CN117495619A - Intelligent travel method and system based on big data sharing - Google Patents
Intelligent travel method and system based on big data sharing Download PDFInfo
- Publication number
- CN117495619A CN117495619A CN202311787720.2A CN202311787720A CN117495619A CN 117495619 A CN117495619 A CN 117495619A CN 202311787720 A CN202311787720 A CN 202311787720A CN 117495619 A CN117495619 A CN 117495619A
- Authority
- CN
- China
- Prior art keywords
- travel
- user
- data
- scenic spot
- planning
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 52
- 230000008569 process Effects 0.000 claims abstract description 24
- 238000011156 evaluation Methods 0.000 claims description 24
- 230000006978 adaptation Effects 0.000 claims description 5
- 230000003044 adaptive effect Effects 0.000 claims description 5
- 238000012546 transfer Methods 0.000 claims description 4
- 230000001932 seasonal effect Effects 0.000 claims description 3
- 238000010586 diagram Methods 0.000 description 4
- 230000004308 accommodation Effects 0.000 description 2
- 238000004590 computer program Methods 0.000 description 2
- 230000037213 diet Effects 0.000 description 2
- 235000005911 diet Nutrition 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 230000000284 resting effect Effects 0.000 description 2
- 238000003491 array Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 239000000919 ceramic Substances 0.000 description 1
- 235000019800 disodium phosphate Nutrition 0.000 description 1
- 230000008451 emotion Effects 0.000 description 1
- 238000000802 evaporation-induced self-assembly Methods 0.000 description 1
- 230000010365 information processing Effects 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003340 mental effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000003068 static effect Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- 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—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/14—Travel agencies
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/74—Browsing; Visualisation therefor
- G06F16/743—Browsing; Visualisation therefor a collection of video files or sequences
-
- 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
-
- 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
-
- 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
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0631—Resource planning, allocation, distributing or scheduling for enterprises or organisations
- G06Q10/06315—Needs-based resource requirements planning or analysis
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Engineering & Computer Science (AREA)
- Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Human Resources & Organizations (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- General Engineering & Computer Science (AREA)
- Data Mining & Analysis (AREA)
- Strategic Management (AREA)
- Economics (AREA)
- Multimedia (AREA)
- Marketing (AREA)
- Entrepreneurship & Innovation (AREA)
- General Business, Economics & Management (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Primary Health Care (AREA)
- General Health & Medical Sciences (AREA)
- Health & Medical Sciences (AREA)
- Human Computer Interaction (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present disclosure provides a big data sharing-based intelligent tourism method and system, comprising: receiving a travel planning request sent by a first user through a user side; generating a travel planning video based on travel duration data and travel consumption data of the first user; transmitting a travel planning video to a user; acquiring user browsing data of a first user in the process of browsing the travel planning video, wherein the user browsing data is sent by a user side; determining travel point of interest information of the first user based on the user browsing data; determining travel time of the first user based on the travel interest point information; generating travel planning information based on travel point of interest information, travel time, travel duration data and travel consumption data of the first user; adjusting the travel planning information corresponding to the first user based on the travel planning information corresponding to the second user; and sending the adjusted travel planning information to the user side. Thus, travel planning information adapted to its points of interest is provided while saving user time.
Description
Technical Field
The embodiment of the disclosure relates to the technical field of travel informatization management, in particular to an intelligent travel method and system based on big data sharing.
Background
The tourism is an entertainment activity with a ceramic emotion, people can directly contact with nature in the tourism process to feel rich connotation, and good physical and mental exercises are obtained after busy work, so that knowledge and intelligence are increased.
In the related art, before traveling, tourists need to make travel strategies by themselves, such as viewing travel sharing pictures and travel sharing experiences of other tourists on some social software, selecting scenic spots interested by themselves, and making travel plans by combining with free time of themselves.
However, in the implementation manner, it takes a certain period of time to make a travel plan, and a work is certainly added between busy works, if the made travel plan is not satisfied, it takes time again to make a new travel plan, which takes a long time.
