Elderly tourism product and experience behavior analysis management system based on big data

Abstract

The invention relates to the technical field of tourism product analysis, in particular to an elderly tourism product and experience behavior analysis management system based on big data. The user terminal obtains feedback content which is input by a user and aims at the tourism product, and then sends the feedback content to the server; the feedback content is processed to obtain text sentences corresponding to the feedback content, and the text sentences are tourism product judgment character evaluation content of the user and are subjected to sentence segmentation processing; the server carries out word recognition on the text sentences on the basis of a tourism item word bank and an emotion judgment word bank and generates an emotion score value corresponding to the feedback content, the emotion score value can reflect the evaluation degree of the user on the tourism product, the feedback content is displayed through the management terminal, and the user experience is improved. And according to the corresponding product numbers and the corresponding emotion score values, management personnel can perform targeted analysis and optimization on the tourism products according to the feedback content and the corresponding emotion score values.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tourism product analysis, and particularly relates to an old-age tourism product and experience behavior analysis management system based on big data. BACKGROUND

[0002] There are many problems in the development and management of current old-age tourism products. On the one hand, the design of tourism products often lacks accurate grasp of the special needs of the old-age group, such as unreasonable itinerary arrangement, insufficient medical security, etc. On the other hand, there is a lack of effective analysis means for the experience and feedback information of old-age tourists in the tourism process, and it is difficult to optimize the tourism product in a timely manner according to the feedback information of tourists. The prior vehicle-mounted user feedback system needs the user to actively wake up or open the interface before performing subsequent operations, whether through voice or touch screen. This feedback method has the shortcomings of long operation process, poor user experience, inability to record logs in time when faults occur, increased difficulty for vehicle manufacturers to solve problems, increased burden on users and R&D personnel for subsequent fault reproduction, and continuous existence of problems after the user forgets to feedback the fault. SUMMARY

[0003] The main purpose of the present application is to provide an old-age tourism product and experience behavior analysis management system based on big data, which aims to solve the problem that current old-age tourism products lack effective analysis means for the experience and feedback information of old-age tourists in the tourism process.

[0004] The technical scheme provided by the present application is as follows: The application discloses an old-age tourism product and experience behavior analysis management system based on big data, which comprises a user terminal, a management terminal and a server; the user terminal and the management terminal are in communication connection with the server; the user terminal is used for obtaining feedback content input by a user for a tourism product, wherein each tourism product is provided with a unique and different product number, and the feedback content is in a text format or an audio format; the feedback content is correspondingly connected with the product number of the tourism product; the feedback content and the corresponding product number are sent to the server; the server is used for performing speech recognition and sentence processing on the feedback content when the feedback content is in a speech format, so as to obtain corresponding text sentences; when the feedback content is in a text format, the feedback content is subjected to sentence processing, so as to obtain corresponding text sentences; a tourism project word library and an emotional judgment word library are obtained; the text sentences are subjected to word recognition based on the tourism project word library and the emotional judgment word library, and an emotional score value corresponding to the feedback content is generated, wherein the higher the emotional score value is, the more positive the experience evaluation of the user for the tourism product is; the feedback content, the corresponding product number and the emotional score value are packaged and sent to the management terminal; the management terminal is used for displaying the feedback content, the corresponding product number and the emotional score value.

[0005] Preferably, the user terminal comprises a microphone and a first display module; the first display module is used for generating a feedback submission page, wherein the feedback submission page comprises a page header area, a text input area and a voice input button, the page header area is used for displaying the name and the product number of the tourism product currently subjected to feedback, and the text input area is used for filling in the feedback content in a text form; the microphone module is used for obtaining the feedback content in an audio format spoken by the user when the voice input button is triggered.

[0006] Preferably, the server is further used for performing speech recognition on the feedback content when the feedback content is in an audio format, so as to obtain corresponding speech text; obtaining and traversing the interval duration between each two adjacent speech texts, marking the middle time point between the two adjacent speech texts as a segmentation time point when the interval duration between the two adjacent speech texts is greater than a first preset duration; segmenting the feedback content in the audio format according to the segmentation time point, so as to obtain a plurality of speech segments; taking the speech text corresponding to each speech segment as the text sentence; taking the speech text corresponding to the entire feedback content as the text sentence when the interval duration between any two adjacent speech texts is not greater than the first preset duration; and segmenting the feedback content based on the punctuation marks in the feedback content when the feedback content is in a text format, so as to obtain the text sentence.

