CN117473169A - Text and travel data screening method based on AIGC - Google Patents
Text and travel data screening method based on AIGC Download PDFInfo
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Abstract
The invention relates to the technical field of travel data screening methods, in particular to an AIGC-based travel data screening method, which comprises the following steps: the data analysis module derives the first based on AIGC techniquesTotal number of data platform search keywords, the firstThe number of the good scores with highest corresponding text heat when searching keywords by the data platform is the firstTotal number and the first number of comments with highest corresponding text heat when searching keywords by data platformThe information of the vermicelli quantity corresponding to the sender with the highest text heat degree when the personal data platform searches the keywords is transmitted to the control module; the control module calculates the provincial hot degree factor according to the related information, obtains provincial hot degree information according to the provincial hot degree factor and transmits the provincial hot degree information to the communication module. The AIGC technology can improve the overall processing efficiency and the information extraction accuracy, provide valuable information for tourists, and better reflect mass information based on big data.
Description
Technical Field
The invention relates to the technical field of travel data screening, in particular to an AIGC-based travel data screening method.
Background
AIGC (Artificial Intelligence Generated Content) is a technology for generating relevant content with a proper generalization ability by learning and recognition of existing data based on a technical method for generating artificial intelligence such as a countermeasure network and a large-scale pre-training model.
The core idea of the AIGC technique is to generate content with a certain creative and quality using artificial intelligence algorithms. Through training the model and learning of a large amount of data, the AIGC can generate content related to the input conditions or guiding ideas. For example, by entering keywords, descriptions, or samples, the AIGC may generate articles, images, audio, etc. that match it.
The text travel data are based on advanced technologies such as cloud computing, big data, machine learning, data visualization and the like, are oriented to the text travel industry, gather elements such as resource distribution, data operation, crowd image, full period analysis and the like, realize dynamic passenger flow monitoring aiming at various areas such as scenic spots, vacation areas, cultural blocks, traffic hubs, business circles and the like, and provide a comprehensive big data platform based on passenger flow analysis for clients.
Through extensive searching and reference discovery, a number of methods for screening travel data have been developed, such as those disclosed in the prior art as CN116822503a, which generally include: collecting evaluation information of a travel route as a target text; obtaining candidate words based on consistency parameters and integrity parameters of short words in the target text; word segmentation is carried out on the target text based on the candidate word set; based on word segmentation results, a TF-idf algorithm is adopted to screen a plurality of characteristic words with highest weights; carrying out travel route aggregation based on the feature word set to obtain a travel route group; counting target group indexes, and removing duplication according to feature word sets appearing in a plurality of travel route groups; labeling the characteristic words of each travel route; and inputting the characteristic word set into a neural network model for training based on the labeling data set and the line characteristic sorting characteristics so as to predict the characteristic word set of the target route. The line characteristic analysis method based on text mining can better assist a user in deciding, help the user to understand line information more quickly and accurately, and promote user experience.
However, the processing speed in the prior art is slow, and the experience of the user is poor.
Disclosure of Invention
The invention aims to improve the data screening speed and provides an AIGC-based text and travel data screening method aiming at the defects.
The invention adopts the following technical scheme:
an AIGC-based text travel data screening method comprises the following steps:
s1: the data statistics module is used for counting data and obtaining information of the flow of people to the province in the present annual holiday, the flow of people to the province self-driving tour in the previous annual holiday, the flow of people to the province in the previous annual holiday and the total number of vehicles to the province in the previous annual holiday, and transmitting the information to the control module;
s2: the data presetting module sets the information of the accuracy rate of the self-driving tourist flow, the total number of the data platforms, the accuracy rate of the data platforms and the average number of people in the vehicle, and transmits the information to the control module;
s3: the data analysis module derives the first based on AIGC techniquesTotal number of data platform search keywords, th ∈>The total number of good scores with highest corresponding text heat when searching keywords by the data platform is +.>Total number of comments and +.>The information of the vermicelli quantity corresponding to the sender with the highest text heat degree when the personal data platform searches the keywords is transmitted to the control module;
s4: the control module calculates the traffic flow of people going to the province self-driving trip in the previous annual holiday according to the total number of vehicles going to the province in the previous annual holiday and the average number of people in the vehicles, calculates the province hot degree factor according to the related information, obtains the province hot degree information according to the province hot degree factor and transmits the province hot degree information to the communication module;
s5: and the communication module transmits the provincial hot degree information to the user side.
