Management method and terminal of smart exhibition one-code pass

Abstract

The present invention provides a management method and terminal for a smart exhibition one-code pass, the management method for the smart exhibition one-code pass includes: receiving a QR code verification request from a visitor, obtaining a request time corresponding to the QR code verification request, extracting the visitor's identity information from the QR code verification request when it is determined that the request time is within a reservation time period, verifying the visitor's identity information, allowing the visitor to enter the exhibition hall after the verification is passed, and obtaining a list of exhibition halls where the visitor can visit the target exhibition hall, constructing a visit authority list based on the exhibition hall list and the visitor's identity information, and sending the visit authority list to all target exhibition halls and corresponding experience devices in the exhibition hall list, and completing the visit authority verification of the visitor in each target exhibition hall or experience device. The present invention does not require the background to continuously verify the visitor's QR code, avoiding excessive background load and system crash, thereby achieving load balancing.

Description

Technical Field

[0001] The present invention relates to the field of smart exhibition technology, and in particular to a management method and terminal for a smart exhibition one-code pass. Background Art

[0002] An exhibition hall is a place used to display a specific theme or a series of related themes. The place can be an art gallery, exhibition venue, cultural center, etc. The exhibition hall contains one or more exhibition halls, which are the spaces inside the exhibition hall for display.

[0003] At present, many exhibition halls have the function of smart exhibition. Smart exhibition refers to the use of mobile Internet technology to integrate the Internet of Things, cloud computing and other new generation information technology applications. For example, through the official website or dedicated application to provide an online reservation system, visitors can purchase and reserve electronic tickets in advance, quickly enter the exhibition hall through QR code scanning verification, and can also enter the exhibition hall or use experience equipment through the same QR code scanning verification. However, when the flow of visitors is large and there are many exhibition halls and experience equipment in the exhibition hall, the background needs to continuously verify the visitor's QR code to determine whether the visitor has the right to enter the exhibition hall or use the experience equipment, which can easily cause the background to be overloaded and the system to crash.

[0004] In the technical solution with application number CN202111516398.0, although it realizes a smart exhibition, that is, when exhibitors visit, they are greeted by voice and screen display, asked about the exhibition areas and exhibits they are interested in, and prompted to use voice communication or options on the touch screen. According to the question options or questions raised by exhibitors at any time, the corresponding answers are found in the database, and the exhibitors' questions are answered by voice and text display. If no answers are found, manual service is switched; but it cannot handle the problems of excessive background load and system crashes.

[0005] In the technical solution with application number CN202111596480.9, although it makes the main data true and accurate by establishing a QR code application data model, the QR code application data model includes QR code-related information of multiple service applications to ensure the sharing of multi-application data, so as to complete identity interaction between multiple industry applications in the one-code access scenario and realize safe and reliable one-code access; but it cannot solve the problem that the background needs to constantly verify the visitor's QR code, which easily leads to excessive background load and system crash. Summary of the invention

[0006] The present invention provides a management method and terminal for a smart exhibition one-code pass to achieve load balancing.

[0007] To solve the above problems, the present invention adopts the following technical solutions:

[0008] The present invention provides a management method for a smart exhibition one-code pass, comprising:

[0009] Receive a QR code verification request from a visitor, and obtain a request time corresponding to the QR code verification request;

[0010] When it is determined that the request time is within the reservation time period, extracting the visitor's identity information from the QR code verification request;

[0011] The identity information of the visitor is verified. After the verification is passed, the visitor is allowed to enter the exhibition hall, and a list of the target exhibition halls that the visitor can visit is obtained. A visit permission list is constructed according to the list of exhibition halls and the identity information of the visitor. The visit permission list is used to record the visitors who have opened all the target exhibition halls and corresponding experience equipment permissions in the exhibition hall list;

[0012] The visitor authority list is distributed to all target exhibition halls and corresponding experience devices in the exhibition hall list, and the visitor's visit authority verification is completed in each target exhibition hall or experience device.

[0013] Furthermore, before receiving the visitor's QR code verification request, the method further includes:

[0014] Obtaining the visitor's identity information and timestamp, and converting the visitor's identity information into a unique identifier according to a hash function to obtain a visitor identification;

[0015] splicing the visitor identification and the timestamp to obtain splicing information;

[0016] Encrypting the splicing information and converting it into binary data to obtain target data;

[0017] The target data is generated into a QR code using a QR code generation library, and the QR code is sent to the visitor.

[0018] Preferably, the splicing information is encrypted and converted into binary data to obtain target data, including:

[0019] Encrypting the splicing information according to a symmetric encryption algorithm to obtain encrypted data;

[0020] The encrypted data is converted into binary data to obtain target data.

[0021] Preferably, completing the visitor's visit authority verification in each of the target exhibition halls or experience devices includes:

[0022] The target exhibition hall or experience device receives a target QR code verification request displayed by a visitor, and extracts the identity information of the visitor from the target QR code verification request;

[0023] The target exhibition hall or experience device determines whether the visitor is recorded in the corresponding visitor authority list according to the identity information of the visitor;

[0024] If so, the target exhibition hall allows the visitor to exhibit or the experience equipment allows the visitor to use.

[0025] Furthermore, after each of the target exhibition halls or experience devices completes the visitor's visit authority verification, it also includes:

[0026] Get the current timestamp;

[0027] Determine whether the current timestamp exceeds the deadline of the visitor's corresponding reservation time period;

[0028] If so, a deletion instruction is generated and sent to the target exhibition halls and experience devices containing the visitor's corresponding visiting authority list, and each of the target exhibition halls and experience devices deletes the visitor's corresponding visiting authority list.

[0029] Furthermore, after each of the target exhibition halls or experience devices completes the visitor's visit authority verification, it also includes:

[0030] Acquire multiple pieces of historical exhibition visit data of the visitor;

[0031] Randomly select any two pieces of historical exhibition visit data from the plurality of historical exhibition visit data in chronological order, concatenate them, and convert them into binary data respectively, to obtain a plurality of visit character strings;

[0032] Obtain the types, locations and traffic of all historical exhibition halls to obtain exhibition hall data;

[0033] After converting the exhibition hall data into binary data, a plurality of exhibition hall character strings are obtained;

[0034] Calculating the visitor's interest in each historical exhibition hall according to the plurality of visit character strings and the plurality of exhibition hall character strings, and generating a visitor interest vector;

[0035] Obtain the types, locations and traffic of all target exhibition halls, and obtain the target exhibition hall data;

[0036] Performing vector processing on the target exhibition hall data to obtain a target exhibition hall vector;

[0037] The similarity between the visitor's interest vector and the target exhibition hall vector is calculated, and the target exhibition hall with a similarity greater than a preset threshold is screened out and recommended to the visitor.