[0007] Preferably, the server stores the travel project word library and the sentiment evaluation word library; the travel project word library includes: scenic spots, scenic areas, landscapes, places, services, staff, routes, flights, trains, catering, food, eating, meals, food, and restaurants; the sentiment evaluation word library includes: good, average, bad, excellent, good-looking, beautiful, suitable, good taste, and bad taste; each word in the sentiment evaluation word library is provided with an evaluation score for expressing the intensity of emotion, and the higher the evaluation score, the more positive the corresponding sentiment evaluation word; the server is further configured to: perform character recognition on the text sentence to obtain sentiment evaluation words and travel project words in the text sentence; determine whether there are other travel project words after the i-th travel project word in the text sentence; if yes, mark the word segment between the i-th travel project word and the i+1-th travel project word in the text sentence as a first to-be-analyzed word segment corresponding to the i-th travel project word; if no, mark all the characters after the i-th travel project word in the text sentence as a second to-be-analyzed word segment corresponding to the i-th travel project word; wherein 1≤i≤I, I is the total number of travel project words in the text sentence; determine whether there are sentiment evaluation words in the first to-be-analyzed word segment or the second to-be-analyzed word segment corresponding to the i-th travel project word, and if yes, establish a corresponding relationship between the sentiment evaluation words in the first to-be-analyzed word segment or the second to-be-analyzed word segment and the i-th travel project word; calculate a sentiment score of the text sentence based on the sentiment evaluation words corresponding to the i-th travel project word; and calculate a sentiment score of the feedback content based on the sentiment score of the text sentence.

[0008] Preferably, the calculation formula for calculating the sentiment score of the text sentence based on the sentiment evaluation words corresponding to the i-th travel project word is: , wherein, is the sentiment score of the text sentence; is the evaluation score of the j-th sentiment evaluation word corresponding to the i-th travel project word in the text sentence; 1≤j≤J, J is the total number of sentiment evaluation words corresponding to the i-th travel project word; , is the total number of sentiment evaluation words corresponding to the i-th travel project word; The calculation formula for calculating the sentiment score of the feedback content based on the sentiment score of the text sentence is: , wherein, is the sentiment score of the feedback content; is the sentiment score of the j-th text sentence of the feedback content, 1≤j≤J, J is the total number of text sentences of the feedback content. ​​

[0009] Preferably, the server is further configured to: acquire all feedback content received in a second preset time period, and corresponding product numbers and emotional score values, every second preset time period, and mark the acquired feedback content as to-be-displayed content; and send the to-be-displayed content and the corresponding product numbers and emotional score values to the management terminal in a package; and the management terminal is further configured to: display the to-be-displayed content in order according to the size of the emotional score values corresponding to the to-be-displayed content.

[0010] Preferably, the management terminal comprises a second display module and a loudspeaker; and the second display module is configured to: generate and display an evaluation display page, wherein the evaluation display page comprises a first tab frame, a second tab frame and a content frame distributed in order from left to right, the first tab frame comprises a plurality of first tabs arranged in order from top to bottom, each first tab is configured to display a different product number, the second tab frame comprises a plurality of second tabs, each second tab is configured to display an emotional score value corresponding to each to-be-displayed content, and the second tabs are arranged in order from top to bottom according to the emotional score values displayed by the second tabs from small to large, when one of the first tabs is clicked to trigger, the emotional score values corresponding to each to-be-displayed content corresponding to the product number in the triggered first tab are displayed in each second tab, when one of the second tabs is clicked to trigger, the to-be-displayed content corresponding to the emotional score value in the triggered second tab is displayed in the content frame on the right, when the to-be-displayed content is in a text format, the to-be-displayed content is directly displayed in the content frame, when the to-be-displayed content is in an audio format, the content frame further displays a play button, and when the play button is clicked to trigger, the to-be-displayed content in the audio format is played through the loudspeaker.

[0011] Preferably, the user terminal is further configured to: when the acquired feedback content is in a text format, generate a text image displaying the feedback content; encrypt the text image to obtain a corresponding encrypted image and decryption data; and send the encrypted image and the decryption data to the server in batches.

[0012] Preferably, the text image is rectangular; the user terminal is further configured to generate an adjustment circle with a radius greater than a preset value in the text image; establish a rectangular coordinate system in the text image, wherein the origin of the rectangular coordinate system is the center of the adjustment circle; evenly divide the adjustment circle according to a preset angle to obtain a plurality of sector regions with the same area, and number the sector regions, wherein the lower straight line segment of the sector region numbered 1 coincides with the horizontal axis of the rectangular coordinate system, the numbers of the subsequent sector regions are sequentially increased in the counterclockwise direction, and the upper straight line segment of the sector region with the largest number coincides with the horizontal axis of the rectangular coordinate system; obtain the encrypted image after performing M times of encryption adjustment operations on the text image, wherein each encryption adjustment operation is as follows: randomly select two different sector regions, swap the image contents of the two selected sector regions, and record the numbers of the two selected sector regions to form a number group; sort the number groups according to the generation order to form a number set; and use the number set, the radius value of the adjustment circle and the preset angle as the decryption data.