Optionally, the data analysis module comprises a data acquisition sub-module, a data conversion sub-module, a data screening sub-module and a data transmission sub-module which are sequentially in communication connection, and the data transmission sub-module is in communication connection with the control module;
the data acquisition sub-module is used for acquiring related voice, image and text information and transmitting the information to the data conversion sub-module;
the data conversion submodule converts the related voice and image information into text information, and transmits the converted text information and the text information acquired by the data acquisition submodule to the data screening submodule;
the data screening submodule screens the converted text information and the acquired text information based on the AIGC technology, obtains the screened text information and transmits the screened text information to the data transmission submodule;
the data transmission sub-module obtains the first data according to the filtered text information based on AIGC technologyTotal number of data platform search keywords, th ∈>The total number of good scores with highest corresponding text heat when searching keywords by the data platform is +.>Total number of comments and +.>And the data platform searches the information of the vermicelli quantity corresponding to the sender with the highest text heat when the keyword is searched, and transmits the information to the control module.
Optionally, when the control module calculates the province hot degree factor, the following formula is satisfied:
；
；
wherein,for saving the warm degree factor, ++>For the flow of people who go to the province in the holiday of this year, +.>For the flow of people who go to the province self-driving tour in the holiday of the previous year,/for the person who goes to the province self-driving tour>For counting the accuracy of the flow of the self-driving tourist, < ->For the flow of people who go to the province in the holiday of the previous year,/the person who goes to the province>Total number of data platforms, < >>Is->Total number of data platform search keywords, < ->First->The total number of the criticism with the highest corresponding text heat when searching keywords by the data platform is +.>Is->Total number of comments corresponding to the highest heat of the text when searching keywords by the data platform,/->Is->The amount of vermicelli corresponding to the sender with the highest text heat when searching keywords by the data platform is +.>The accuracy of the statistical data platform is obtained;
for the total number of vehicles going to the province in the holiday of the previous year, < >>Is the average number of people in the vehicle.
Optionally, when the control module calculates the provincial hot degree information, the following formula is satisfied:
；
wherein,for saving the information of the hot degree, +.>A threshold value for selecting a threshold value for saving a threshold value for the threshold value of the threshold value>The time is that the province is low in the hot degree, and the time is +.>The time is the saving and the hot degree is high.
Optionally, in step S1, the data statistics module further obtains information of an average value of the traffic of people going to the scenic spot in the holiday of the previous year and the recommended index set by tourists going to the scenic spot in the holiday of the previous year, and transmits the information to the control module;
in step S2, the data presetting module also sets the firstInformation accuracy index and +.>The information of the weight indexes of the data platforms is transmitted to the control module;
in step S3, the data analysis module also obtains the firstThe data platform searches the information of the total amount of the original texts appearing at the scenic spot and transmits the information to the control module;
in step S4, the control module calculates a provincial hot degree reference index according to the provincial hot degree factor, calculates a crowding degree factor of the provincial scenic spots according to the related information, obtains crowding degree information of the provincial scenic spots according to the crowding degree factor of the provincial scenic spots, and transmits the crowding degree information to the communication module;
in step S5, the communication module transmits congestion information of the scenic spots in the province to the user side.
Optionally, the data filtering submodule further obtains a firstThe data platform searches information of the total amount of the texts appearing at the scenic spot and transmits the information to the control module.
Optionally, when the control module calculates the congestion factor of the scenic spots in the province, the following formula is satisfied:
；
；
wherein,is the crowding degree factor of scenic spots in province, < ->Is->The data platform searches the total amount of texts appearing in the scenic spot, < >>Is->Information accuracy index of individual data platform, +.>Is->Weight index of individual data platform,/->Is the flow of people going to scenic spots in the holiday of the previous year, and is>An average value of recommended indexes set for tourists who go to the scenic spot in the holiday of the previous year;
for provincial hot degree reference index, +.>To->A selection threshold for different provincial preference reference indices, wherein +.></></></>，/>To->The threshold values are selected for different provincial popularity factors.