[0038] Preferably, the visitor's interest in each historical exhibition hall is calculated according to the plurality of visit character strings and the plurality of exhibition hall character strings, and a visitor interest vector is generated, including:

[0039] Set minimum support and minimum confidence;

[0040] Based on the minimum support and the minimum confidence, all possible frequent item sets of multiple visit character strings and multiple exhibition hall character strings are generated according to the Apriori algorithm, and the frequent item sets are used to characterize the association between the visit character string and the corresponding exhibition hall character string;

[0041] After weighted summing up the correlation between all visit character strings and the corresponding exhibition hall character strings in the frequent item set, the visitor's interest in each historical exhibition hall is obtained, and multiple visit character strings, multiple exhibition hall character strings and the corresponding interest degrees are respectively mapped to a unique position in the high-dimensional space, each position corresponds to a dimension, and the visitor interest vector is obtained.

[0042] Furthermore, after each of the target exhibition halls or experience devices completes the visitor's visit authority verification, it also includes:

[0043] Obtaining the question content about the target exhibition hall or experience equipment sent by the visitor in voice or text form;

[0044] Performing vectorization processing on the question content to obtain a question vector corresponding to the question content;

[0045] Input the question vector corresponding to the question content into a pre-trained knowledge base model, output a plurality of answer contents, select the answer contents whose question vectors corresponding to the question content are greater than a preset similarity from the plurality of answer contents, and obtain the target answer contents, wherein the knowledge base model is a neural network model, which is used to analyze and process the question content and generate the answer contents;

[0046] Selecting keywords and key sentences from the target answer content, and generating an answer summary based on the keywords and key sentences;

[0047] The answer summary is sent to the terminal where the visitor is located.

[0048] Furthermore, before inputting the question vector corresponding to the question content into the pre-trained knowledge base model, the method further includes:

[0049] Acquire multiple training samples, wherein the training samples include reference question content and corresponding reference answer content;

[0050] Constructing a convolutional neural network model, dividing the plurality of training samples into a training set and a test set according to a preset ratio;

[0051] Inputting the training set into the convolutional neural network model for multiple iterative training, and calculating the loss value obtained after the multiple iterative training of the convolutional neural network model according to a preset loss function;

[0052] Determining whether the loss value is lower than a preset value;

[0053] If not, based on the loss value, adjusting each parameter of the convolutional neural network model using a preset stochastic gradient descent method;

[0054] The convolutional neural network model with adjusted parameters is iteratively trained again using the training set until the loss value is lower than a preset value, thereby obtaining an initial knowledge base model;

[0055] The test set is input into the initial knowledge base model for testing, and after the test is passed, a knowledge base model is generated.

[0056] The present invention provides a terminal, comprising a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the management method of the smart exhibition one-code pass as described in any one of the above items.

[0057] Compared with the prior art, the technical solution of the present invention has at least the following advantages:

[0058] The management method and terminal of the smart exhibition one-code pass provided by the present invention ensure that only visitors with legal reservations can enter the exhibition hall by verifying the visitor's identity information, thereby enhancing the security management of the exhibition hall; at the same time, by constructing a visitor authority list and accurately controlling the visitor's access rights to the exhibition hall and experience equipment, the exhibition hall resources can be better allocated and utilized, for example, avoiding overcrowded exhibition halls and equipment, and ensuring that every visitor can have a good visiting experience; in addition, by distributing the visitor authority list to each exhibition hall and experience equipment, each exhibition hall and experience equipment independently completes the visitor's identity authentication, without the need for the background to continuously verify the visitor's QR code, avoiding excessive background load and system crash, thereby achieving load balancing. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A flowchart of an embodiment of the management method of the smart exhibition one-code pass of the present invention;

[0060] Figure 2 A module block diagram of an embodiment of a management device for a smart exhibition one-code pass of the present invention;

[0061] Figure 3 FIG. 4 is a block diagram of the internal structure of a terminal in one embodiment of the present invention. DETAILED DESCRIPTION

[0062] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0063] In some of the processes described in the specification and claims of the present invention and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that the operations may not be executed in the order in which they appear in this article or in parallel. The sequence numbers of the operations, such as S11, S12, etc., are only used to distinguish between different operations, and the sequence numbers themselves do not represent any execution order. In addition, the process may include more or fewer operations, and the operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to be different types.

[0064] It will be understood by those of ordinary skill in the art that, unless expressly stated, the singular forms "a", "an", "said" and "the" used herein may also include plural forms. It should be further understood that the term "comprising" used in the specification of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, the "connection" or "coupling" used herein may include wireless connection or wireless coupling. The term "and / or" used herein includes all or any unit and all combinations of one or more associated listed items.

[0065] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as generally understood by those skilled in the art in the art to which the present invention belongs. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with the meanings in the context of the prior art, and will not be interpreted with idealized or overly formal meanings unless specifically defined as herein.

[0066] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the drawings in the embodiments of the present invention, wherein the same or similar reference numerals throughout represent the same or similar elements or elements with the same or similar functions. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0067] See also Figure 1 The present invention provides a management method for a smart exhibition one-code pass, comprising:

[0068] S11, receiving a QR code verification request from a visitor, and obtaining a request time corresponding to the QR code verification request;

[0069] S12, when it is determined that the request time is within the reservation time period, extracting the visitor's identity information from the QR code verification request;

[0070] S13, verifying the identity information of the visitor. After the verification is passed, the visitor is allowed to enter the exhibition hall, and a list of the target exhibition halls that the visitor can visit is obtained. A visit permission list is constructed according to the list of exhibition halls and the identity information of the visitor. The visit permission list is used to record the visitors who have opened all the target exhibition halls and corresponding experience equipment permissions in the exhibition hall list;

[0071] S14, the visitor authority list is distributed to all target exhibition halls and corresponding experience devices in the exhibition hall list, and the visitor's visit authority verification is completed in each target exhibition hall or experience device.