[0013] The above technical solution can achieve the following beneficial effects: The big data-based old-age tourism product and experience behavior analysis management system can solve the problem that current old-age tourism products lack effective analysis means for experience and feedback information of old-age tourists in a tourism process. In specific use, a user terminal acquires feedback content input by a user for a tourism product, and then sends the feedback content to a server. The server processes the feedback content in a targeted manner according to the format of the feedback content to obtain a text sentence corresponding to the feedback content. The text sentence is a judgment text evaluation content of the user for the tourism product, and has been processed by sentence segmentation, which is more convenient for subsequent sentiment analysis. The server performs word recognition on the text sentence based on a tourism project word library and a sentiment judgment word library, and generates a sentiment score value corresponding to the feedback content. The sentiment score value can reflect the evaluation degree of the user for the tourism product. Subsequently, a management terminal displays the feedback content, the corresponding product number and the sentiment score value, so that a management personnel can analyze and optimize the tourism product according to the feedback content and the corresponding sentiment score value, thereby further improving the tourism experience of the user. In summary, the technical solution of the present application can effectively collect experience and feedback information of tourists in a tourism process, and can also perform sentiment analysis and scoring on the collected experience and feedback information, thereby subsequently performing targeted optimization. BRIEF DESCRIPTION OF DRAWINGS

[0014] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings required by the embodiments or the prior art description. Obviously, the drawings in the following description only show some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained according to the structures shown in these drawings without creative labor.

[0015] Figure 1 A schematic diagram of a structure of an old-age tourism product and experience behavior analysis management system based on big data according to the present application; Figure 2 A schematic diagram of an evaluation display page of a management terminal of an old-age tourism product and experience behavior analysis management system based on big data according to the present application; Figure 3 A schematic diagram of a text image of an old-age tourism product and experience behavior analysis management system based on big data according to the present application. DETAILED DESCRIPTION

[0016] It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0017] The present application provides an old-age tourism product and experience behavior analysis management system based on big data.

[0018] As shown in the accompanying Figure 1 In an embodiment of the old-age tourism product and experience behavior analysis management system based on big data according to the present application, the old-age tourism product and experience behavior analysis management system based on big data comprises a user terminal (a smart terminal operated by a user participating in tourism, such as a smart phone), a management terminal (a smart terminal used by a management personnel of a tourism operation unit, such as a personal computer) and a server; the user terminal and the management terminal are both communicatively connected to the server; the user terminal is configured to: acquire feedback content input by a user for a tourism product, wherein each tourism product is correspondingly provided with a unique and different product number (to identify each tourism product and feedback content submitted subsequently for different tourism products), and the feedback content is in a text format or an audio format (i.e., the user can submit the feedback content in the form of manually inputting text, or can submit the feedback content in the form of recording audio); establish a corresponding relationship between the feedback content and the product number of the tourism product to which the feedback content corresponds; and send the feedback content and the corresponding product number to the server.

[0019] The server is configured to: when the feedback content is in a voice format, perform voice recognition and sentence segmentation processing on the feedback content to obtain corresponding text sentences (by performing voice recognition and sentence segmentation processing on the feedback content in an audio format to obtain text sentences corresponding to the feedback content, wherein the text sentences are generally multiple); when the feedback content is in a text format, perform sentence segmentation processing on the feedback content to obtain corresponding text sentences; obtain a tourism project word library and an emotional evaluation word library; perform word recognition on the text sentences based on the tourism project word library and the emotional evaluation word library, and generate an emotional score value corresponding to the feedback content (in this embodiment, the emotional score value has a value range of [1, 10]), wherein the higher the emotional score value, the more positive the user's experience evaluation of the tourism product, that is, the higher the user's evaluation of the tourism product and the better the experience; and package and send the feedback content, the corresponding product number and the emotional score value to the management terminal.

[0020] The management terminal is configured to: display the feedback content, the corresponding product number and the emotional score value, so that the management personnel can analyze and optimize the tourism product according to the feedback content and the corresponding emotional score value.