Optionally, when the control module calculates the congestion degree information of the scenic spots in the province, the following formula is satisfied:
；
wherein,to save the crowding degree of the scenic spotsInformation (I)>A threshold value for selecting the crowding degree factor of scenic spots in province, when +.>The crowding degree of scenic spots in province is low, < ->The crowding degree of scenic spots in provinces is high.
The beneficial effects obtained by the invention are as follows:
1. the AIGC technology can improve the overall processing efficiency and the information extraction accuracy, provide more valuable information for tourists, and better reflect the information of masses based on big data;
2. when the province hot degree factor is calculated, the ratio of the flow of people going to the province in the present holiday and the flow of people going to the province in the previous holiday is taken into consideration, and then the flow of people going to the province self-driving trip in the previous holiday and the data reacted in a data platform are considered, and the influence of the actual flow of people and the network data platform on tourists is comprehensively considered, so that the accuracy of calculating the province hot degree factor is improved;
3. most tourists who travel in the holiday can select comfortable and less-man travel routes, and after provinces of travel are clarified, the control module calculates the crowding degree factors of scenic spots in the provinces and obtains crowding degree information of the scenic spots in the provinces, and the tourists select whether to travel to the scenic spots or not by referring to the crowding degree information of the scenic spots in the provinces, so that the experience of travel is improved;
4. and the AIGC technology can also filter and identify some maliciously-assailed original texts, junk information, fraud information and advertisements, so that the calculation accuracy is improved.
For a further understanding of the nature and the technical aspects of the present invention, reference should be made to the following detailed description of the invention and the accompanying drawings, which are provided for purposes of reference only and are not intended to limit the invention.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a schematic diagram of the overall structure of the present invention;
FIG. 3 is a schematic diagram of a data analysis module according to the present invention;
FIG. 4 is a schematic overall structure of a second embodiment of the present invention;
fig. 5 is a schematic structural diagram of a size measurement module according to a second embodiment of the invention.
Detailed Description
The following embodiments of the present invention are described in terms of specific examples, and those skilled in the art will appreciate the advantages and effects of the present invention from the disclosure herein. The invention is capable of other and different embodiments and its several details are capable of modification and variation in various respects, all without departing from the spirit of the present invention. The drawings of the present invention are merely schematic illustrations, and are not drawn to actual dimensions, and are stated in advance. The following embodiments will further illustrate the related art of the present invention in detail, but the disclosure is not intended to limit the scope of the present invention.
Embodiment one: the present embodiment provides an AIGC-based travel data screening method, which is shown in fig. 1 to 3.
An AIGC-based text travel data screening method comprises the following steps:
s1: the data statistics module is used for counting data and obtaining information of the flow of people to the province in the present annual holiday, the flow of people to the province self-driving tour in the previous annual holiday, the flow of people to the province in the previous annual holiday and the total number of vehicles to the province in the previous annual holiday, and transmitting the information to the control module;
s2: the data presetting module sets the information of the accuracy rate of the self-driving tourist flow, the total number of the data platforms, the accuracy rate of the data platforms and the average number of people in the vehicle, and transmits the information to the control module;
s3: the data analysis module derives the first based on AIGC techniquesTotal number of data platform search keywords, th ∈>The total number of good scores with highest corresponding text heat when searching keywords by the data platform is +.>Total number of comments and +.>The information of the vermicelli quantity corresponding to the sender with the highest text heat degree when the personal data platform searches the keywords is transmitted to the control module;
s4: the control module calculates the traffic flow of people going to the province self-driving trip in the previous annual holiday according to the total number of vehicles going to the province in the previous annual holiday and the average number of people in the vehicles, calculates the province hot degree factor according to the related information, obtains the province hot degree information according to the province hot degree factor and transmits the province hot degree information to the communication module;
s5: and the communication module transmits the provincial hot degree information to the user side.
Specifically, all references to provinces throughout are to be given provinces.
