CN110750716A - Automatic recommendation method of scenic spots in intelligent scenic spot, computer equipment and storage medium - Google Patents
Automatic recommendation method of scenic spots in intelligent scenic spot, computer equipment and storage medium Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9537—Spatial or temporal dependent retrieval, e.g. spatiotemporal queries
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/14—Travel agencies
Abstract
The invention discloses an automatic recommendation method of scenic spots in an intelligent scenic spot, computer equipment and a readable storage medium, wherein the method comprises the following steps: when a sight spot query request is received, based on a target ticket identifier, acquiring tourist attribute information of a target passenger who purchases a target ticket with the unique identifier of the target ticket identifier and a sight spot type corresponding to the tourist type determined based on the tourist attribute information, then acquiring total waiting time, next determining a sight spot recommendation priority level based on the total waiting time, and finally pushing the target sight spot information of the target sight spot of the sight spot type in a target sight spot to a client according to the sequence from high to low of the sight spot recommendation priority level, so that the recommendation accuracy of the sight spot is improved, manual interference is not needed, and the recommendation efficiency of the sight spot is improved.
Description
Technical Field
The invention relates to the field of intelligent tourism data processing, in particular to an automatic recommendation method for scenic spots in an intelligent scenic spot, computer equipment and a readable storage medium.
Background
After the physical life of more and more users is satisfied, more and more users begin to pursue the spiritual life, and the travel is a good spiritual life.
At present, under the general condition, adopt artifical mode to recommend the user with the interior scenery spot of wisdom scenic spot to lead to the recommendation inefficiency of the interior scenery spot of wisdom scenic spot, recommend the user with whole scenic spots in the wisdom scenic spot once only simultaneously, but, often different users are different to the browsing demand of scenic spot, thereby lead to the recommendation accuracy of the interior scenery spot of wisdom scenic spot low.
Therefore, finding an efficient and accurate recommendation method for scenic spots in an intelligent scenic spot is a problem that needs to be solved by those skilled in the art.
Disclosure of Invention
The embodiment of the invention provides an automatic recommendation method, computer equipment and a readable storage medium for scenic spots in an intelligent scenic spot, and aims to solve the problems that the recommendation efficiency of the scenic spots in the intelligent scenic spot is low due to the fact that scenic spot recommendation is carried out in a manual mode, and the recommendation accuracy of the scenic spots in the intelligent scenic spot is low due to the fact that scenic spot recommendation is carried out in a one-time full-scale mode.
An automatic recommendation method of scenic spots in an intelligent scenic spot comprises the following steps:
receiving a sight spot query request aiming at a target sight spot in a target sight zone sent by a target passenger through a client, wherein the sight spot query request carries a target ticket identifier;
acquiring tourist attribute information of the target passenger who purchases the target ticket in the target scenic spot with the unique identifier of the target ticket identifier based on the target ticket identifier;
determining a guest type of the target guest based on the guest attribute information;
obtaining a sight spot type corresponding to the tourist type based on a preset type corresponding relation;
acquiring pre-estimated total waiting time required to wait before browsing the target scenic spot;
determining a sight recommendation priority level based on the total waiting time, wherein the total waiting time is negatively correlated with the sight recommendation priority level;
and pushing the target sight spot information of the target sight spot of the sight spot type in the target sight zone to the client according to the sequence of the sight spot recommendation priority levels from high to low, so that the client outputs the target sight spot information according to the sequence of the sight spot recommendation priority levels from high to low.
A computer device comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor executes the computer program to realize the steps of the automatic recommendation method of the scenic spots in the intelligent scenic spot.
A computer-readable storage medium, which stores a computer program, which, when executed by a processor, implements the steps of the above-described method for automatically recommending sights within an intelligent scenic spot.
In the automatic recommendation method, the computer device and the readable storage medium for scenic spots in the intelligent scenic spot, when a scenic spot query request for a target scenic spot in the target scenic spot sent by a target passenger through a client is received, based on a target ticket identifier, tourist attribute information of the target passenger who purchases a target ticket in the target scenic spot with the unique identifier of the target ticket identifier is obtained, and a scenic spot type corresponding to the tourist type determined based on the tourist attribute information is obtained, then a pre-estimated total waiting time required to wait before browsing the target scenic spot is obtained, next, based on the total waiting time, a scenic spot recommendation priority level is determined, and finally, according to the sequence of the scenic spot recommendation priority levels from high to low, the target scenic spot information of the target scenic spot type in the target scenic spot is pushed to the client so that the client can recommend priority level from high to low, target sight spot information is output, so that the target sight spot information of the sight spot which is suitable for the tourist and needs the shortest waiting time can be accurately recommended to the tourist, the recommendation accuracy of the sight spot is improved, manual interference is not needed, and the recommendation efficiency of the sight spot is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a schematic diagram of an application environment of an automatic recommendation method for scenic spots in an intelligent scenic spot according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for automatically recommending scenic spots in an intelligent scenic spot according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a computer device according to an embodiment of the invention.
