CN111680827A - Working method of cloud computing route planning system based on electronic ticketing - Google Patents
Working method of cloud computing route planning system based on electronic ticketing Download PDFInfo
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Abstract
The invention relates to a working method of a cloud computing route planning system based on electronic ticketing, which comprises the following steps: a tourist attraction ticket selling department obtains tourist information of tourist buying tickets and transmits the information to a cloud server; the cloud server acquires historical ticket information of the user on the Internet according to the user information; the cloud server acquires a numerical value of the recorded scenic spot classification information according to the historical ticketing information, and the recorded scenic spot classification is suitable for scenic spot classification of the current scenic spot; the cloud server sorts the scenic regions according to the recorded scenic region classification information; the tourist uploads the current scenic spot information to the cloud server; the method comprises the steps that a cloud server obtains all scenic spots of a current scenic spot and obtains scenic spot classifications corresponding to the scenic spots; the cloud server sorts all scenic spots of the current scenic spot according to the recorded scenic spot classification; the cloud server screens the scenic spots ranked in the top 50% according to the ranking of all the scenic spots in the current scenic spot; the cloud server connects the scenic spots sequenced in the first 50% in series to form a tour route; the cloud server alternates and recommends the scenic spots ranked at the last 50% on the series-connected tourism routes.
Description
Technical Field
The invention relates to the field of cloud computing and electronic ticketing, in particular to a working method of a cloud computing route planning system based on electronic ticketing.
Background
With the development of the tourism industry and business, more and more people like going out for travel at leisure. Before going out to a tour, a visitor usually queries the information of tourist attractions on a website, but the information that the visitor can query on the website is limited, and a lot of time and energy are consumed. Each scenic spot has a plurality of scenic spots, and the conventional scenic spots cannot plan the tour route of the scenic spots for the tourists according to the actual situation of each scenic spot in the scenic spots. Meanwhile, the existing scenic spot can not provide an individualized scenic spot visiting route for each tourist according to the actual conditions of physical conditions and the like of each tourist. Summarizing, the current major algorithms can be divided into traditional optimization algorithms and modern optimization algorithms. In the conventional optimization algorithm, the method can be divided into an optimal solution algorithm and an approximation method. Traditional optimization algorithms include branch and bound methods, modified-loop methods, greedy algorithms, interpolation methods, and the like. Although the optimal solution method can obtain an accurate solution, the calculation time is not tolerable, so that various approximate methods are generated, and although the approximate algorithms can quickly obtain a feasible solution close to the optimal solution, the approximate method is not satisfactory in the degree of approaching the optimal solution. Therefore, it is desirable to provide a system or method for tourists to plan the tour route according to the situation of the tourists.
Disclosure of Invention
The purpose of the invention is as follows:
aiming at the problem that a system or a method capable of planning a tour route according to the condition of a tourist is urgently needed to be provided for the tourist, the invention provides a working method of a cloud computing route planning system based on electronic ticketing.
The technical scheme is as follows:
a working method of a cloud computing route planning system based on electronic ticketing is used for planning the route of tourists in a scenic spot, and comprises the following steps:
s01: a tourist attraction ticket selling department obtains tourist information of tourist buying tickets and transmits the information to a cloud server;
s02: the cloud server acquires historical ticket information of the user on the Internet according to the user information;
s03: the cloud server acquires a numerical value of the recorded scenic spot classification information according to the historical ticketing information, and the recorded scenic spot classification is suitable for scenic spot classification of the current scenic spot;
s04: the cloud server sorts the scenic regions according to the recorded scenic region classification information;
s05: the tourist uploads the current scenic spot information to the cloud server;
s06: the method comprises the steps that a cloud server obtains all scenic spots of a current scenic spot and obtains scenic spot classifications corresponding to the scenic spots;
s07: the cloud server sorts all scenic spots of the current scenic spot according to the recorded scenic spot classification;
s08: the cloud server screens the scenic spots ranked in the top 50% according to the ranking of all the scenic spots in the current scenic spot;
s09: the cloud server connects the scenic spots sequenced in the first 50% in series to form a tour route;
s10: the cloud server alternates and recommends the scenic spots ranked at the last 50% on the series-connected tourism routes.