Optionally, the data analysis module comprises a data acquisition sub-module, a data conversion sub-module, a data screening sub-module and a data transmission sub-module which are sequentially in communication connection, and the data transmission sub-module is in communication connection with the control module;
the data acquisition sub-module is used for acquiring related voice, image and text information and transmitting the information to the data conversion sub-module;
the data conversion submodule converts the related voice and image information into text information, and transmits the converted text information and the text information acquired by the data acquisition submodule to the data screening submodule;
the data screening submodule screens the converted text information and the acquired text information based on the AIGC technology, obtains the screened text information and transmits the screened text information to the data transmission submodule;
the data transmission sub-module obtains the first data according to the filtered text information based on AIGC technologyTotal number of data platform search keywords, th ∈>The total number of good scores with highest corresponding text heat when searching keywords by the data platform is +.>Total number of comments and +.>And the data platform searches the information of the vermicelli quantity corresponding to the sender with the highest text heat when the keyword is searched, and transmits the information to the control module.
Optionally, when the control module calculates the province hot degree factor, the following formula is satisfied:
；
；
wherein,for saving the warm degree factor, ++>For the flow of people going to the province in the present holiday, the flow of people going to the province in the present holiday is preferably obtained by the total number of railways, airplanes and ships with specified provinces in all holidays so far; />For the flow of people who go to the province self-driving tour in the holiday of the previous year,/for the person who goes to the province self-driving tour>For counting the accuracy of the flow of the self-driving tourist, < ->For the flow of people going to the province in the holiday of the previous year, the data is preferably directly captured by the data of the relevant statistical platform, such as a website; />Total number of data platforms, < >>Is->The data platform searches for the total number of keywords,first->The total number of the criticism with the highest corresponding text heat when searching keywords by the data platform is +.>Is->Total number of comments corresponding to the highest heat of the text when searching keywords by the data platform,/->Is->The amount of vermicelli corresponding to the sender with the highest text heat when searching keywords by the data platform is +.>The accuracy of the statistical data platform is obtained;
for the total number of vehicles going to the province in the holiday of the previous year, < >>Is the average number of people in the vehicle.
Specifically, the following illustrates the matters to be noted when calculating the popularity factor of the province, for example, 2 months in this month, only the primordial denier and the spring festival before this month, assuming that the legal vacation time corresponding to the primordial denier vacation is 1 month 1 day to 1 month 2 days, the traffic to the province in the vacation mentioned in the calculation is 12 months 30 days (two days earlier than the first day of the legal vacation time) before the year, the total number of railways, airplanes and tickets to the province is purchased between 24 days in the early morning and 1 month 1 day (one day earlier than the last day of the legal vacation time), the total number of railways, airplanes and tickets corresponding to the spring festival is acquired in the same way, and the sum of the total number of primordial denier and the spring festival is the traffic to the province in the present year vacation; the total number of vehicles is calculated through the total travel sum of vehicles counted by all high-speed intersections in the province, for example, A, B and C three high-speed entrances are arranged in the Guangdong province, the vehicles enter high speed from an entrance outside the Guangdong province and then enter the Guangdong province from an exit A of the Guangdong province, the vehicles belong to one of the total number of vehicles, and the vehicles do not belong to one of the total number of vehicles provided that the vehicles enter high speed from the entrance A of the Guangdong province and then enter the target road section from the exit B of the Guangdong province; when a reddish book, a knowledge and a microblog are selected as the data platforms, the total number of the data platforms is 3; calculation of the following exampleThe items to be noted when searching the total amount of the data platform, for example, the time for calculating the provincial popularity factor is 9 months 1 day, then +.>The total number of data platform search keywords corresponds to a time of within 30 days before 9 months 1 day (excluding 9 months 1 day)) First->The total sum of the search amount of each day of the key words of the data platform, the key words refer to provinces, all relevant areas in the provinces, all scenic spot names in the provinces, relevant substance cultural heritage or non-substance cultural heritage, delicacies and the like in the provinces, for example, the Guangdong province is taken as a target province, and the key words of 'blind public cakes', 'Buddha mountain', 'forward and right', 'clear and clean garden', 'Xiqian mountain', 'double skin milk' all belong to the search; the calculation of +.