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 some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The automatic recommendation method of the scenic spots in the intelligent scenic spot can be applied to the application environment shown in fig. 1, wherein the application environment comprises a server and a client, and the client communicates with the server through a wired network or a wireless network. Among other things, the client may be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of a plurality of servers. The client is used for initiating a scenery spot query request of a target scenery spot, and the server is used for responding to the scenery spot query request and sending scenery spot information to the client.
In an embodiment, as shown in fig. 2, an automatic recommendation method for scenic spots in an intelligent scenic spot is provided, which is described by taking the method applied to the service end in fig. 1 as an example, and includes the following steps:
and S10, receiving a sight spot query request which is sent by a target passenger through a client and aims at a target sight spot in a target sight spot, wherein the sight spot query request carries a target entrance ticket identifier.
Specifically, a mobile client carried by a target passenger installs a scenic spot application program, after the target passenger logs in the scenic spot application program on the mobile client, the client receives a target ticket identifier of the target passenger who has purchased a target ticket in the target scenic spot, and simultaneously, when the client receives a confirmation button that the target passenger clicks to inquire scenic spot information, the client generates a scenic spot inquiry request aiming at the target scenic spot in the target scenic spot and sends the scenic spot inquiry request to a server, and the server receives the scenic spot inquiry request in real time or within a preset time interval.
It should be noted that the target ticket identifier uniquely identifies the target ticket, where the target ticket identifier may be a combination of letters and/or numbers, and the specific content of the target ticket identifier may be set according to an actual application, which is not limited herein.
S20, acquiring the attribute information of the tourist who has purchased the target ticket in the target scenic spot with the unique identifier of the target ticket identifier based on the target ticket identifier.
Specifically, when a target traveler successfully purchases tickets in a target scenic spot, the server generates a target ticket identifier, receives visitor attribute information input by the target traveler, and stores the visitor attribute information in the information database.
For example, the information database is a MySQL database, the storage path of the guest attribute information of the target guest who purchases the target ticket in the target scenic spot with the unique identifier of the target ticket identifier is "C: \ ProgramFiles \ MySQL \ MySQLServer 5.0\ data \", firstly, the "C: \ ProgramFiles \ MySQL \ MySQL Server5.0\ data \ is obtained in the MySQL database, and then the guest attribute information is extracted according to the" C: \ ProgramFiles \ MySQL \ MyServer 5.0\ data ".
It should be noted that the attribute information of the guest includes gender, age, academic calendar, hobby, and the like, the information database may be a MySQL database or an oracle database, and the specific content of the attribute information of the guest and the information database may be set according to the actual application, which is not limited herein.
And S30, determining the tourist type of the target passenger based on the tourist attribute information.
Specifically, before determining the guest type of the target guest based on the guest attribute information, the method further includes: acquiring the program type of a scenic spot performance program played by a target scenic spot in a target scenic area; acquiring the moving distance of a target tourist sent by a client in a preset time interval; based on the travel distance and the time interval, the travel speed of the target guest is determined.
Wherein, because different target visitors have different favorite scenic spots, for example, some target visitors prefer scenic spots with beautiful scenery, some target visitors prefer scenic spots with historical culture, some target visitors prefer to go across horse flower, some target visitors prefer to enjoy carefully, so their moving speed in scenic spots is different, the program types performed in different favorite scenic spots of target visitors are different, some target visitors prefer to be funny, some target visitors prefer to be rich in culture background, some tourist types suitable for target visitors need to be determined based on the attribute information of the visitors, the moving speed and the program types, that is, the types of the visitors of the target visitors are determined based on the sex, age, academic history, hobbies, moving speed, program types, etc. of the target visitors acquired in step S30, for example, if the sex of the target visitor obtained in step S30 is male, the age is 8 years, the school calendar is elementary school, and the hobby is sport, the moving speed is 6km/S, and the program genre is fairy, the type of the target visitor is determined to be child sport.
It should be noted that the type of the guest is a type of a target guest, the type of the guest may be a type of sports for children or a type of youth literature, the type of the scenic spot is a type of a target scenic spot, the type of the scenic spot may be a type of scenic beauty or a type of cultural profound, and the specific contents of the type of the guest and the type of the scenic spot may be set according to actual situations.
And S40, acquiring the sight spot type corresponding to the tourist type based on the preset type corresponding relation.