As a preferable mode of the present invention, in S02, the cloud server searches the internet for the dynamic information displayed by the guest and determines the dynamic information classification corresponding to the recorded scenic spot classification according to the searched dynamic information, and the cloud server corrects the recorded scenic spot classification order by combining the dynamic information classification.
In a preferred embodiment of the present invention, in the step S04, when performing the classification of the scenic spots, the cloud server acquires a city where the scenic spot is located and a situation of the remaining scenic spots in the city, and determines the classification of the remaining scenic spots.
As a preferred mode of the present invention, in S04, for each city, the cloud server performs user visit number statistics on scenic spots in the city according to the user historical ticket information and sorts the user visit numbers, and the cloud server corrects the scenic spot classification and sorting according to the scenic spot proportion of each scenic spot in the corresponding city.
As a preferred embodiment of the present invention, the method further comprises the steps of:
a01: the method comprises the steps that a cloud server obtains information of a scene area in a city;
a02: the cloud server classifies scenic spots according to the scenic spot information;
a03: the cloud server calculates the proportion of each scenic spot classification of the city in all scenic spots of the city;
a04: the cloud server calculates the weight value of each scenic spot classification through the proportion;
a05: and the cloud server corrects the sequence of the recorded scenic spots according to the weight values.
As a preferable mode of the present invention, for the a04, the weight value is calculated as a ratio of the number of times that the user goes to the scenic spot of the same scenic spot classification in the city to the proportion value of the scenic spot classification in the city.
As a preferable mode of the present invention, for S03, the cloud server replaces the numerical value of the obtained record scenic region classification information according to the historical ticketing information in the same city with the weight value.
As a preferable mode of the present invention, in S10, when performing spot cut, the cloud server acquires the visiting numbers of the visitors of the positions of the last 50% of the scenic spots, sorts the visitors, and performs cut priority determination by the sorting.
The invention realizes the following beneficial effects:
the method comprises the steps of recording the selection preference of scenic spot scenic spots when tourists go out in the past, calculating the weight value of the number of sightseeing times corresponding to the classification of the scenic spot scenic spots, representing the selection preference of a user under the condition of a large number of samples by using the weight value, selecting the scenic spots biased by the user, generating route planning, and solving the problem that a system or a method capable of planning the sightseeing route according to the self condition of the tourists needs to be provided to the tourists urgently.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
FIG. 1 is a diagram illustrating the steps of the present invention;
FIG. 2 is a diagram illustrating the steps of calculating weight values according to the present invention;
fig. 3 is a frame diagram.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
The first embodiment is as follows:
the reference figures are figures 1-3. A working method of a cloud computing route planning system based on electronic ticketing is used for planning the route of tourists in a scenic spot, and comprises the following steps:
s01: a tourist attraction ticket selling department obtains tourist information of tourist buying tickets and transmits the information to a cloud server;
s02: the cloud server acquires historical ticket information of the user on the Internet according to the user information;
s03: the cloud server acquires a numerical value of the recorded scenic spot classification information according to the historical ticketing information, and the recorded scenic spot classification is suitable for scenic spot classification of the current scenic spot;
s04: the cloud server sorts the scenic regions according to the recorded scenic region classification information;
s05: the tourist uploads the current scenic spot information to the cloud server;
s06: the method comprises the steps that a cloud server obtains all scenic spots of a current scenic spot and obtains scenic spot classifications corresponding to the scenic spots;
s07: the cloud server sorts all scenic spots of the current scenic spot according to the recorded scenic spot classification;
s08: the cloud server screens the scenic spots ranked in the top 50% according to the ranking of all the scenic spots in the current scenic spot;
s09: the cloud server connects the scenic spots sequenced in the first 50% in series to form a tour route;
s10: the cloud server alternates and recommends the scenic spots ranked at the last 50% on the series-connected tourism routes.
As a preferable mode of the present invention, in S02, the cloud server searches the internet for the dynamic information displayed by the guest and determines the dynamic information classification corresponding to the recorded scenic spot classification according to the searched dynamic information, and the cloud server corrects the recorded scenic spot classification order by combining the dynamic information classification.