>The method has the advantages that matters needing to be noted when the data platform searches the total number of keywords can be analyzed based on the AIGC technology, historical text content and historical comment behaviors of original authors can be analyzed, including praise, forwarding, attention and other information, so that the text published by some users is determined to have reference value, rather than the garbage text appearing in searching is directly calculated, in addition, some malicious and assailable text, garbage information, fraud information and advertisements can be filtered and identified through the AIGC technology, and therefore calculation accuracy is improved; the calculation of +.>The method comprises the steps that when a personal data platform searches keywords, matters needing to be noted are corresponding to the total evaluation quantity with highest original text heat, wherein the highest original text heat refers to the highest total browsing quantity of the text, and the original text refers to the fact that the original text is published by an original author and is not counted about plagiarism or forwarding; the calculation of +.>Items to be noted when the individual data platform searches keywords and corresponds to the total number of good comments with highest text heat degree are good comments, namely, words with sense such as recommendation, good comments, no defect and the like appear in comments, conversely, words with sense such as lightning protection, non-recommendation, pit stepping and the like appear in comments are bad comments, or AIGC technology can be adopted through natureLanguage processing technology, which analyzes the semantics and emotion of comment content so as to determine the total number of criticisms; the average number of people in the vehicle is set according to the historical data, and the average number of people in the vehicle is generally set to be 3; the method for calculating and counting the accuracy rate of the self-driving tourist flow comprises the following steps: since a certain error exists when the traffic of the self-driving tour is counted, the calculated value is smaller, so that a person skilled in the art can set the range value of the accuracy of the traffic of the self-driving tour to be between 1.1 and 1.3 according to the actual situation, and the accuracy of the traffic of the corresponding self-driving tour is set to be 1.1 according to the road condition of the hot spots corresponding to provinces, for example, if the Sichuan hot spots are only 'rice city butylene', due to the complex topography, the passenger has low requirement on selecting the self-driving tour.
Optionally, when the control module calculates the provincial hot degree information, the following formula is satisfied:
；
wherein,for saving the information of the hot degree, +.>A threshold value for selecting a threshold value for saving a threshold value for the threshold value of the threshold value>The time is that the province is low in the hot degree, and the time is +.>The time is the saving and the hot degree is high.
Optionally, in step S1, the data statistics module further obtains information of an average value of the traffic of people going to the scenic spot in the holiday of the previous year and the recommended index set by tourists going to the scenic spot in the holiday of the previous year, and transmits the information to the control module;
in step S2, the data presetting module also sets the firstInformation accuracy index and +.>The information of the weight indexes of the data platforms is transmitted to the control module;
in step S3, the data analysis module also obtains the firstThe data platform searches the information of the total amount of the original texts appearing at the scenic spot and transmits the information to the control module;
in step S4, the control module calculates a provincial hot degree reference index according to the provincial hot degree factor, calculates a crowding degree factor of the provincial scenic spots according to the related information, obtains crowding degree information of the provincial scenic spots according to the crowding degree factor of the provincial scenic spots, and transmits the crowding degree information to the communication module;
in step S5, the communication module transmits congestion information of scenic spots in provinces to the user terminal
Optionally, the data filtering submodule further obtains a firstThe data platform searches information of the total amount of the texts appearing at the scenic spot and transmits the information to the control module.
Optionally, when the control module calculates the congestion factor of the scenic spots in the province, the following formula is satisfied:
；
；
wherein,is the crowding degree factor of scenic spots in province, < ->Is->The data platform searches the total amount of texts appearing in the scenic spot, < >>Is->Information accuracy index of individual data platform, +.>Is->Weight index of each data platform, which value is empirically set in advance by the staff, is +.>Is the flow of people going to scenic spots in the holiday of the previous year, and is>An average value of recommended indexes set for tourists who go to the scenic spot in the holiday of the previous year;
for provincial hot degree reference index, +.>To->A selection threshold for different provincial preference reference indices, wherein +.></></></>，/>To->The threshold values are selected for different provincial popularity factors.