Specifically, based on the type correspondence, the sight spot type corresponding to the guest type determined in step S30 is obtained, for example, if the guest type of the target guest determined in step S30 is a child sport type, a colorful item corresponding to the child sport type is obtained.
And S50, acquiring the pre-estimated total waiting time required to wait before browsing the target scenic spot.
Specifically, receiving the number of target tourists waiting for tourists browsing a target scenic spot in a preset first target time period from a client, wherein the end time of the first target time period is the current system time; acquiring the historical visitor number of the historical visitors who have browsed the target scenic spot in the second target time period; determining the quotient between the second target time period and the historical visitor number as the historical browsing time as the calculated average browsing time; determining the product of the number of the target tourists and the average browsing time as the estimated first waiting time; acquiring the geographical positions of scenic spots of target scenic spots in a target scenic area which is acquired in advance; determining tourist sight spot distances based on the geographical positions of the tourists and the geographical positions of the sight spots; the quotient between the visitor sight distance and the estimated travel speed is determined as an estimated second wait time. The sum between the first latency and the second latency is determined as the total latency. The first waiting time required for queuing and waiting before browsing the target scenic spot and the second waiting time required for the target tourist to move to the target scenic spot are calculated respectively, and then the sum of the first waiting time and the second waiting time is used as the total waiting time, so that the accuracy of determining the waiting time is improved.
The number of the target tourists is the number of the target tourists, and the number of the historical tourists is the number of the historical tourists.
And S60, determining the scenic spot recommendation priority level based on the total waiting time, wherein the total waiting time is inversely related to the scenic spot recommendation priority level.
Specifically, the service end determines the scenery recommendation priority level based on the total waiting time determined in step S50, wherein the total waiting time is negatively correlated with the scenery recommendation priority level, that is, the longer the total waiting time determined in step S50 is, the lower the scenery recommendation priority level is, and otherwise, the shorter the total waiting time determined in step S50 is, the higher the scenery recommendation priority level is. The scenic spot recommendation priority level is a priority level from a recommended target scenic spot to the client, the higher the scenic spot recommendation priority level of the target scenic spot is, the more the service end pushes the target scenic spot information of the target scenic spot to the client, and otherwise, the lower the scenic spot recommendation priority level of the target scenic spot is, the later the service end pushes the target scenic spot information of the target scenic spot to the client.
It should be noted that the target sight information is attribute information of the target sight, such as an entertainment item and a scene effect map of the target sight information being a sight.
And S70, pushing the target sight spot information of the target sight spot of the sight spot type in the target sight zone to the client according to the sequence of the sight spot recommendation priority levels from high to low, so that the client outputs the target sight spot information according to the sequence of the sight spot recommendation priority levels from high to low.
Specifically, the server pushes target sight spot information of a target sight spot of a sight spot type in the target sight zone to the client according to the sequence of the sight spot recommendation priority levels determined in step S60 from high to low, and when the client receives the target sight spot information, the client displays the received target sight spot information on a human-computer interaction interface through a rendering function of a browser, so that a target tourist can browse the target sight spot information through the human-computer interaction interface.
Further, after the target sight information is output according to the order of the sight recommendation priority levels from high to low, the method further comprises the following steps: other sight spot information of other sight spots is randomly pushed to the client, and when the client receives the other sight spot information, the client displays the received other sight spot information on a human-computer interaction interface through the rendering function of the browser, so that a target tourist can browse the other sight spot information through the human-computer interaction interface.
In the embodiment corresponding to fig. 2, when a sight spot query request for a target sight spot in a target sight spot sent by a target passenger through a client is received, based on a target ticket identifier, tourist attribute information of the target passenger who purchases a target ticket in the target sight spot with the unique identifier of the target ticket identifier, and a sight spot type corresponding to the tourist type determined based on the tourist attribute information are obtained, then a pre-estimated total waiting time required to wait before browsing the target sight spot is obtained, then based on the total waiting time, a sight spot recommendation priority level is determined, and finally, according to the sequence of the sight spot recommendation priority levels from high to low, the target sight spot information of the target sight spot in the target sight spot type is pushed to the client, so that the client outputs the target sight spot information according to the sequence of the sight spot recommendation priority levels from high to low, and can accurately recommend the target sight spot information suitable for the sight spot with the shortest waiting time required by the tourist to the client The tourist improves the recommendation accuracy of the scenic spots, meanwhile, manual interference is not needed, and the recommendation efficiency of the scenic spots is improved.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 3. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile readable storage medium, an internal memory. The non-transitory readable storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile readable storage medium. The database of the computer equipment is used for storing data related to the automatic recommendation method of the scenic spots in the intelligent scenic spot. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to realize an automatic recommendation method of scenic spots in an intelligent scenic spot.