[0072] In modern exhibition halls, in order to ensure the visitor experience and the safety of exhibits, a series of digital verification and management processes are generally adopted. Specifically, when visitors arrive at the exhibition hall, they need to show the QR code obtained when making an appointment. The scanner automatically scans the QR code displayed by the visitor, and the background will record the time of the QR code verification request. At the same time, it will check the visitor's appointment time period, compare the request time with the appointment time period that the visitor has made in advance, and confirm whether the current time is within the appointment time. If the request time is within the appointment time period, the background will extract the visitor's identity information from the QR code verification request. The identity information may include name, ID number, contact information, registration account, etc. This information is used to verify the identity of the visitor.

[0073] The identity information of the visitor is verified to confirm whether the visitor has made an appointment for the exhibition and whether he has the right to enter the exhibition hall. After the identity verification is passed, the background allows the visitor to enter the exhibition hall. At the same time, a visitor permission list will be constructed based on the visitor's identity information and the list of exhibition halls that can be visited. The list records which visitors are authorized to visit specific exhibition halls and experience equipment. Among them, the experience equipment may include virtual reality (VR) equipment: such as head-mounted displays (HMDs), VR handles, etc., which simulate a three-dimensional environment to allow users to experience the feeling of being in another world. Augmented reality (AR) equipment: such as smart glasses, AR mobile phone applications, etc., which superimpose virtual information on the real world to enhance the user's perception of the real world. Interactive projection: Through projection technology and sensors, the wall or ground is transformed into an interactive surface, and the user can interact with it through body movements. 4D / 5D cinema: Provides multiple sensory experiences such as vision, hearing and touch, and allows the audience to experience a more realistic viewing experience through special effects such as seat vibration, wind effects, and fragrance.

[0074] The visit permission list will be sent to the exhibition halls and experience devices that the visitors are going to visit. Each exhibition hall and experience device will organize, merge and store the visit permission lists corresponding to each visitor. When the visitor arrives at each exhibition hall or experience device, the scanner or experience device in each exhibition hall will scan the QR code presented by the visitor again to verify the visitor's visit permission and ensure that they can only access the authorized part. At the same time, each exhibition hall and experience device will complete the visitor's identity authentication separately, and there is no need for the background to constantly verify the visitor's QR code, avoiding excessive background load and system crashes.

[0075] For example, suppose Mr. Li has made an appointment to visit the aerospace exhibition hall and the robot exhibition hall of a science and technology museum on Saturday afternoon. He made an appointment through the official channel and received a QR code. On Saturday afternoon, Mr. Li arrived at the science and technology museum and presented his QR code. The scanner scanned the QR code, and the background verified that the request time of the QR code matched the time period of Mr. Li's appointment. Subsequently, the background extracted Mr. Li's identity information and verified it. After the verification, Mr. Li was allowed to enter the exhibition hall, and at the same time, Mr. Li's visit permission list was constructed and sent to the aerospace exhibition hall and the robot exhibition hall. Mr. Li presented the QR code again at the entrance of the aerospace exhibition hall. The scanner at the entrance of the aerospace exhibition hall scanned and verified the QR code displayed by Mr. Li again, confirming his visit permission. Mr. Li was then able to enter the exhibition hall to visit. Identity authentication and permission control can prevent unauthorized persons from entering specific areas, which not only improves the operation efficiency of the exhibition hall, but also improves the overall experience of visitors.

[0076] The management method of the smart exhibition one-code pass provided by the present invention ensures that only visitors with legal reservations can enter the exhibition hall by verifying the visitor's identity information, thereby enhancing the security management of the exhibition hall; at the same time, by constructing a visitor authority list and accurately controlling the visitor's access rights to the exhibition hall and experience equipment, the exhibition hall resources can be better allocated and utilized, for example, overcrowding of exhibition halls and equipment can be avoided, ensuring that every visitor can have a good visiting experience; in addition, by distributing the visitor authority list to each exhibition hall and experience equipment, each exhibition hall and experience equipment can complete the visitor's identity authentication independently, without the need for the background to continuously verify the visitor's QR code, avoiding excessive background load and system crash, thereby achieving load balancing.

[0077] In one embodiment, before receiving the visitor's QR code verification request, the method further includes:

[0078] Obtaining the visitor's identity information and timestamp, and converting the visitor's identity information into a unique identifier according to a hash function to obtain a visitor identification;

[0079] splicing the visitor identification and the timestamp to obtain splicing information;

[0080] Encrypting the splicing information and converting it into binary data to obtain target data;

[0081] The target data is generated into a QR code using a QR code generation library, and the QR code is sent to the visitor.

[0082] In modern exhibition halls and events, a series of digital identity authentication and data management processes are used to enhance the visitor experience and ensure safe and efficient management. Specifically, when a visitor arrives at the exhibition hall and presents the QR code for the appointment, the background will capture the visitor's identity information, such as name, ID number, etc., as well as the current timestamp. Then a hash function (such as SHA-256) is used to convert the visitor's identity information into a unique identifier. The identifier is irreversible, ensuring the security of the identity information. The generated visitor ID is spliced ​​with the timestamp to form a comprehensive data containing identity authentication and time information, such as ID number + timestamp.

[0083] The spliced ​​information is encrypted to ensure the security of the data during transmission, and then converted into a binary data format. A QR code generation library (such as Python's qrcode library) is used to encode the target data in binary data format into a QR code. The QR code contains the visitor's identity information and timestamp, as well as possible other verification information.

[0084] The generated QR code is sent to visitors through application push or other methods. Visitors can use smartphones or other devices to show the QR code, and the scanner automatically scans the QR code shown by the visitor and performs identity authentication in the background to complete the identity authentication and admission procedures.

[0085] For example, suppose Mr. Li makes an appointment to visit a museum. He submits his personal information and selects a visit time through the museum's official website. The system generates a hash value for Mr. Li that contains his identity information and appointment time, concatenates this information with the timestamp, encrypts it, and then generates a QR code. Mr. Li arrives at the museum on the day of the visit and displays the QR code on his mobile phone. The scanner automatically scans the QR code displayed by Mr. Li, verifies Mr. Li's identity and appointment time, and then allows him to enter the museum.