In particular, the method comprises the steps of,all are different, and the higher the value of the provincial hot degree factor is, the higher the corresponding provincial hot degree reference index is; the average value of recommended indexes set by tourists who go to scenic spots in the holiday of the previous year is calculated, the recommended indexes of the corresponding scenic spots are counted together, the maximum value and the minimum value are removed and then calculated, the numerical range of the recommended indexes set by tourists who go to scenic spots in the holiday of the previous year is set to be 0 to 10, and when the satisfaction degree of tourists to scenic spots is higher, the recommended indexes set by tourists who go to scenic spots in the holiday of the previous year are higher; set the->When the information accuracy index of each data platform is required to be considered, comparing all data of the corresponding data platform with the screened junk data, and if the proportion of the junk data of the corresponding data platform to all data is larger, corresponding +.>The information accuracy index of each data platform is lower; the total number of registered users and the average number of online people of the data platform are considered when the weight index of the data platform is set, and the weight index of the data platform is set to be larger when the total number of registered users and the average number of online people of the day are higher, and is set to be smaller otherwise.
Optionally, when the control module calculates the congestion degree information of the scenic spots in the province, the following formula is satisfied:
；
wherein,for province's congestion degree information of scenic spots in the interior, < ->A threshold value for selecting the crowding degree factor of scenic spots in province, when +.>The crowding degree of scenic spots in province is low, < ->The crowding degree of scenic spots in provinces is high.
The method solves the problem of low screening speed of the traditional text and travel data screening method, and particularly, the AIGC technology can improve the overall processing efficiency and the information extraction accuracy, provide valuable information for tourists, and better reflect mass information based on big data.
In addition, the traditional screening method can not predict the condition of the provincial and popular degree of travel, the control module can obtain the provincial and popular degree information, tourists can plan the travel route conveniently, merchants can be reminded to increase the strength and stock goods through the information, and relevant police force can be reminded to be arranged to adjust the site order.
And when the province hot degree factor is calculated, the ratio of the flow of people going to the province in the present holiday and the flow of people going to the province in the previous holiday is taken into consideration, and then the flow of people going to the province self-driving trip in the previous holiday and the data reacted in the data platform are considered, and the influence of the actual flow of people and the network data platform on tourists is comprehensively considered, so that the accuracy of calculating the province hot degree factor is improved.
Finally, most tourists who travel in the holiday can select comfortable and less-man travel routes, and after the provinces of the travel are clarified, the control module calculates the crowding degree factors of the scenic spots in the provinces and obtains the crowding degree information of the scenic spots in the provinces, and the tourists select whether to travel to the scenic spots or not by referring to the crowding degree information of the scenic spots in the provinces, so that the experience of the travel is improved.
Embodiment two: the present embodiment includes the whole content of the first embodiment, and provides an AIGC-based travel data screening method, which is shown in fig. 4 and 5.
An AIGC-based text travel data screening method comprises the following steps:
in step S1: the size measurement module is also utilized to measure the size and obtain the total area of the province and the distance information between the first scenic spot and the second scenic spot in the province, and the total area and the distance information are transmitted to the control module;
in step S4: the control module calculates the safety degree coefficient between the two scenic spots in the province according to the related information, obtains the safety degree information between the two scenic spots in the province according to the safety degree coefficient between the two scenic spots in the province, and transmits the safety degree information to the communication module;
in step S5: and the communication module transmits the safety degree information between the two scenic spots in the province to the user side.
Optionally, the size measurement module comprises an image shooting sub-module, a target extraction sub-module and a size calculation sub-module which are sequentially in communication connection, and the size calculation sub-module is in communication connection with the control module;
the image shooting sub-module is used for shooting and obtaining shooting images and transmitting the shooting images to the target extraction sub-module;
the target extraction submodule extracts a shooting image according to a set target, obtains a target image and transmits the target image to the size calculation submodule;
the size calculation sub-module obtains the total area of the province according to the target image, obtains the distance information between the first scenic spot and the second scenic spot in the province according to the target image and by combining with navigation software, and transmits the distance information to the control module.
Specifically, the dimension measurement module detects the total area of the province and the distance information between the first scenic spot and the second scenic spot in the province by using the existing visual detection technology, so that the accuracy of overall calculation and the processing speed of the whole method are improved.