[0021] The old-age tourism product and experience behavior analysis management system based on big data can solve the problem that current old-age tourism products lack effective analysis means for experience and feedback information of old-age tourists in a tourism process. In specific use, a user terminal obtains feedback content input by a user for a tourism product, and then sends the feedback content to a server. According to the format of the feedback content, corresponding processing is performed to obtain text sentences corresponding to the feedback content, wherein the text sentences are judgment text evaluation content of the user for the tourism product and have been subjected to sentence segmentation processing, which is more convenient for subsequent emotional analysis. The server performs word recognition on the text sentences based on a tourism project word library and an emotional evaluation word library, and generates an emotional score value corresponding to the feedback content. The emotional score value can reflect the evaluation of the user for the tourism product. Subsequently, the management terminal displays the feedback content, the corresponding product number and the emotional score value, so that the management personnel can analyze and optimize the tourism product according to the feedback content and the corresponding emotional score value, thereby further improving the tourism experience of the user. In summary, the technical solution of the present application can effectively collect experience and feedback information of tourists in a tourism process, and can also perform emotional analysis and scoring on the collected experience and feedback information, so that subsequent targeted optimization can be performed.

[0022] In addition, the user terminal comprises a microphone and a first display module (e.g. a touch display screen); the first display module is configured to generate a feedback submission page, wherein the feedback submission page comprises a page header area, a text input area and a voice input button, the page header area is configured to display the name and product number of the tourism product currently being fed back, and the text input area is configured to fill in the feedback content in the form of text; the microphone module is configured to obtain the feedback content in the form of audio spoken by the user when the voice input button is triggered.

[0023] Meanwhile, the server is further configured to: when the feedback content is in the form of audio, perform voice recognition on the feedback content to obtain corresponding voice text; obtain and traverse the interval duration between each two adjacent voice texts, and when the interval duration between the two adjacent voice texts is greater than a first preset duration (the normal speaking speed is 200-260 words, and in this embodiment, 240 words per minute, i.e. the interval duration between each word in a normal sentence should be less than 0.05 seconds, and the pause interval duration between each sentence is generally about 0.2 seconds, so in this embodiment, the first preset duration is set to 0.2 seconds), mark the middle time between the two adjacent voice texts as a segmentation time (here, the segmentation time is the middle time between two adjacent sentences); segment the feedback content in the form of audio according to the segmentation time to obtain a plurality of voice segments; and take the voice text corresponding to each voice segment as the text sentence (i.e. one voice segment corresponds to one text sentence).

[0024] Specifically, generally speaking, each sentence corresponds to one matter when a person speaks, and in a tourism review, each sentence generally reviews a certain item (e.g. catering, transportation, accommodation and scenic spots) in tourism; the purpose of this embodiment is to show how to identify and segment the feedback content in the form of text and audio respectively to obtain the corresponding text sentence, which is more convenient for subsequent sentiment analysis.

[0025] In addition, the server stores the travel project word library and the sentiment evaluation word library. The travel project word library includes, but is not limited to, the following: scenic spot, scenic area, landscape, place, service, staff, service staff, attitude, tour guide, reception, price, cost, money, cost performance, accommodation, hotel, room, inn, restaurant, transportation, car, driver, distance, flight, train, catering, food, eating, meal, food, and restaurant. The sentiment evaluation word library includes, but is not limited to, the following: good, general, poor, excellent, beautiful, beautiful, magnificent, stingy, thoughtful, full, fast, slow, on time, friendly, polite, many people, few people, professional, amateur, low, appropriate, delicious, not very used to, good taste, too salty, and bad taste.

[0026] Each word in the sentiment evaluation word library is provided with an evaluation score for expressing the intensity of emotion (the value range of the evaluation score is consistent with the value range of the emotion score, and in this embodiment, is [1, 10]), and the higher the evaluation score, the more positive the corresponding sentiment evaluation word. Specifically, in this embodiment, the following can be used as examples: good (evaluation score is 8), general (evaluation score is 6), poor (evaluation score is 3), excellent (evaluation score is 9), beautiful (evaluation score is 8), beautiful (evaluation score is 8), magnificent (evaluation score is 9), stingy (evaluation score is 2), thoughtful (evaluation score is 9), full (evaluation score is 7), fast (evaluation score is 7), convenient (evaluation score is 8), slow (evaluation score is 4), on time (evaluation score is 8), relatively far (evaluation score is 4), friendly (evaluation score is 9), polite (evaluation score is 9), many people (evaluation score is 7), few people (evaluation score is 6), professional (evaluation score is 9), amateur (evaluation score is 2), low (evaluation score is 3), appropriate (evaluation score is 7), delicious (evaluation score is 8), not very used to (evaluation score is 4), good taste (evaluation score is 9), too salty (evaluation score is 3), and bad taste (evaluation score is 2).