[0086] This embodiment can ensure the security of visitor identity information through hash functions and encryption technology. The background can also effectively manage visitor information to facilitate real-time monitoring and future data analysis. The automated identity authentication process also reduces errors and delays in human operations.

[0087] In one embodiment, the splicing information is encrypted and converted into binary data to obtain target data, including:

[0088] Encrypting the splicing information according to a symmetric encryption algorithm to obtain encrypted data;

[0089] The encrypted data is converted into binary data to obtain target data.

[0090] In this embodiment, the symmetric encryption algorithm is an encryption method that uses the same key to encrypt and decrypt data. The characteristic of this algorithm is that the encryption process and decryption process of the algorithm are symmetrical, hence the name "symmetric encryption".

[0091] When encrypting the spliced ​​information in this embodiment, a key is first generated, which will be used in the subsequent encryption and decryption process. The spliced ​​information is converted into ciphertext through the encryption algorithm and the key to obtain encrypted data, which can be restored to plaintext through the decryption algorithm and the same key. Finally, the encrypted data is converted into binary data to obtain the target data. Among them, the symmetric encryption algorithm includes DES (Data Encryption Standard), AES (Advanced Encryption Standard) and 3DES (Triple DES).

[0092] This embodiment can be encrypted, even if the data is intercepted by unauthorized persons, the content cannot be interpreted. In addition, for sensitive information, such as personal privacy or business secrets, encryption can effectively prevent leakage.

[0093] In one embodiment, completing the visitor's visit authority verification in each of the target exhibition halls or experience devices includes:

[0094] The target exhibition hall or experience device receives a target QR code verification request displayed by a visitor, and extracts the identity information of the visitor from the target QR code verification request;

[0095] The target exhibition hall or experience device determines whether the visitor is recorded in the corresponding visitor authority list according to the identity information of the visitor;

[0096] If so, the target exhibition hall allows the visitor to exhibit or the experience equipment allows the visitor to use.

[0097] In this embodiment, when visitors arrive at the target exhibition hall or experience device, they need to show the QR code previously generated by the background, and the scanner of the exhibition hall or experience device will automatically scan the QR code to obtain the visitor's identity information. The QR code contains the visitor's identity information, which may include name, reservation number, visit authority and other data.

[0098] The scanner of the exhibition hall or experience device will also decode and extract the identity information from the QR code for subsequent verification steps. The exhibition hall or experience device will check the visitor authorization list based on the extracted identity information, which records all visitors who are authorized to visit the exhibition hall or use the experience device.

[0099] If the visitor's identity information is in the permission list, it means that they have obtained the permission to visit or use the experience equipment. After the verification is passed, the gate of the exhibition hall will automatically allow the visitor to enter the exhibition hall or use the experience equipment. Otherwise, the visitor will be prohibited from entering the exhibition hall or using the experience equipment.

[0100] For example, suppose Mr. Li makes an appointment for a VR experience at the Science and Technology Museum. He makes the appointment through the Science and Technology Museum's online system and receives a QR code. On the day of the appointment, Mr. Li arrives at the VR experience area of ​​the Science and Technology Museum and shows his QR code to the Science and Technology Museum's scanner. The scanner extracts Mr. Li's identity information from the QR code and checks the list of visitor permissions. If the list shows that Mr. Li has permission to use the VR experience equipment, he is allowed to enter the experience area and start the experience.

[0101] This embodiment can ensure that only authorized visitors can enter specific areas or use experience devices through identity authentication; the automated identity authentication process reduces errors and delays in human operations; at the same time, each exhibition hall and experience device independently completes the visitor's identity authentication through a pre-issued visitor permission list, without the need for the background to constantly verify the visitor's QR code, avoiding excessive background load and system crashes, thereby achieving load balancing.

[0102] In one embodiment, after each of the target exhibition halls or experience devices completes the visitor's visit authority verification, the method further includes:

[0103] Get the current timestamp;

[0104] Determine whether the current timestamp exceeds the deadline of the visitor's corresponding reservation time period;

[0105] If so, a deletion instruction is generated and sent to the target exhibition halls and experience devices containing the visitor's corresponding visiting authority list, and each of the target exhibition halls and experience devices deletes the visitor's corresponding visiting authority list.

[0106] In the digital management system of an exhibition hall or experience center, in order to maintain the real-time and accuracy of visit permissions, this embodiment sets a mechanism to automatically update and delete outdated permissions. Specifically, the background will obtain the current date and time, generally expressed in the form of a timestamp, which is the number of seconds or milliseconds since January 1, 1970 (UTC). The background will check whether the current timestamp has exceeded the deadline of the visitor's reservation time period. The reservation time period refers to the time period when visitors can enter the exhibition hall or use the experience equipment. If the current time has exceeded the reservation deadline, the background will automatically generate a deletion instruction, which is used to delete the list of visit permissions corresponding to the outdated visitor.

[0107] The background will send the deletion command to all the target exhibition halls and experience equipment that contain the visiting permission list to ensure that the visitor's permissions are removed in time after the appointment time ends.

[0108] After receiving the deletion instruction, each target exhibition hall and experience device will delete the visitor's record from the local database or visitor permission list to ensure that they cannot continue to visit after the appointment time. There is no need to maintain the visitor permission list in the background, saving background computer resources.

[0109] For example, suppose Ms. Wang has made an appointment to visit a special exhibition at an art museum from 2:00 to 4:00 p.m. on Saturday. The museum's system will automatically check the current time at the end of Ms. Wang's appointment time, which is 4:00 p.m. Once the time exceeds 4:00 p.m., the background will generate a deletion instruction and send it to the special exhibition hall. After receiving the instruction, the exhibition hall will delete Ms. Wang's record from the visitor permission list, and Ms. Wang will not be able to continue to visit after 4:00 p.m.

[0110] This embodiment automatically deletes outdated permissions to prevent visitors from continuing to access the exhibition hall or experience equipment without authorization, and also ensures that the exhibition hall and experience equipment can release resources for other visitors or maintenance work after the appointment time. At the same time, automated permission management also reduces the need for staff to manually update the visit permission list, reducing the possibility of errors. In addition, the maintenance of the visit permission list is completed through the exhibition hall and experience equipment, and there is no need to maintain the visit permission list in the background, saving computer resources in the background.