Disclosure of Invention
Embodiments described herein provide a big data sharing based intelligent travel method and system that overcomes the above-referenced problems.
In a first aspect, according to the present disclosure, there is provided a smart travel method based on big data sharing, comprising:
receiving a travel planning request sent by a first user through a user side, wherein the travel planning request comprises the following steps: travel duration data and travel consumption data describing payment planning data for travel trips;
Responding to the travel planning request, and generating a travel planning video based on the travel duration data and the travel consumption data of the first user, wherein the travel planning video comprises multiple frames of images, each frame of image corresponds to one travel browsing information, and the travel browsing information comprises a travel scenic spot area, a travel rest area and a travel food area;
the travel planning video is sent to the user side, so that the first user browses the travel planning video through the user side;
obtaining user browsing data of the first user in the process of browsing the travel planning video, wherein the user browsing data are sent by the user side and comprise: browsing time length of each frame of image;
determining travel point of interest information of the first user based on the user browsing data, wherein the travel point of interest information comprises: intent scenic spot data;
determining travel time of the first user based on the travel point of interest information;
generating travel planning information matched with the first user based on the travel interest point information, the travel time, the travel duration data and the travel consumption data of the first user;
Acquiring a second user with travel associated information from a user database;
based on the travel planning information corresponding to the second user, adjusting the travel planning information corresponding to the first user, wherein the travel planning information corresponding to the second user comprises: historical interest point information, wherein the adjusting the travel planning information corresponding to the first user based on the travel planning information corresponding to the second user includes: adding the historical interest point information into the travel planning information corresponding to the first user;
and sending the adjusted travel planning information of the first user to the user side.
In a second aspect, according to the present disclosure, there is provided a smart travel system based on big data sharing, comprising:
the receiving module is used for receiving a travel planning request sent by a first user through a user side, wherein the travel planning request comprises the following components: travel duration data and travel consumption data describing payment planning data for travel trips;
the first generation module is used for responding to the travel planning request, generating a travel planning video based on the travel duration data and the travel consumption data of the first user, wherein the travel planning video comprises multiple frames of images, each frame of image corresponds to one travel browsing information, and the travel browsing information comprises a travel scenic spot area, a travel rest area and a travel food area;
The first sending module is used for sending the travel planning video to the user side so that the first user can browse the travel planning video through the user side;
the first obtaining module is configured to obtain user browsing data of the first user in the process of browsing the travel planning video, where the user browsing data is sent by the user side and includes: browsing time length of each frame of image;
the determining module is used for determining travel interest point information of the first user based on the user browsing data, wherein the travel interest point information comprises the following components: intent scenic spot data; determining travel time of the first user based on the travel point of interest information;
the second generation module is used for generating travel planning information matched with the first user based on the travel interest point information, the travel time, the travel duration data and the travel consumption data of the first user;
the second acquisition module is used for acquiring a second user with travel association information with the first user from a user database;
the adjustment module is used for adjusting the travel planning information corresponding to the first user based on the travel planning information corresponding to the second user;
And the second sending module is used for sending the adjusted travel planning information of the first user to the user side.
In a third aspect, a computer device is provided, comprising a memory in which a computer program is stored, and a processor, which when executing the computer program, performs the steps of the intelligent tour method according to any of the above embodiments based on big data sharing.