Optionally, when the control module calculates the safety degree coefficient between two scenic spots in the province, the following formula is satisfied:
；
wherein,for the safety factor between two scenic spots in province, ++>For the total area of provinces->For the crowding degree information of the first scenic spot in province, +.>For saving the congestion degree information of the second scenic spot in the province, the congestion degree information is all according to the congestion degree information +.>Calculation formula is obtained>For the distance between the first sight and the second sight in the province, the distance is calculated as follows: the size calculation sub-module acquires the central position information of the first scenic spot and the second scenic spot, and then combines the self-driving mode of the navigation software to obtain the shortest distance.
Specifically, the calculation mode of the congestion degree information of the first scenic spot in the province and the calculation mode of the congestion degree information of the second scenic spot in the province are the same as those of the congestion degree information of the scenic spot in the province, and the congestion degree information of the first scenic spot in the province and the congestion degree information of the second scenic spot in the province are only the congestion degree information of the scenic spot in the province for distinguishing two different scenic spots.
Optionally, when the control module calculates the safety degree information between two scenic spots in the province, the following formula is satisfied:
；
wherein,for the security information between two scenic spots in province, +.>A threshold value for the safety factor between two scenic spots in the province is selected as +.>The security degree between two scenic spots in province is high, when +.>The safety degree between two scenic spots in the province is low.
The embodiment solves the problem that the traditional text travel data screening method cannot judge the safety between two scenic spots in the same province, specifically, the embodiment calculates the safety degree coefficient between the two scenic spots in the province through the control module, and obtains the safety degree information between the two scenic spots in the province through the safety degree coefficient between the two scenic spots in the province whenThe safety degree between two scenic spots in the province is low, more police coordination needs to be arranged on a main road between the two scenic spots at the moment, the open time of the scene is prolonged, and merchants around the scenic spots are informed of arranging enough commodities to meet the basic requirements of tourists.
The foregoing disclosure is only a preferred embodiment of the present invention and is not intended to limit the scope of the invention, so that all equivalent technical changes made by the application of the present invention and the accompanying drawings are included in the scope of the invention, and in addition, the elements in the invention can be updated with the technical development.
Claims (8)
1. The text travel data screening method based on AIGC is characterized by comprising the following steps of:
s1: the data statistics module is used for counting data and obtaining information of the flow of people to the province in the present annual holiday, the flow of people to the province self-driving tour in the previous annual holiday, the flow of people to the province in the previous annual holiday and the total number of vehicles to the province in the previous annual holiday, and transmitting the information to the control module;
s2: the data presetting module sets the information of the accuracy rate of the self-driving tourist flow, the total number of the data platforms, the accuracy rate of the data platforms and the average number of people in the vehicle, and transmits the information to the control module;
s3: the data analysis module derives the first based on AIGC techniquesTotal number of data platform search keywords, th ∈>The total number of good scores with highest corresponding text heat when searching keywords by the data platform is +.>Total number of comments and +.>The information of the vermicelli quantity corresponding to the sender with the highest text heat degree when the personal data platform searches the keywords is transmitted to the control module;
s4: the control module calculates the traffic flow of people going to the province self-driving trip in the previous annual holiday according to the total number of vehicles going to the province in the previous annual holiday and the average number of people in the vehicles, calculates the province hot degree factor according to the related information, obtains the province hot degree information according to the province hot degree factor and transmits the province hot degree information to the communication module;
s5: and the communication module transmits the provincial hot degree information to the user side.
2. The text and travel data screening method based on AIGC according to claim 1, wherein the data analysis module comprises a data acquisition sub-module, a data conversion sub-module, a data screening sub-module and a data transmission sub-module which are connected in sequence in a communication manner, and the data transmission sub-module is connected with the control module in a communication manner;
the data acquisition sub-module is used for acquiring related voice, image and text information and transmitting the information to the data conversion sub-module;
the data conversion submodule converts the related voice and image information into text information, and transmits the converted text information and the text information acquired by the data acquisition submodule to the data screening submodule;
the data screening submodule screens the converted text information and the acquired text information based on the AIGC technology, obtains the screened text information and transmits the screened text information to the data transmission submodule;
the data transmission sub-module obtains the first data according to the filtered text information based on AIGC technologyTotal number of data platform search keywords, th ∈>The total number of good scores with highest corresponding text heat when searching keywords by the data platform is +.>Total number of comments and +.>And the data platform searches the information of the vermicelli quantity corresponding to the sender with the highest text heat when the keyword is searched, and transmits the information to the control module.