[0111] In one embodiment, after each of the target exhibition halls or experience devices completes the visitor's visit authority verification, the method further includes:

[0112] Acquire multiple pieces of historical exhibition visit data of the visitor;

[0113] Randomly select any two pieces of historical exhibition visit data from the plurality of historical exhibition visit data in chronological order, concatenate them, and convert them into binary data respectively, to obtain a plurality of visit character strings;

[0114] Obtain the types, locations and traffic of all historical exhibition halls to obtain exhibition hall data;

[0115] After converting the exhibition hall data into binary data, a plurality of exhibition hall character strings are obtained;

[0116] Calculating the visitor's interest in each historical exhibition hall according to the plurality of visit character strings and the plurality of exhibition hall character strings, and generating a visitor interest vector;

[0117] Obtain the types, locations and traffic of all target exhibition halls, and obtain the target exhibition hall data;

[0118] Performing vector processing on the target exhibition hall data to obtain a target exhibition hall vector;

[0119] The similarity between the visitor's interest vector and the target exhibition hall vector is calculated, and the target exhibition hall with a similarity greater than a preset threshold is screened out and recommended to the visitor.

[0120] This embodiment can recommend exhibition halls by analyzing the historical data of visitors and the characteristics of the exhibition halls. Specifically, the data of all exhibitions that visitors have visited in the past are collected to obtain multiple historical exhibition visit data, which may include the date, time, length of stay, etc. of the visit.

[0121] Two records are randomly selected from multiple historical exhibition visit data of visitors and spliced ​​into a new data record in chronological order to capture the changes in visitors' interests by combining data at different time points.

[0122] Convert the spliced ​​historical visit data into binary format for subsequent similarity calculation and processing. Collect information such as the type, location, and flow of people of all historical exhibition halls to obtain exhibition hall data, which will be used to analyze the interests of visitors. Convert the exhibition hall data of the exhibition hall into binary data or vector form for calculation. Then, based on the multiple visit character strings and exhibition hall character strings of visitors, calculate the visitor's interest in each historical exhibition hall, and generate a vector representing the interest. Collect the data of the target exhibition hall, which may include the type, location, and flow of people of the exhibition hall. Vectorize the data of the target exhibition hall to generate the vector of the target exhibition hall, and calculate the similarity between the visitor's interest vector and the target exhibition hall vector, for example, using the cosine similarity or other similarity measurement methods in the vector space model.

[0123] Based on the calculated similarity, exhibition halls with similarity greater than a preset threshold are screened out. The exhibition halls are considered to be of possible interest to the visitors and are recommended to the visitors.

[0124] For example, suppose that a visitor named Mr. Zhang has visited the Robotics and Astronomy exhibition halls in the Science and Technology Museum. The backend randomly selects these two records, converts them into binary data, and analyzes that Mr. Zhang is more interested in the exhibition halls with high-tech and space exploration themes. The backend further obtains data on all exhibition halls in the Science and Technology Museum, including the newly opened virtual reality exhibition hall. By calculating the similarity between Mr. Zhang's interest vector and the vector of the virtual reality exhibition hall, it is analyzed that the match is very high, so the backend recommends the virtual reality exhibition hall to Mr. Zhang.

[0125] This embodiment can accurately provide personalized exhibition hall recommendations based on visitors' historical behaviors, which can increase visitors' stay time and participation in the exhibition hall. At the same time, the data-driven recommendation model can improve the exhibition hall's operating efficiency and provide visitors with a more customized visiting experience.

[0126] In one embodiment, the visitor's interest in each historical exhibition hall is calculated based on multiple visit character strings and multiple exhibition hall character strings, and a visitor interest vector is generated, including:

[0127] Set minimum support and minimum confidence;

[0128] Based on the minimum support and the minimum confidence, all possible frequent item sets of multiple visit character strings and multiple exhibition hall character strings are generated according to the Apriori algorithm, and the frequent item sets are used to characterize the association between the visit character string and the corresponding exhibition hall character string;

[0129] After weighted summing up the correlation between all visit character strings and the corresponding exhibition hall character strings in the frequent item set, the visitor's interest in each historical exhibition hall is obtained, and multiple visit character strings, multiple exhibition hall character strings and the corresponding interest degrees are respectively mapped to a unique position in the high-dimensional space, each position corresponds to a dimension, and the visitor interest vector is obtained.

[0130] In this embodiment, when constructing a recommendation model or performing association rule mining, the minimum support and minimum confidence are two important parameters that can help determine which rules or models are significant and worthy of further analysis.

[0131] Among them, the minimum support refers to the frequency of an item set (such as the behavior of visitors visiting a certain exhibition hall) in all historical exhibition visit data. If the support of an item set is lower than the minimum support, it will not be considered as a frequent item set. If the support of an item set is higher than the minimum support, it is considered frequent because it means that this item set is relatively common in historical behaviors. For example, if the minimum support is set to 5%, only those item sets that appear in at least 5% of the historical behaviors will be considered frequent.

[0132] The minimum confidence is the conditional probability of the next action occurring when the previous action occurs. It is used to measure the reliability of the rules. If the confidence of a rule is higher than the minimum confidence, then the rule is considered reliable. For example, if the minimum confidence is set to 70%, only those rules that have at least a 70% probability of the next action occurring when the previous action occurs will be retained.

[0133] It should be noted that the minimum support and minimum confidence can be customized.

[0134] Preferably, in a large data set, a lower minimum support may need to be set, because the frequency of occurrence of the item set itself may be very low. In a small data set, a higher minimum support may need to be set to avoid generating too many irrelevant frequent item sets. Therefore, when setting the minimum support, the data volume of multiple visit character strings and the data volume of multiple exhibition hall character strings can be calculated, and the data volume of multiple visit character strings and the data volume of multiple exhibition hall character strings are added together to obtain the total data volume. The minimum support corresponding to the total data volume is set according to the corresponding relationship between the data volume and the minimum support to complete the setting of the minimum support.

