solutions: a scenario-driven large-model cultural tourism question-and-answer service system, including a priori knowledge system, a posteriori knowledge system, a von Neumann thinking framework and a knowledge connection mechanism, which can automatically retrieve corresponding knowledge and generate personalized answers according to the specific context of the user's question, wherein the priori knowledge is stored in a knowledge base or memory, thereby improving system performance, effectively saving tokens and reducing response time.
[0007] As a preferred technical solution of the present invention, the prior knowledge system divides knowledge into broad scenarios, detailed scenarios and specific tasks through a three-level structure, and realizes efficient answer generation based on this structure, wherein the prior knowledge is stored in the format of large model instructions, including CoT (Chain-of-Thought), ReAct and other forms, thereby realizing refined reasoning for different scenarios.
[0008] As a preferred technical solution of the present invention, the a posteriori knowledge system includes a structured database and a vector database, which are respectively used to store quantitative information and semantic information to support complex query requirements and provide accurate information retrieval.
[0009] As a preferred technical solution of the present invention, the von Neumann thinking architecture combines a priori knowledge with a posteriori knowledge and ensures flexibility and efficiency in the decision-making process through a storage-computation separation architecture, thereby improving system performance and avoiding excessive reliance on long context.
[0010] As a preferred technical solution of the present invention, the knowledge connection mechanism optimizes the database structure and improves resource utilization efficiency by establishing a linkage between prior knowledge, a posteriori knowledge and intelligent agents, thereby ensuring the efficiency and accuracy of information processing.
[0011] As a preferred technical solution of the present invention, users can ask questions through text or voice input, and the system can automatically identify the intention of the question and return personalized answers to improve the user interaction experience.
[0012] As a preferred technical solution of the present invention, the system can obtain and update the latest tourism-related information in real time, including weather forecasts, news updates and other content, so as to improve the timeliness and accuracy of recommendations and ensure that users obtain the most timely information.
[0013] As a preferred technical solution of the present invention, the intelligent agent can actively ask questions to collect more relevant information when the user asks questions, thereby improving the accuracy and personalization of the answers and enhancing user satisfaction.
[0014] As a preferred technical solution of the present invention, the system is applicable to a variety of application scenarios, including but not limited to travel recommendations, itinerary planning, real-time information query, etc., and has high application value and wide adaptability.
[0015] The present invention provides a scenario-driven large-scale model cultural tourism question-and-answer service system. It has the following beneficial effects:
[0016] 1. This scenario-driven large-model cultural and tourism question-and-answer service system, by combining advanced knowledge systems with artificial intelligence technology, can effectively improve the level of intelligent services in the cultural and tourism field and provide users with personalized and accurate information support.
[0017] 2. This is a scenario-driven large-model cultural tourism question-and-answer service system. By analyzing the context of the user's questions, the system can provide more personalized answers, especially for the needs of the cultural tourism field, and can provide customized attraction recommendations, activity suggestions, etc.
[0018] 3. This scenario-driven large-scale cultural and tourism question-and-answer service system, with its integrated knowledge system and intelligent agent mechanism, has greatly improved the speed of information retrieval and answer generation, especially the rapid response in multiple scenarios can improve user experience.
[0019] 4. This scenario-driven large-scale cultural and tourism question-and-answer service system can obtain and update the latest tourism-related information (such as opening hours of scenic spots, changes in activities, etc.) in real time, ensure the timeliness and accuracy of recommendations, and improve the reliability of user decision-making.
[0020] 5. This is a scenario-driven large-model cultural tourism question-and-answer service system. The von Neumann thinking architecture ensures that the system can flexibly respond to various complex scenarios, especially in the field of cultural tourism. It can flexibly allocate knowledge resources to provide accurate and personalized answers to diverse issues.