3. The AIGC-based travel data screening method of claim 2, wherein the control module, when calculating the province popularity factor, satisfies the following equation:
；
；
wherein,for saving the warm degree factor, ++>For the flow of people who go to the province in the holiday of this year, +.>For the flow of people who go to the province self-driving tour in the holiday of the previous year,/for the person who goes to the province self-driving tour>For counting the accuracy of the flow of the self-driving tourist, < ->For the flow of people who go to the province in the holiday of the previous year,/the person who goes to the province>Total number of data platforms, < >>Is->Total number of data platform search keywords, < ->First->The total number of the criticism with the highest corresponding text heat when searching keywords by the data platform is +.>Is->Total number of comments corresponding to the highest heat of the text when searching keywords by the data platform,/->Is->The amount of vermicelli corresponding to the sender with the highest text heat when searching keywords by the data platform is +.>The accuracy of the statistical data platform is obtained;
for the total number of vehicles going to the province in the holiday of the previous year, < >>Is the average number of people in the vehicle.
4. The AIGC-based travel data screening method of claim 3, wherein the control module, when calculating the provincial popularity information, satisfies the following equation:
；
wherein,for saving the information of the hot degree, +.>A threshold value for selecting a threshold value for saving a threshold value for the threshold value of the threshold value>The time is that the province is low in the hot degree, and the time is +.>The time is the saving and the hot degree is high.
5. The method for screening data of travel according to claim 4, wherein in step S1, the data statistics module further obtains information of average values of the traffic of people to the scenic spot in the previous holiday and the recommended indexes set by tourists to the scenic spot in the previous holiday, and transmits the information to the control module;
in step S2, the data presetting module also sets the firstInformation accuracy index and +.>The information of the weight indexes of the data platforms is transmitted to the control module;
in step S3, the data analysis module also obtains the firstThe data platform searches the information of the total amount of the original texts appearing at the scenic spot and transmits the information to the control module;
in step S4, the control module calculates a provincial hot degree reference index according to the provincial hot degree factor, calculates a crowding degree factor of the provincial scenic spots according to the related information, obtains crowding degree information of the provincial scenic spots according to the crowding degree factor of the provincial scenic spots, and transmits the crowding degree information to the communication module;
in step S5, the communication module transmits congestion information of the scenic spots in the province to the user side.
6. The method of claim 5, wherein the data filtering submodule further obtains the first dataThe data platform searches information of the total amount of the texts appearing at the scenic spot and transmits the information to the control module.
7. The AIGC-based travel data screening method of claim 6, wherein the control module, when calculating congestion factors of scenic spots in provinces, satisfies the following equation:
；
；
wherein,is the crowding degree factor of scenic spots in province, < ->Is->The data platform searches the total amount of texts appearing in the scenic spot, < >>Is->Information accuracy index of individual data platform, +.>Is->Weight index of individual data platform,/->Is the flow of people going to scenic spots in the holiday of the previous year, and is>An average value of recommended indexes set for tourists who go to the scenic spot in the holiday of the previous year;
for provincial hot degree reference index, +.>To->Selecting thresholds for different provincial level reference indices, wherein</></></>，/>To->The threshold values are selected for different provincial popularity factors.
8. The AIGC-based travel data screening method of claim 7, wherein the control module, when calculating congestion degree information of scenic spots in provinces, satisfies the following equation:
；
wherein,for province's congestion degree information of scenic spots in the interior, < ->A threshold value for selecting the crowding degree factor of scenic spots in province, when +.>The crowding degree of scenic spots in province is low, < ->The crowding degree of scenic spots in provinces is high.
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| AU2010201127A1 (en) * | 2009-06-09 | 2010-12-23 | Earthcheck Pty Ltd | Sustainability assessment |
| CN109858388A (en) * | 2019-01-09 | 2019-06-07 | 武汉中联智诚科技有限公司 | A kind of intelligent tourism management system |
| CN110795673A (en) * | 2019-10-30 | 2020-02-14 | 成都中科大旗软件股份有限公司 | Comprehensive text and travel management platform based on multidimensional data analysis |
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