[0135] The minimum confidence can be set by first determining the expected rule strength, which is used to characterize the reliability of the rule for filtering all possible frequent item sets. If you want the filtering rule to be very reliable, you can set a higher minimum confidence. If you want to discover more possible filtering rules, even if they are not particularly strongly associated, you can set a lower minimum confidence.

[0136] This embodiment can use the Apriori algorithm to generate frequent itemsets according to the set minimum support and minimum confidence, and then perform weighted summation on the association between the visit string and the exhibition hall string in the frequent itemsets to obtain the visitor's interest in each historical exhibition hall. For example, assuming that the exhibition hall string corresponding to exhibition hall A is a, and the visit strings corresponding to the exhibition hall string a are a1, a2, and a3, if the corresponding associations are 0.9, 0.8, and 0.8, respectively, and the corresponding weights are 10, 15, and 20, respectively, then through weighted summation, the visitor's interest in exhibition hall A is 0.9*10+0.8*15+0.8*20=37.

[0137] Among them, the Apriori algorithm is an algorithm for association rule mining, which mines all frequent item sets in an iterative manner.

[0138] Finally, the visit string, exhibition hall string and their corresponding interest are mapped to a unique position in the high-dimensional space, and each position corresponds to a dimension, so as to obtain the visitor interest vector. All frequent item sets can be accurately mined through data mining technology, and the corresponding vectors can be generated, so as to improve the accuracy of subsequent similarity calculations, and then accurately screen out the target exhibition halls for visitors.

[0139] For example, suppose visitor Zhang San has visited the Robot Exhibition Hall and Astronomy Exhibition Hall of the Science and Technology Museum in the past. The backend uses the Apriori algorithm to analyze the string corresponding to Zhang San's visit record and finds that he is more interested in the exhibition halls with high-tech and space exploration themes. All interests are mapped into a high-dimensional space to form an interest vector. When the backend needs to recommend a new exhibition hall, it calculates the similarity between the interest vector and the new exhibition hall vector. If the similarity is higher than a certain threshold, the exhibition hall will be recommended to Zhang San.

[0140] In one embodiment, after each of the target exhibition halls or experience devices completes the visitor's visit authority verification, the method further includes:

[0141] Obtaining the question content about the target exhibition hall or experience equipment sent by the visitor in voice or text form;

[0142] Performing vectorization processing on the question content to obtain a question vector corresponding to the question content;

[0143] Input the question vector corresponding to the question content into a pre-trained knowledge base model, output a plurality of answer contents, select the answer contents whose question vectors corresponding to the question content are greater than a preset similarity from the plurality of answer contents, and obtain the target answer contents, wherein the knowledge base model is a neural network model, which is used to analyze and process the question content and generate the answer contents;

[0144] Selecting keywords and key sentences from the target answer content, and generating an answer summary based on the keywords and key sentences;

[0145] The answer summary is sent to the terminal where the visitor is located.

[0146] In this embodiment, visitors can ask questions about the exhibition hall or experience equipment to the background in the form of voice or text. When the visitor's question is in voice form, it must first be converted into text form to form the question content. The background converts the question content into a numerical vector to obtain the question vector corresponding to the question content. This process is called vectorization, which converts text data into a format that can be processed by a computer, allowing the computer to quickly process and analyze large amounts of text data, and also helps to improve the system's understanding of the text content.

[0147] Specifically, a unique binary vector can be assigned to each unique word in the question content, in which only one element is 1 and the rest are 0. In addition, each word in the question content can be extracted and mapped to a vector in a high-dimensional space to form a question vector corresponding to the question content, which can capture the semantic relationship between words.

[0148] For example, suppose a visitor asks, "What is the history of this exhibit?" The background will first use word segmentation technology to break down the sentence into words or vocabulary units, and then use the Word2Vec model to convert the word into a vector, that is, each word will be converted into a point in a high-dimensional space, and the position of the point in the space reflects the semantic similarity between them.

[0149] The question vector is input into a pre-trained neural network model, which is trained based on a large amount of data and can understand and process language. The neural network model analyzes the question vector and generates multiple possible answers. The backend will filter out the answer that is most relevant to the question from multiple answers based on the preset similarity threshold and obtain the target answer.

[0150] Finally, the TF-IDF algorithm is used to extract keywords from the screened answer content, and the TextRanking algorithm is used to extract key sentences from the screened answer content. The keywords and key sentences are used to generate a brief answer summary, and the answer summary is sent to the visitor's terminal device, such as a smartphone or tablet computer.

[0151] Among them, the TF-IDF (Term Frequency-Inverse Document Frequency) algorithm is a statistical method used to evaluate the importance of a word to a text or one of the texts in a corpus. The importance of a word increases in proportion to the number of times it appears in the text, but at the same time it decreases inversely with the frequency of its appearance in the corpus. The TF-IDF value can be used to find the keywords in the text. The Text Ranking algorithm can be used to extract key sentences from the text. This algorithm is based on graph ranking algorithms, such as PageRank, which determine their importance by analyzing the mutual reference relationship between sentences.

[0152] For example, suppose that visitor Ms. Wang is interested in a historical exhibit. She asks by voice: "What is the historical background of this exhibit?" After receiving the question, the background converts it into text and performs vector processing. Then, the question vector is input into the knowledge base model, and the model provides multiple answer options after analysis. The background further selects the most relevant answers, extracts key information from them, and generates a summary: "This exhibit is from the 15th century and is related to the Renaissance." Finally, the summary is sent to Ms. Wang's mobile device.

[0153] Visitors of this embodiment can get answers to their questions instantly, which enhances the interactivity and educational value of the visit. Through the automated question-and-answer system, the exhibition hall can use human resources more efficiently, allowing staff to focus on other tasks. At the same time, the pre-trained knowledge base model can provide accurate and consistent answers to avoid human errors.