[0021] 6. This scenario-driven large-model cultural and tourism question-and-answer service system is not only suitable for scenarios such as travel recommendations and itinerary planning, but can also be expanded to areas such as cultural activities and catering recommendations. It has high application value, especially in innovative applications combining culture and tourism, and has demonstrated wide adaptability. BRIEF DESCRIPTION OF THE DRAWINGS
[0022] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification for people familiar with this technology to understand and read, and are not used to limit the conditions under which the present invention can be implemented, so they have no substantial technical significance.
[0023] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION
[0024] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for the implementation methods or the description of the prior art. Obviously, the drawings described below are only exemplary, and for ordinary technicians in this field, other implementation drawings can be derived from the provided drawings without creative work.
[0025] The structures, proportions, sizes, etc. illustrated in this specification are only used to match the contents disclosed in the specification so as to facilitate understanding and reading by persons familiar with the technology. They are not used to limit the conditions under which the present invention can be implemented, and therefore have no substantial technical significance. Any structural modification, change in proportion or adjustment of size shall still fall within the scope of the technical contents disclosed in the present invention without affecting the effects and purposes that can be achieved by the present invention.
[0026] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.
[0027] In the description of the embodiments of the present invention, it should be noted that the terms "center", "upper", "lower", "inner", "outer", "side", etc. indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the invented product is usually placed when in use, which is only for the convenience of describing the present invention and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", etc. are only used to distinguish the description, and cannot be understood as indicating or implying relative importance.
[0028] In the description of the embodiments of the present invention, it is also necessary to explain that, unless otherwise clearly specified and limited, the terms "set", "install", "connect", and "connect" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the embodiments of the present invention can be understood according to specific circumstances.
[0029] Example 1
[0030] See also Figure 1 As shown in the figure, a scenario-driven large-scale cultural tourism question-and-answer service system includes a priori knowledge system, a posteriori knowledge system, a von Neumann thinking framework, and a knowledge connection mechanism. It can automatically retrieve the corresponding knowledge and generate personalized answers according to the specific context of the user's question. The priori knowledge is stored in the knowledge base or memory, which improves the system performance and effectively saves tokens and reduces the response time. "Token" refers to the smallest unit used to represent text in natural language processing (NLP). Usually, in text processing or machine learning models, a "token" can be a word, a subword, a character, or even a punctuation mark, depending on how the model segments or segments the text.
[0031] The prior knowledge system divides knowledge into broad scenarios, detailed scenarios and specific tasks through a three-level structure, and achieves efficient answer generation based on this structure. The prior knowledge is stored in the format of large model instructions, including CoT (Chain-of-Thought), ReAct and other forms, so as to achieve refined reasoning for different scenarios.
[0032] The a posteriori knowledge system includes a structured database and a vector database, which are used to store quantitative information and semantic information respectively to support complex query requirements and provide accurate information retrieval.
[0033] The von Neumann thinking architecture improves system performance and avoids excessive reliance on long context by combining prior knowledge with a posteriori knowledge and ensuring flexibility and efficiency in the decision-making process through a storage-computation separation architecture.
[0034] The knowledge connection mechanism optimizes the database structure and improves resource utilization efficiency by establishing linkages between prior knowledge, a posteriori knowledge and intelligent agents, ensuring the efficiency and accuracy of information processing.
[0035] Users can ask questions via text or voice input, and the system can automatically identify the intent of the question and return personalized answers to improve the user interaction experience.
[0036] The system can obtain and update the latest travel-related information in real time, including weather forecasts, news and other content, to improve the timeliness and accuracy of recommendations and ensure that users obtain the most timely information.
[0037] Intelligent agents can proactively ask questions to collect more relevant information when users ask questions, thereby improving the accuracy and personalization of answers and enhancing user satisfaction.
[0038] The system is suitable for a variety of application scenarios, including but not limited to travel recommendations, itinerary planning, real-time information query, etc. It has high application value and wide adaptability.