In a preferred embodiment of the present invention, in the step S04, when performing the classification of the scenic spots, the cloud server acquires a city where the scenic spot is located and a situation of the remaining scenic spots in the city, and determines the classification of the remaining scenic spots.
As a preferred mode of the present invention, in S04, for each city, the cloud server performs user visit number statistics on scenic spots in the city according to the user historical ticket information and sorts the user visit numbers, and the cloud server corrects the scenic spot classification and sorting according to the scenic spot proportion of each scenic spot in the corresponding city.
As a preferred embodiment of the present invention, the method further comprises the steps of:
a01: the method comprises the steps that a cloud server obtains information of a scene area in a city;
a02: the cloud server classifies scenic spots according to the scenic spot information;
a03: the cloud server calculates the proportion of each scenic spot classification of the city in all scenic spots of the city;
a04: the cloud server calculates the weight value of each scenic spot classification through the proportion;
a05: and the cloud server corrects the sequence of the recorded scenic spots according to the weight values.
As a preferable mode of the present invention, for the a04, the weight value is calculated as a ratio of the number of times that the user goes to the scenic spot of the same scenic spot classification in the city to the proportion value of the scenic spot classification in the city.
As a preferable mode of the present invention, for S03, the cloud server replaces the numerical value of the obtained record scenic region classification information according to the historical ticketing information in the same city with the weight value.
As a preferable mode of the present invention, in S10, when performing spot cut, the cloud server acquires the visiting numbers of the visitors of the positions of the last 50% of the scenic spots, sorts the visitors, and performs cut priority determination by the sorting.
In the specific implementation process, when a tourist needs to plan a scenic spot route of a scenic spot, the tourist uploads user information, the cloud server acquires historical ticketing information of the user on the internet according to the user information, the historical ticketing information comprises information of scenic spot tickets purchased by the tourist at each ticketing APP, each ticketing website and each ticketing window, the cloud server records the acquired scenic spot ticket information and classifies the scenic spots according to scenic spot classifications, such as historical historic sites, cultural heritage, natural landscapes and the like, the scenic spots are classified according to the classifications, and various scenic spots are counted, namely, each time one scenic spot record is acquired, the scenic spot record is recorded once under the corresponding classification according to the classification of the scenic spot, and the count value is accumulated.
The cloud server searches the dynamic information displayed by the tourists on the internet and judges the dynamic information classification corresponding to the recorded scenic spot classification according to the searched dynamic information, the cloud server corrects the recorded scenic spot classification sequencing by combining the dynamic information classification, namely, the information of the user, such as the tour photos of the XX historical relics, the additional counting of the historical historic site classification and the photos of the XX ancient houses, the additional counting of the cultural heritage classification and the like are obtained through the internet dynamics of the tourists, such as the dynamics publicly displayed in social software, so that the scenic spot classification sequencing is adjusted according to the additional counting.
When the scenic regions are classified, the cloud server acquires the city where the scenic regions are located and other scenic region conditions of the city, the classification of the other scenic regions is judged, for each city, the cloud server carries out user visit frequency statistics on the scenic regions in the city according to the historical ticketing information of the users and sequences the user visit frequencies, and the cloud server corrects the classified sequencing of the scenic regions according to the scenic region proportion of each scenic region in the corresponding city. After the cloud server obtains information of scenic spots in a city, classifying the scenic spots according to the scenic spot information, calculating the proportion of each scenic spot classification in the city, calculating the weight value of each scenic spot classification according to the proportion, and then correcting the recorded scenic spot sequence according to the weight value, namely directly replacing the value of each scenic spot classification of the city with the weight value in the whole classification, wherein for example, the historical historic site proportion of the city A is a, the cultural heritage proportion is b, the natural landscape proportion is c, the historical historic site frequency of the user visiting the city A is M, the weight is calculated to be M/a, and the weight is counted in the frequency of the overall sequence reference instead of the frequency M. And calculating the weight value as the ratio of the times of the user going to the scenic spot classified by the same scenic spot in the city to the ratio of the scenic spot classification ratio value in the city.