[0154] In one embodiment, before inputting the question vector corresponding to the question content into the pre-trained knowledge base model, the method further includes:

[0155] Acquire multiple training samples, wherein the training samples include reference question content and corresponding reference answer content;

[0156] Constructing a convolutional neural network model, dividing the plurality of training samples into a training set and a test set according to a preset ratio;

[0157] Inputting the training set into the convolutional neural network model for multiple iterative training, and calculating the loss value obtained after the multiple iterative training of the convolutional neural network model according to a preset loss function;

[0158] Determining whether the loss value is lower than a preset value;

[0159] If not, based on the loss value, adjusting each parameter of the convolutional neural network model using a preset stochastic gradient descent method;

[0160] The convolutional neural network model with adjusted parameters is iteratively trained again using the training set until the loss value is lower than a preset value, thereby obtaining an initial knowledge base model;

[0161] The test set is input into the initial knowledge base model for testing, and after the test is passed, a knowledge base model is generated.

[0162] In this embodiment, the training samples include pairs of reference question content and corresponding reference answer content. The samples are used to train the model so that it can learn how to generate corresponding answers based on the questions.

[0163] The convolutional neural network is a deep learning model that can be used in text data analysis and processing. In text processing, the convolutional neural network model can capture local features, such as n-gram features.

[0164] The system divides the acquired training samples into a certain ratio (e.g. 80% training set and 20% test set) so that the performance of the model can be tested after training. The convolutional neural network model is then trained multiple times using the training set, and the number of iterations can be customized. In each iteration, the model tries to adjust the parameters to reduce the difference between the predicted results and the actual results.

[0165] This loss function (such as the cross entropy loss function) is used to evaluate the difference between the predicted results of the convolutional neural network model and the actual results. During the training process, the goal is to minimize the loss value. The loss value obtained after multiple iterations of training of the convolutional neural network model is calculated according to the loss function. If the loss value is lower than the preset threshold, the model is considered to be good enough. If not, the model parameters need to be further adjusted.

[0166] In this embodiment, stochastic gradient descent (SGD) or other optimization algorithms may be used to adjust the model parameters to reduce the loss value. The model is trained continuously using the adjusted parameters until the loss value is lower than a preset value.

[0167] Among them, Stochastic Gradient Descent (SGD) is an optimization algorithm used to adjust the parameters of machine learning models, especially deep learning models. It is a variant of the gradient descent algorithm and is used to optimize the objective function, that is, to minimize the loss function. In machine learning, a model is built that predicts the output through a set of parameters (or weights). The optimal value of the parameter is found by minimizing the loss function, which measures the difference between the model's predicted value and the true value. The gradient descent algorithm calculates the gradient of the loss function with respect to each parameter (that is, the slope of the loss function on each parameter) and uses the gradient to update the parameters in order to reduce the prediction error.

[0168] Finally, the trained model is tested using the test set to verify the model’s performance. Once the model performs well on the test set, it can be used as a knowledge base model for the actual question-answering system.

[0169] For example, a question-and-answer system can be built to answer questions about exhibits in a science and technology museum. The system collects a series of questions and answers about the exhibits as training samples. By building a convolutional neural network model and dividing the sample into a training set and a test set, the model can be trained to identify the keywords and patterns of the questions and generate corresponding answers. After multiple iterations of training and parameter adjustment, when the model's loss value is lower than the preset value, the model is considered to have been trained and can be used in actual question-and-answer scenarios.

[0170] In this embodiment, through training and optimization, the convolutional neural network model can more accurately understand questions and provide relevant answers, and the automated question-and-answer system can quickly respond to user questions and improve service efficiency.

[0171] Please refer to Figure 2 The embodiment of the present invention further provides a management device for a smart exhibition one-code pass, including:

[0172] The receiving module 11 is used to receive a QR code verification request from a visitor and obtain a request time corresponding to the QR code verification request;

[0173] An extraction module 12, for extracting the identity information of the visitor from the QR code verification request when it is determined that the request time is within the reservation time period;

[0174] The verification module 13 is used to verify the identity information of the visitor. After the verification is passed, the visitor is allowed to enter the exhibition hall, and a list of exhibition halls that the visitor can visit is obtained. A visitor authority list is constructed according to the exhibition hall list and the identity information of the visitor. The visitor authority list is used to record the visitors who have opened all the target exhibition halls and corresponding experience equipment permissions in the exhibition hall list;

[0175] The sending module 14 is used to send the visitor authority list to all target exhibition halls and corresponding experience devices in the exhibition hall list, and complete the visitor's visit authority verification in each target exhibition hall or experience device.

[0176] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0177] A terminal provided by the present invention includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the management method of the smart exhibition one-code pass as described in any one of the above items.

[0178] In one embodiment, the terminal provided in one embodiment of the present application refers to Figure 3 The terminal may be a computer device, and its internal structure may be as follows Figure 3 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected via a system bus. Among them, the processor designed by the computer is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store relevant data of the management method of the smart exhibition one-code pass. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the management method of the smart exhibition one-code pass described in the above embodiment is implemented.

[0179] In one embodiment, the present invention further proposes a storage medium storing computer-readable instructions, which, when executed by one or more processors, enables one or more processors to execute the above-mentioned management method of the smart exhibition one-code pass. The storage medium may be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0180] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0181] Based on the above embodiments, it can be seen that the greatest beneficial effect of the present invention is:

[0182] The management method and terminal of the smart exhibition one-code pass provided by the present invention ensure that only visitors with legal reservations can enter the exhibition hall by verifying the visitor's identity information, thereby enhancing the security management of the exhibition hall; at the same time, by constructing a visitor authority list and accurately controlling the visitor's access rights to the exhibition hall and experience equipment, the exhibition hall resources can be better allocated and utilized, for example, avoiding overcrowded exhibition halls and equipment, and ensuring that every visitor can have a good visiting experience; in addition, by distributing the visitor authority list to each exhibition hall and experience equipment, each exhibition hall and experience equipment independently completes the visitor's identity authentication, without the need for the background to continuously verify the visitor's QR code, avoiding excessive background load and system crash, thereby achieving load balancing.

[0183] The technical features of the above-described embodiments may be arbitrarily combined. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of the technical features, they should be considered to be within the scope of this specification.

[0184] The above-mentioned embodiments only express several implementation methods of the present invention, and the description thereof is relatively specific and detailed, but it cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, which all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention shall be subject to the attached claims.