[0039] Example 2
[0040] See also Figure 1 As shown, based on Example 1, this embodiment mainly targets the field of cultural tourism and designs an intelligent question-answering service system that integrates multiple advanced technologies, which is specifically divided into the following modules:
[0041] 1. Prior knowledge system
[0042] The prior knowledge system divides knowledge into three levels:
[0043] Major scenarios: scene-based, activity-based, common sense-based and real-time-based, all of which are designed for specific scenarios in the cultural and tourism sector.
[0044] Segmented scenarios: Based on user needs, tasks are further segmented to meet personalized needs in the field of cultural tourism.
[0045] Specific tasks: Special emphasis is placed on the storage structure of basic information and special information (such as scenic spot information, activity information, etc.), which are particularly important in the field of cultural tourism.
[0046] In each specific task module, there are "specific conditions", "answer paradigm", "boundary type" and "example question and answer". This structure helps the intelligent agent gradually locate the correct situation and generate high-quality answers through standardized prompt words.
[0047] 2. A posteriori knowledge system
[0048] The a posteriori knowledge system consists of a structured database and a vector database:
[0049] Structured database: stores quantitative information, such as attractions, restaurants, hotels, etc., as well as common knowledge such as entertainment activities and policies.
[0050] Vector database: stores semantic information (such as text descriptions, comments, etc.), which is very important for cultural tourism question-and-answer services because semantic matching and context analysis can greatly enhance the user experience.
[0051] This hierarchical structure can not only effectively improve the efficiency of knowledge retrieval, but also enhance the accuracy of information, especially in the field of cultural tourism, where the data involved are often diverse and complex.
[0052] 3. Von Neumann’s Thinking Framework
[0053] The workflow of this architecture is as follows:
[0054] The system first assesses the general context of the user's question.
[0055] Then, the relevant a posteriori knowledge base and tools are accessed and their accuracy is evaluated. Finally, the prompt words of the prior knowledge system are combined for reasoning to generate answers.
[0056] This architecture enhances the flexibility and efficiency of the system when facing complex problems, especially in the ever-changing field of cultural tourism, and can dynamically adjust the answer generation strategy.
[0057] 4. Knowledge connection mechanism
[0058] The knowledge connection mechanism achieves the following:
[0059] The "answer paradigm" in the prior knowledge corresponds to the prompt word knowledge base one by one and is updated synchronously;
[0060] The specific scenarios of prior knowledge correspond one-to-one with the tables in the a posteriori knowledge database;
[0061] The "specific conditions" of the prior knowledge correspond one-to-one to the fields in the a posteriori knowledge database table.
[0062] This mechanism enables efficient collaboration between different knowledge systems, thereby improving the system's response speed and accuracy, and ensuring that users receive personalized and real-time answers.
[0063] Working principle of the present invention:
[0064] 1. The user asks a question via text or voice input.
[0065] 2. The system first identifies the content of the user's question and determines the context of the question through scenario analysis (such as attraction query, activity recommendation, etc.).
[0066] 3. The system accesses the a posteriori knowledge base to obtain quantitative information (such as basic information about attractions) and related semantic information (such as activity evaluation) to generate preliminary answers.
[0067] 4. If the initial answer is not sufficient to meet the user's needs, the system will further query the prior knowledge base and refine and supplement it based on the existing information.
[0068] 5. Finally, the system combines the specific context of the user's question, the content of the a posteriori knowledge base, and the structured prompts in the prior knowledge to generate personalized and accurate answers.
[0069] The above working principle can ensure that the system can flexibly respond to diverse and complex user needs in the field of cultural tourism, while improving the accuracy and practicality of the answers.
[0070] The scenario-driven large-scale cultural tourism question-and-answer service system provided by the present invention has the following advantages:
[0071] (1) Personalized service: By analyzing the context of the user’s question, the system can provide more personalized answers, especially for the needs of the cultural tourism field, and can provide customized recommendations for attractions and activities, etc.