And for the scenic spot insertion, namely acquiring the visiting number of visitors of the scenic spots sequenced in the last 50% at the cloud server, sequencing, performing insertion priority judgment through sequencing, acquiring the planned route, thereby acquiring the scenic spots on the route, and inserting the scenic spots sequenced in the front into the planned route according to the sequencing.
The above embodiments are merely illustrative of the technical ideas and features of the present invention, and are intended to enable those skilled in the art to understand the contents of the present invention and implement the present invention, and not to limit the scope of the present invention. All equivalent changes or modifications made according to the spirit of the present invention should be covered within the protection scope of the present invention.
Claims (8)
1. A working method of a cloud computing route planning system based on electronic ticketing is used for planning the route of tourists in a scenic spot, and is characterized by comprising the following steps:
s01: a tourist attraction ticket selling department obtains tourist information of tourist buying tickets and transmits the information to a cloud server;
s02: the cloud server acquires historical ticket information of the user on the Internet according to the user information;
s03: the cloud server acquires a numerical value of the recorded scenic spot classification information according to the historical ticketing information, and the recorded scenic spot classification is suitable for scenic spot classification of the current scenic spot;
s04: the cloud server sorts the scenic regions according to the recorded scenic region classification information;
s05: the tourist uploads the current scenic spot information to the cloud server;
s06: the method comprises the steps that a cloud server obtains all scenic spots of a current scenic spot and obtains scenic spot classifications corresponding to the scenic spots;
s07: the cloud server sorts all scenic spots of the current scenic spot according to the recorded scenic spot classification;
s08: the cloud server screens the scenic spots ranked in the top 50% according to the ranking of all the scenic spots in the current scenic spot;
s09: the cloud server connects the scenic spots sequenced in the first 50% in series to form a tour route;
s10: the cloud server alternates and recommends the scenic spots ranked at the last 50% on the series-connected tourism routes.
2. The method of claim 1, wherein the cloud computing routing system comprises: for the step S02, the cloud server searches for the dynamic information displayed by the guest on the internet and determines the dynamic information classification corresponding to the recorded scenic spot classification according to the searched dynamic information, and the cloud server corrects the recorded scenic spot classification sequence by combining the dynamic information classification.
3. The method of claim 1, wherein the cloud computing routing system comprises: in step S04, when performing the classification of the scenic spots, the cloud server obtains the city where the scenic spot is located and the conditions of the rest of the scenic spots in the city, and determines the classification of the rest of the scenic spots.
4. The method of claim 3, wherein the cloud computing routing system comprises: for the step S04, for each city, the cloud server performs user visit number statistics on scenic spots in the city according to the user historical ticket information and sequences the user visit numbers, and the cloud server corrects the scenic spot classification sequence according to the scenic spot proportion of each scenic spot in the corresponding city.
5. The method of claim 4, wherein the cloud computing routing system comprises: further comprising the steps of:
a01: the method comprises the steps that a cloud server obtains information of a scene area in a city;
a02: the cloud server classifies scenic spots according to the scenic spot information;
a03: the cloud server calculates the proportion of each scenic spot classification of the city in all scenic spots of the city;
a04: the cloud server calculates the weight value of each scenic spot classification through the proportion;
a05: and the cloud server corrects the sequence of the recorded scenic spots according to the weight values.
6. The method of claim 5, wherein the cloud computing routing system comprises: for the A04, calculating the weight value as the ratio of the number of times that the user goes to the scenic spot of the same scenic spot classification in the city to the proportion value of the scenic spot classification in the city.
7. The method of claim 6, wherein the cloud computing routing system comprises: for the step S03, the cloud server replaces the numerical value of the obtained recorded scenic region classification information according to the historical ticketing information in the same city with the weight value.
8. The method of claim 1, wherein the cloud computing routing system comprises: for the step S10, when performing scene cut-through, the cloud server acquires the visiting numbers of the visitors of the positions of the scenic spots ranked in the last 50%, ranks the visitors, and determines the cut-through priority by ranking the visitors.
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