[0027] The server is further configured to: perform character recognition on the text sentence to obtain sentiment evaluation words and travel project words in the text sentence; determine whether there are other travel project words after the i-th travel project word in the text sentence; If so, mark the segment of words between the i-th tourism project word and the (i+1)-th tourism project word in the text sentence as the first segment of words to be analyzed corresponding to the i-th tourism project word; (If a tourism project word appears in the text sentence, then the segment of words between this tourism project word (the i-th tourism project word) and the next tourism project word (the (i+1)-th tourism project word) (i.e., the first segment of words to be analyzed) is highly likely to contain sentiment evaluation words for this tourism project word, and these sentiment evaluation words are valid evaluations for the i-th tourism project word, and need to be used to facilitate the subsequent calculation of sentiment score values). If not, mark all text following the i-th tourism item word in the text sentence as the second segment to be analyzed corresponding to the i-th tourism item word (the second segment to be analyzed is likely to contain sentiment evaluation words for the i-th tourism item word, and these sentiment evaluation words are valid evaluations of the i-th tourism item word, which need to be used to facilitate the subsequent calculation of sentiment score); where 1≤i≤I, and I is the total number of tourism item words in the text sentence; Determine whether there are sentiment judgment words in the first or second segment of words to be analyzed corresponding to the i-th tourism project word; If they exist, establish a correspondence between the sentiment evaluation words in the first or second segment of words to be analyzed corresponding to the i-th tourism project word and the i-th tourism project word; calculate the sentiment score of the text sentence based on the sentiment evaluation words corresponding to the i-th tourism project word; calculate the sentiment score of the feedback content based on the sentiment score of the text sentence.

[0028] For details, see attached. Figure 2 As shown, attached Figure 2 The corresponding negative content includes three text sentences: "Convenient transportation", "Accommodation is relatively far away", and "Diet is not to my liking". It can be seen that: the first tourism item word in the first text sentence is "transportation", the corresponding second word segment to be analyzed is "convenient", and the emotional judgment word in the second word segment to be analyzed is "convenient"; the first tourism item word in the second text sentence is "accommodation", the corresponding second word segment to be analyzed is "relatively far away", and the emotional judgment word in the second word segment to be analyzed is "relatively far away"; the first tourism item word in the third text sentence is "diet", the corresponding second word segment to be analyzed is "not to my liking", and the emotional judgment word in the second word segment to be analyzed is "not to my liking".

[0029] Furthermore, the formula for calculating the sentiment score of the text sentence based on the sentiment evaluation words corresponding to the i-th tourism project words is as follows: , In the formula, The sentiment score for the text sentence; is the evaluation score of the i-th sentiment evaluation word corresponding to the i-th travel project word in the text sentence; 1≤i≤I, I is the total number of the travel project words in the text sentence. is the total number of the sentiment evaluation words corresponding to the i-th travel project word.

[0030] Specifically, as shown in the following table, according to the above embodiment, the sentiment score of the first text sentence is 8, the sentiment score of the second text sentence is 4, and the sentiment score of the third text sentence is 4. Figure 2

[0031] The calculation formula for calculating the sentiment score value corresponding to the feedback content based on the sentiment score value of the text sentence is: In the formula, sentiment score value corresponding to the feedback content is the sentiment score value corresponding to the feedback content; is the sentiment score value of the j-th text sentence of the feedback content, 1≤j≤J, J is the total number of the text sentences of the feedback content.

[0032] Specifically, the sentiment score values of the respective text sentences corresponding to the feedback content are taken as the average value, which is taken as the final sentiment score value corresponding to the feedback content.

[0033] In addition, the server is further configured to: every second preset time length (for example, 1 day), obtain all the feedback contents received in the past second preset time length, and the corresponding product number and sentiment score value, and mark the obtained feedback contents as to-be-displayed contents; package and send the to-be-displayed contents, and the corresponding product number and sentiment score value to the management terminal; the management terminal is further configured to: display the to-be-displayed contents in order according to the size of the sentiment score values corresponding to the to-be-displayed contents.

[0034] Specifically, the to-be-displayed contents are displayed in order according to the size of the sentiment score values corresponding to the to-be-displayed contents, that is, the feedback contents with lower sentiment score values are displayed preferentially, so as to facilitate the management personnel to optimize the travel products.