[0072] (2) Efficiency: The integrated knowledge system and intelligent agent mechanism greatly improve the speed of information retrieval and answer generation. In particular, the rapid response in multiple scenarios can improve the user experience.
[0073] (3) Real-time update: The system can obtain and update the latest tourism-related information (such as opening hours of attractions, changes in activities, etc.) in real time to ensure the timeliness and accuracy of recommendations and improve the reliability of user decision-making.
[0074] (4) Flexibility and precision: The von Neumann thinking architecture ensures that the system can flexibly respond to various complex scenarios, especially to diverse issues in the field of cultural tourism, and can flexibly allocate knowledge resources to provide accurate and personalized answers.
[0075] (5) Wide applicability: The system is not only suitable for scenarios such as travel recommendations and itinerary planning, but can also be expanded to areas such as cultural activities and catering recommendations. It has high application value, especially in innovative applications combining culture and tourism, demonstrating wide adaptability.
[0076] In summary, the present invention, by combining advanced knowledge systems with artificial intelligence technology, can effectively improve the level of intelligent services in the cultural and tourism field and provide users with personalized and accurate information support.
[0077] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited by the above embodiments, and the above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, and these changes and improvements all fall within the scope of the present invention to be protected.
Claims
1. A scenario-driven large-scale cultural tourism question-and-answer service system, characterized by: It includes a priori knowledge system, a posteriori knowledge system, von Neumann thinking framework and knowledge connection mechanism, which can automatically retrieve corresponding knowledge and generate personalized answers according to the specific context of the user's question. The priori knowledge is stored in the knowledge base or memory, which improves system performance and effectively saves tokens and reduces response time.
2. A scenario-driven large-scale cultural tourism question-and-answer service system according to claim 1, characterized in that: The prior knowledge system divides knowledge into broad scenarios, detailed scenarios and specific tasks through a three-level structure, and achieves efficient answer generation based on this structure, wherein the prior knowledge is stored in the form of large model instructions, including CoT (Chain-of-Thought), ReAct and other forms, thereby achieving refined reasoning for different scenarios.
3. A scenario-driven large-scale cultural tourism question-and-answer service system according to claim 1, characterized in that: The a posteriori knowledge system includes a structured database and a vector database, which are used to store quantitative information and semantic information respectively to support complex query requirements and provide accurate information retrieval.
4. A scenario-driven large-scale cultural tourism question-and-answer service system according to claim 1, characterized in that: The von Neumann thinking architecture combines prior knowledge with a posteriori knowledge and ensures flexibility and efficiency in the decision-making process through a storage-computation separation architecture, thereby improving system performance and avoiding excessive reliance on long context.
5. A scenario-driven large-scale cultural tourism question-and-answer service system according to claim 1, characterized in that: The knowledge connection mechanism optimizes the database structure and improves resource utilization efficiency by establishing a linkage between prior knowledge, a posteriori knowledge and intelligent agents, thereby ensuring the efficiency and accuracy of information processing.
6. A scenario-driven large-scale cultural tourism question-and-answer service system according to claim 1, characterized in that: Users can ask questions via text or voice input, and the system can automatically identify the intent of the question and return personalized answers to improve the user interaction experience.
7. A scenario-driven large-scale cultural tourism question-and-answer service system according to claim 1, characterized in that: The system can obtain and update the latest travel-related information in real time, including weather forecasts, news and other content, to improve the timeliness and accuracy of recommendations and ensure that users obtain the most timely information.
8. The scenario-driven large-scale cultural tourism question-and-answer service system according to claim 1, characterized in that: Intelligent agents can proactively ask questions to collect more relevant information when users ask questions, thereby improving the accuracy and personalization of answers and enhancing user satisfaction.
9. A scenario-driven large-scale cultural tourism question-and-answer service system according to claim 1, characterized in that: The system is suitable for a variety of application scenarios, including but not limited to travel recommendations, itinerary planning, real-time information query, etc. It has high application value and wide adaptability.