In one embodiment, a computer device is provided, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the automatic recommendation method for scenic spots in an intelligent scenic spot, such as the steps S10 to S70 shown in fig. 2.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the method for automatic recommendation of sights within an intelligent scenic spot of the above-described method embodiments. It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. An automatic recommendation method for scenic spots in an intelligent scenic spot is characterized by comprising the following steps:
receiving a sight spot query request aiming at a target sight spot in a target sight zone sent by a target passenger through a client, wherein the sight spot query request carries a target ticket identifier;
acquiring tourist attribute information of the target passenger who purchases the target ticket in the target scenic spot with the unique identifier of the target ticket identifier based on the target ticket identifier;
determining a guest type of the target guest based on the guest attribute information;
obtaining a sight spot type corresponding to the tourist type based on a preset type corresponding relation;
acquiring pre-estimated total waiting time required to wait before browsing the target scenic spot;
determining a sight recommendation priority level based on the total waiting time, wherein the total waiting time is negatively correlated with the sight recommendation priority level;
and pushing the target sight spot information of the target sight spot of the sight spot type in the target sight zone to the client according to the sequence of the sight spot recommendation priority levels from high to low, so that the client outputs the target sight spot information according to the sequence of the sight spot recommendation priority levels from high to low.
2. The method of claim 1, wherein said obtaining a pre-estimated total waiting time to wait before browsing said target attraction comprises:
acquiring a pre-estimated first waiting time required to wait before browsing the target scenic spot;
acquiring pre-estimated second waiting time required to wait before browsing the target scenic spot;
determining a sum between the first latency and the second latency as the estimated total latency.
3. The method of claim 2, wherein before the obtaining a pre-estimated first waiting time to wait before browsing the target attraction, the method further comprises:
receiving the target tourist number of the tourists waiting for browsing the target scenic spots in a preset first target time period from the client, wherein the end time of the first target time period is the current system time;
acquiring pre-calculated average browsing time of the tourist who browses the target scenic spot within a preset second target time period;
and determining the product of the target number of the tourists and the average browsing time as the estimated first waiting time.
4. The method of claim 2, wherein the attraction query request further carries a passenger geographic location of the target passenger, and wherein the method of automatically recommending attractions in an intelligent attraction further comprises, prior to obtaining a second pre-estimated wait time that requires waiting before viewing the target attraction:
acquiring the geographical positions of the scenic spots of the target scenic spot in the target scenic area, which are acquired in advance;
determining tourist attraction distances based on the passenger geographic position and the attraction geographic positions;
and determining the quotient between the tourist attraction distance and the estimated travel speed as the estimated second waiting time.
5. The method of claim 3, wherein before obtaining the pre-computed average browsing time that the target attraction has been browsed by the visitor during the second predetermined target time period, the method further comprises:
acquiring the historical visitor number of the historical visitors who have browsed the target scenic spot in the second target time period;
determining a quotient between the second target time period and the historical number of visitors as a historical browsing time as the calculated average browsing time.
6. The method of automatically recommending sights within a smart scenic spot as recited in any one of claims 1 to 5, wherein prior to said determining the guest type of the target guest based on the guest attribute information, the method of automatically recommending sights within a smart scenic spot further comprises:
acquiring the moving distance of the target tourist sent by the client in a preset time interval;
determining a moving speed of the target guest based on the moving distance and the time interval;
the determining the guest type of the target guest based on the guest attribute information includes:
determining a guest type of the target guest based on the guest attribute information and the moving speed.
7. The method of claim 6, wherein before the obtaining the moving distance of the target visitor from the client within a predetermined time interval, the method further comprises:
acquiring the program type of a scenic spot performance program played by the target scenic spot in the target scenic area;
the determining the guest type of the target guest based on the guest attribute information and the moving speed includes:
determining a guest type of the target guest based on the guest attribute information, the moving speed, and the program type.
8. The method of any one of claims 1 to 5, wherein after the pushing target attraction information of target attractions of the attraction type in the target attraction to the client in order of the attraction recommendation priority levels from high to low for the client to output the target attraction information in order of the attraction recommendation priority levels from high to low, the method of automatically recommending attractions in a smart attraction further comprises:
randomly pushing other sight spot information of other sight spots to the client so that the client randomly outputs the other sight spot information, wherein the other sight spots are the sight spots in the target sight zone except the target sight spot of the sight spot type.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor when executing the computer program implements the method for automatic recommendation of sights within a smart scenic spot of any one of claims 1 to 8.
10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the method for automatically recommending sights in an intelligent scenic spot according to any one of claims 1 to 8.
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| CN111488522A (en) * | 2020-04-07 | 2020-08-04 | 湘潭大学 | Personalized multidimensional scenic spot recommendation method |
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