[0035] ​​​​​​Further, the management terminal comprises a second display module and a loudspeaker; the second display module is configured to generate and display an evaluation display page, wherein the evaluation display page comprises a first tab frame, a second tab frame and a content frame arranged in sequence from left to right, the first tab frame comprises a plurality of first tabs arranged in sequence from top to bottom, each first tab is configured to display a different product number, the second tab frame comprises a plurality of second tabs, each second tab is configured to display an emotional score value corresponding to each to-be-displayed content, and the second tabs are arranged in sequence from top to bottom in the order of the emotional score values displayed by the second tabs from small to large, when one of the first tabs is clicked to trigger, the emotional score values corresponding to each to-be-displayed content corresponding to the product number in the triggered first tab are displayed in each second tab, when one of the second tabs is clicked to trigger, the to-be-displayed content corresponding to the emotional score value in the triggered second tab is displayed in the content frame on the right, when the to-be-displayed content is in text format, the to-be-displayed content is directly displayed in the content frame, when the to-be-displayed content is in audio format, a play button is further displayed in the content frame, and when the play button is clicked to trigger, the to-be-displayed content in audio format is played through the loudspeaker.

[0036] Specifically, the evaluation display page is as shown in the accompanying drawings, which can clearly and clearly display the feedback content of a tourism product, and the second tabs are arranged in sequence from top to bottom in the order of the emotional score values displayed by the second tabs from small to large, so that the manager can preferentially process and analyze the feedback content with a lower emotional score value. Figure 2

[0037] Further, the user terminal is further configured to: when the obtained feedback content is in text format, generate a text image displaying the feedback content; perform encryption processing on the text image to obtain a corresponding encrypted image and decryption data; and send the encrypted image and the decryption data to the server in batches.

[0038] Specifically, in actual application, the feedback content input by the user may contain personal privacy information (for example, the identity information of the staff during the tour, the identity information of the staff at the scenic spot, or even the identity information of the user), which is easy to be stolen during network transmission and cause privacy leakage; therefore, the feedback content is converted into a text image in image format, and then the text image is encrypted to obtain a corresponding encrypted image and decryption data; the encrypted image and the decryption data are sent to the server in batches; thereby avoiding the situation that the text image is stolen during network transmission and causes privacy leakage.

[0039] ​Further, the text image is in a rectangular shape; the user terminal is further configured to generate an adjustment circle with a radius greater than a preset value (set as 85% of the length of the shorter side of the text image) within the text image, wherein the center of the adjustment circle is the center point of the text image; establish a rectangular coordinate system in the text image, wherein the origin of the rectangular coordinate system is the center of the adjustment circle; evenly divide the adjustment circle according to a preset angle (e.g., 10°) to obtain a plurality of sector regions with the same area, and number the sector regions, wherein the lower straight line segment of the sector region numbered 1 coincides with the horizontal axis of the rectangular coordinate system, and the numbering of the subsequent sector regions increases in the counterclockwise direction, and the upper straight line segment of the sector region with the largest number coincides with the horizontal axis of the rectangular coordinate system; and obtain the encrypted image after performing M times of encryption adjustment operations on the text image, wherein each encryption adjustment operation is: randomly selecting two different sector regions, swapping the image contents of the two selected sector regions, and recording the numbers of the two selected sector regions to form a number group; sorting the number groups according to the order of generation to form a number set (the number of number groups in the number set is M); and taking the number set, the radius value of the adjustment circle, and the preset angle as the decryption data.

[0040] Specifically, by the above steps, the text image can be encrypted, so that the feedback content in the text image is no longer readable, and privacy information leakage is avoided; specifically, as shown in FIG. 8, an adjustment circle and a rectangular coordinate system are constructed in the text image, and then a plurality of sector regions are constructed in the adjustment circle; subsequently, the image contents of any two sector regions are randomly swapped to complete image encryption. Figure 3

[0041] ​Meanwhile, the server is further configured to: acquire the encrypted image and the decryption data sent from the user terminal and corresponding to each other; generate an adjustment circle in the encrypted image, wherein a radius of the adjustment circle is a radius value in the decryption data; establish a rectangular coordinate system in the encrypted image, wherein an origin of the rectangular coordinate system is a center of the adjustment circle; uniformly divide the adjustment circle according to a preset angle in the decryption data to obtain a plurality of sector regions with consistent areas, and number the sector regions, wherein a lower straight line segment of the sector region numbered 1 coincides with a horizontal axis of the rectangular coordinate system, the numbering of the subsequent sector regions is sequentially increased in an anticlockwise direction, and an upper straight line segment of the sector region with the largest number coincides with the horizontal axis of the rectangular coordinate system; reversely sort the numbering groups in the numbering set to obtain a new numbering set; and obtain the decrypted image after performing M times of decryption adjustment operations on the encrypted image, wherein before performing the mth decryption adjustment operation, a numbering group with a serial number of m in the new numbering set is marked as a target group, and the target group of the other numbering groups is removed, 1≤m≤M, and each decryption adjustment operation is: selecting two sector regions corresponding to the numbering in the target group, and swapping the image contents of the two selected sector regions.