Claims

1. A management method for a smart exhibition one-code pass, characterized in that: include: Receive a QR code verification request from a visitor, and obtain a request time corresponding to the QR code verification request; When it is determined that the request time is within the reservation time period, extracting the visitor's identity information from the QR code verification request; The identity information of the visitor is verified. After the verification is passed, the visitor is allowed to enter the exhibition hall, and a list of the target exhibition halls that the visitor can visit is obtained. A visit permission list is constructed according to the list of exhibition halls and the identity information of the visitor. The visit permission list is used to record the visitors who have opened all the target exhibition halls and corresponding experience equipment permissions in the list of exhibition halls; The visitor authority list is distributed to all target exhibition halls and corresponding experience devices in the exhibition hall list, and the visitor's visit authority verification is completed in each target exhibition hall or experience device; The verification of the visitor's visiting authority in each of the target exhibition halls or experience devices includes: When the target exhibition hall receives a target QR code verification request displayed by a visitor, the identity information of the visitor is extracted from the target QR code verification request; The target exhibition hall determines whether the visitor is recorded in the corresponding visitor authority list according to the identity information of the visitor; If so, the target exhibition hall allows the visitor to exhibit; When the experience device receives a target QR code verification request displayed by a visitor, the identity information of the visitor is extracted from the target QR code verification request; The experience device determines whether the visitor is recorded in the corresponding visitor authority list according to the identity information of the visitor; If so, the visitor is allowed to use the experience equipment; After the visitor's visiting authority verification is completed in each of the target exhibition halls or experience devices, the method further includes: Acquire multiple pieces of historical exhibition visit data of the visitor; Randomly select any two pieces of historical exhibition visit data from the plurality of historical exhibition visit data in chronological order, concatenate them, and convert them into binary data respectively, to obtain a plurality of visit character strings; Obtain the types, locations and traffic of all historical exhibition halls to obtain exhibition hall data; After converting the exhibition hall data into binary data, a plurality of exhibition hall character strings are obtained; Calculating the visitor's interest in each historical exhibition hall according to the plurality of visit character strings and the plurality of exhibition hall character strings, and generating a visitor interest vector; Obtain the types, locations and traffic of all target exhibition halls, and obtain the target exhibition hall data; Performing vector processing on the target exhibition hall data to obtain a target exhibition hall vector; Calculating the similarity between the visitor's interest vector and the target exhibition hall vector, selecting a first target exhibition hall whose similarity is greater than a preset threshold and recommending it to the visitor; The calculating the visitor's interest in each historical exhibition hall according to the plurality of visit character strings and the plurality of exhibition hall character strings and generating a visitor's interest vector comprises: Set minimum support and minimum confidence; Based on the minimum support and the minimum confidence, all frequent item sets involved in multiple visit character strings and multiple exhibition hall character strings are generated according to the Apriori algorithm, and the frequent item sets are used to characterize the association between the visit character string and the corresponding exhibition hall character string; After weighted summing up the correlation between all visit character strings and the corresponding exhibition hall character strings in the frequent item set, the visitor's interest in each historical exhibition hall is obtained, and multiple visit character strings, multiple exhibition hall character strings and corresponding interest degrees are respectively mapped to a unique position in the high-dimensional space, each position corresponds to a dimension, and the visitor interest vector is obtained.

2. The management method of the smart exhibition one-code pass according to claim 1 is characterized in that: Before receiving the visitor's QR code verification request, it also includes: Obtaining the visitor's identity information and timestamp, and converting the visitor's identity information into a unique identifier according to a hash function to obtain a visitor identification; splicing the visitor identification and the timestamp to obtain splicing information; Encrypting the splicing information and converting it into binary data to obtain target data; The target data is generated into a QR code using a QR code generation library, and the QR code is sent to the visitor.

3. The management method of the smart exhibition one-code pass according to claim 2 is characterized in that: The splicing information is encrypted and converted into binary data to obtain target data, including: Encrypting the splicing information according to a symmetric encryption algorithm to obtain encrypted data; The encrypted data is converted into binary data to obtain target data.

4. The management method of the smart exhibition one-code pass according to claim 1 is characterized in that: After each of the target exhibition halls or experience devices completes the visitor's visit authority verification, the following further includes: Get the current timestamp; Determine whether the current timestamp exceeds the deadline of the visitor's corresponding reservation time period; If so, a deletion instruction is generated and sent to the target exhibition halls and experience devices containing the visitor's corresponding visiting authority list, and each of the target exhibition halls and experience devices deletes the visitor's corresponding visiting authority list.

5. The management method of the smart exhibition one-code pass according to claim 1 is characterized in that: After each of the target exhibition halls or experience devices completes the visitor's visit authority verification, the following further includes: Obtaining the question content about the target exhibition hall or experience equipment sent by the visitor in voice or text form; Performing vectorization processing on the question content to obtain a question vector corresponding to the question content; Inputting the question vector corresponding to the question content into a pre-trained knowledge base model, outputting a plurality of answer contents, screening out the answer contents whose question vectors corresponding to the question content are greater than a preset similarity from the plurality of answer contents, and obtaining the target answer contents, wherein the knowledge base model is a neural network model for analyzing and processing the question content and generating the answer contents; Selecting keywords and key sentences from the target answer content, and generating an answer summary based on the keywords and key sentences; The answer summary is sent to the visitor's terminal.

6. The management method of the smart exhibition one-code pass according to claim 5 is characterized in that: Before inputting the question vector corresponding to the question content into the pre-trained knowledge base model, the method further includes: Acquire multiple training samples, wherein the training samples include reference question content and corresponding reference answer content; Constructing a convolutional neural network model, dividing the plurality of training samples into a training set and a test set according to a preset ratio; Inputting the training set into the convolutional neural network model for multiple iterative training, and calculating the loss value obtained after the multiple iterative training of the convolutional neural network model according to a preset loss function; Determining whether the loss value is lower than a preset value; If not, based on the loss value, adjusting each parameter of the convolutional neural network model using a preset stochastic gradient descent method; The convolutional neural network model with adjusted parameters is iteratively trained again using the training set until the loss value is lower than a preset value, thereby obtaining an initial knowledge base model; The test set is input into the initial knowledge base model for testing, and after the test is passed, a knowledge base model is generated.

7. A terminal, characterized in that: It includes a memory and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the processor executes the steps of the management method of the smart exhibition one-code pass as described in any one of claims 1 to 6.

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