[0042] Specifically, the encrypted image can be decrypted based on the decryption data through the above steps, and the operation idea is consistent with the above encryption idea, except that the order of the sector regions is swapped and the encryption process is reversed.

[0043] The serial numbers of the above embodiments of the present application are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0044] The embodiments of the present application are described above in combination with the drawings, but the present application is not limited to the above specific embodiments, and the above specific embodiments are only illustrative, but not restrictive, and those skilled in the art can make many forms under the inspiration of the present application without departing from the purpose of the present application and the scope protected by the claims, which are all within the protection of the present application.

Claims

1.A big data-based elderly travel product and experience behavior analysis management system, characterized by, The application relates to a feedback processing method and device for a tourism product, and a system thereof. 2.The big data-based elderly travel product and experience behavior analysis management system of claim 1, wherein, The user terminal comprises a microphone and a first display module; the first display module is used for generating a feedback submission page, wherein the feedback submission page comprises a page header area, a text input area and a voice input button, the page header area is used for displaying the name and product number of the tourism product currently subjected to feedback, and the text input area is used for filling in the feedback content in the form of text; the microphone module is used for acquiring the feedback content in the form of audio spoken by the user when the voice input button is triggered. 3.The big data-based elderly travel product and experience behavior analysis management system of claim 1, wherein, The server is further used for: when the feedback content is in the form of audio, performing voice recognition on the feedback content to obtain corresponding voice text; acquiring and traversing the interval duration between each two adjacent voice texts, marking the middle time point between the two adjacent voice texts as a segmentation time point when the interval duration between the two adjacent voice texts is greater than a first preset duration; segmenting the feedback content in the form of audio according to the segmentation time point to obtain a plurality of voice segments; taking the voice text corresponding to each voice segment as the text sentence; when the interval duration between any two adjacent voice texts is not greater than the first preset duration, taking the voice text corresponding to the entire feedback content as the text sentence; when the feedback content is in the form of text, segmenting the feedback content based on the punctuation marks in the feedback content to obtain the text sentence. 4.The big data-based elderly travel product and experience behavior analysis management system of claim 1, wherein, The tourism project word library and the sentiment judgment word library are stored in the server. The user terminal comprises a microphone and a first display module; the first display module is used for generating a feedback submission page, wherein the feedback submission page comprises a page header area, a text input area and a voice input button, the page header area is used for displaying the name and product number of the tourism product currently subjected to feedback, and the text input area is used for filling in the feedback content in the form of text; the microphone module is used for acquiring the feedback content in the form of audio spoken by the user when the voice input button is triggered. The server is further used for: when the feedback content is in the form of audio, performing voice recognition on the feedback content to obtain corresponding voice text; acquiring and traversing the interval duration between each two adjacent voice texts, marking the middle time point between the two adjacent voice texts as a segmentation time point when the interval duration between the two adjacent voice texts is greater than a first preset duration; segmenting the feedback content in the form of audio according to the segmentation time point to obtain a plurality of voice segments; taking the voice text corresponding to each voice segment as the text sentence; when the interval duration between any two adjacent voice texts is not greater than the first preset duration, taking the voice text corresponding to the entire feedback content as the text sentence; when the feedback content is in the form of text, segmenting the feedback content based on the punctuation marks in the feedback content to obtain the text sentence. The tourism project word library and the sentiment judgment word library are stored in the server. The tourism project word library comprises: scenic spots, scenic areas, landscapes, places, services, staff, routes, flights, trains, catering, diet, eating, meals, food and restaurants; the emotional evaluation word library comprises: good, general, poor, excellent, good-looking, beautiful, suitable, good taste and bad taste; each word in the emotional evaluation word library is provided with an evaluation score for expressing the emotional intensity, and the higher the evaluation score, the more positive the emotion of the corresponding emotional evaluation word; the server is further configured to: perform character recognition on the text sentence to obtain emotional evaluation words and tourism project words in the text sentence; determine whether there are other tourism project words after the i th tourism project word in the text sentence; if yes, mark the word segment between the i th tourism project word and the i+1 th tourism project word in the text sentence as a first to-be-analyzed word segment corresponding to the i th tourism project word; if not, mark all the characters after the i th tourism project word in the text sentence as a second to-be-analyzed word segment corresponding to the i th tourism project word; wherein 1≤i≤I, I is the total number of tourism project words in the text sentence; determine whether there are emotional evaluation words in the first to-be-analyzed word segment or the second to-be-analyzed word segment corresponding to the i th tourism project word, and if yes, establish a corresponding relationship between the emotional evaluation words in the first to-be-analyzed word segment or the second to-be-analyzed word segment corresponding to the i th tourism project word and the i th tourism project word; calculate the emotional score of the text sentence based on the emotional evaluation word corresponding to the i th tourism project word; and calculate the emotional score of the feedback content based on the emotional score of the text sentence. 5.The big data-based senior travel product and experience behavior analysis management system of claim 4, wherein, The calculation formula for calculating the emotional score of the text sentence based on the emotional evaluation word corresponding to the i th tourism project word is: ， In the formula, is the sentiment score value of the text sentence; is the evaluation score value of the i-th sentiment evaluation word corresponding to the i-th tourism project word in the text sentence; 1≤i≤n; , is the total number of sentiment evaluation words corresponding to the i-th tourism project word.​​ The calculation formula for calculating the emotional score of the feedback content based on the emotional score of the text sentence is: ， In the formula, is the emotional score value corresponding to the feedback content; is the emotional score value of the jth text sentence of the feedback content, 1≤j≤J, and J is the total number of text sentences of the feedback content. 6.The big data-based senior travel product and experience behavior analysis management system of claim 1, wherein, The server is further configured to: every second preset time length, obtain all the feedback contents received within the second preset time length, and the corresponding product numbers and emotional scores, and mark the obtained feedback contents as to-be-displayed contents; The to-be-displayed contents, the corresponding product numbers and the emotional scores are packaged and sent to the management terminal; the management terminal is further configured to: display the to-be-displayed contents in order according to the sizes of the emotional scores corresponding to the to-be-displayed contents. 7.The big data-based senior travel product and experience behavior analysis management system of claim 6, wherein, The management terminal comprises a second display module and a loudspeaker; the second display module is configured to generate and display an evaluation display page, wherein the evaluation display page comprises a first tab frame, a second tab frame and a content frame arranged in sequence from left to right, the first tab frame comprises a plurality of first tabs arranged in sequence from top to bottom, each first tab is configured to display a different product number, the second tab frame comprises a plurality of second tabs, each second tab is configured to display an emotional score value corresponding to each content to be displayed, and the second tabs are arranged in sequence from top to bottom in ascending order of the emotional score values displayed by the second tabs, when one of the first tabs is clicked to trigger, the emotional score values corresponding to each content to be displayed corresponding to the product number in the triggered first tab are displayed in each second tab, when one of the second tabs is clicked to trigger, the content to be displayed corresponding to the emotional score value in the triggered second tab is displayed in the content frame on the right, when the content to be displayed is in text format, the content to be displayed is directly displayed in the content frame, when the content to be displayed is in audio format, a play button is further displayed in the content frame, and when the play button is clicked to trigger, the content to be displayed in audio format is played through the loudspeaker. 8.The big data-based senior travel product and experience behavior analysis management system of claim 1, wherein, The user terminal is further configured to: when the obtained feedback content is in text format, generate a text image displaying the feedback content; encrypt the text image to obtain a corresponding encrypted image and decryption data; and send the encrypted image and the decryption data to the server in batches. 9.The big data-based senior travel product and experience behavior analysis management system of claim 8, wherein, The text image is in a rectangular shape; the user terminal is further configured to: generate an adjustment circle with a radius greater than a preset value in the text image; establish a rectangular coordinate system in the text image, wherein the origin of the rectangular coordinate system is the center of the adjustment circle; evenly divide the adjustment circle according to a preset angle to obtain a plurality of sector regions with the same area, and number the sector regions, wherein the lower straight line segment of the sector region numbered 1 coincides with the horizontal axis of the rectangular coordinate system, the numbers of the subsequent sector regions are sequentially increased in the counterclockwise direction, and the upper straight line segment of the sector region with the largest number coincides with the horizontal axis of the rectangular coordinate system; and obtain the encrypted image after performing M times of encryption adjustment operations on the text image, wherein each encryption adjustment operation comprises: randomly selecting two different sector regions, swapping the image contents of the two selected sector regions, and recording the numbers of the two selected sector regions to form a number group; sorting the number groups according to the generation order to form a number set; and taking the number set, the radius value of the adjustment circle and the preset angle as the decryption data.

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