According to the intelligent travel method based on big data sharing, a travel planning request sent by a first user through a user side is received, wherein the travel planning request comprises: travel duration data and travel consumption data, the travel consumption data describing payment planning data for travel trips; responding to a travel planning request, generating a travel planning video based on travel duration data and travel consumption data of a first user, wherein the travel planning video comprises multiple frames of images, each frame of image corresponds to one travel browsing information, and the travel browsing information comprises a travel scenic spot area, a travel rest area and a travel food area; transmitting the travel planning video to a user side so that a first user browses the travel planning video through the user side; user browsing data of a first user in the process of browsing the travel planning video, which is sent by a user side, are obtained, wherein the user browsing data comprises: browsing time length of each frame of image; determining travel interest point information of the first user based on the user browsing data, wherein the travel interest point information comprises: intent scenic spot data; determining travel time of the first user based on the travel interest point information; generating travel planning information matched with the first user based on the travel interest point information, travel time, travel duration data and travel consumption data of the first user; acquiring a second user with travel association information with the first user from a user database; based on the travel planning information corresponding to the second user, the travel planning information corresponding to the first user is adjusted, wherein the travel planning information corresponding to the second user comprises: historical interest point information, based on travel planning information corresponding to a second user, adjusts travel planning information corresponding to a first user, including: adding historical interest point information into travel planning information corresponding to a first user; and sending the adjusted travel planning information of the first user to the user side. Therefore, the user can quickly generate the viewable travel planning video by only providing travel duration data and travel consumption data, the user can conveniently browse and view the video, the travel interest points of the user are captured in the process of viewing the video by the user, travel planning information is generated by combining the user demands, travel planning information adjustment is performed by combining the travel planning information of other related users, the travel planning information of the user is obtained, excessive operations are not needed by the user in the whole process, the travel planning information matched with the interest points of the user is provided while the time of the user is saved, and the travel of the user is effectively promoted.
The foregoing description is only an overview of the technical solutions of the embodiments of the present application, and may be implemented according to the content of the specification, so that the technical means of the embodiments of the present application can be more clearly understood, and the following detailed description of the present application will be presented in order to make the foregoing and other objects, features and advantages of the embodiments of the present application more understandable.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the following brief description of the drawings of the embodiments will be given, it being understood that the drawings described below relate only to some embodiments of the present disclosure, not to limitations of the present disclosure, in which:
fig. 1 is a flow chart of an intelligent tour method based on big data sharing provided in the present disclosure.
Fig. 2 is a schematic structural diagram of an intelligent tourism system based on big data sharing provided by the present disclosure.
Fig. 3 is a schematic structural diagram of a computer device provided in the present disclosure.
It is noted that the elements in the drawings are schematic and are not drawn to scale.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings. It will be apparent that the described embodiments are some, but not all, of the embodiments of the present disclosure. All other embodiments, which can be made by those skilled in the art based on the described embodiments of the present disclosure without the need for creative efforts, are also within the scope of the protection of the present disclosure.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the presently disclosed subject matter belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the specification and relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein. As used herein, a statement that two or more parts are "connected" or "coupled" together shall mean that the parts are joined together either directly or joined through one or more intermediate parts.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearances of the phrase "an embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments.
The term "and/or" is herein merely an association relationship describing an associated object, meaning that there may be three relationships, e.g., a and/or B, may represent: there are three cases, a, B, a and B simultaneously. In addition, the character "/" herein generally indicates that the front and rear associated objects are an "or" relationship. Terms such as "first" and "second" are used merely to distinguish one component (or portion of a component) from another component (or another portion of a component).
In the description of the present application, unless otherwise indicated, the meaning of "plurality" means two or more (including two), and similarly, "plural sets" means two or more (including two).
In order to better understand the technical solutions of the present application, the following description will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of an intelligent tour method based on big data sharing according to an embodiment of the present disclosure. As shown in fig. 1, the specific process of the intelligent tourism method based on big data sharing comprises the following steps:
s110, a travel planning request sent by a first user through a user side is received.
The user side can be a client side or an application program for viewing the travel video of the user.
The travel planning request includes: travel duration data and travel consumption data. Travel duration data such as travel time days, e.g., 3 days, filled in by the user at the user end. The travel consumption data is used for describing payment planning data of the first user for travel, such as total cost amount planned by the user for the travel, wherein the total cost amount comprises bus taking cost, accommodation cost, scenic spot ticket cost, diet cost and the like.
And S120, responding to the travel planning request, and generating a travel planning video based on the travel duration data and the travel consumption data of the first user.
The travel planning video comprises a plurality of frames of images, each frame of image corresponds to one piece of travel browsing information, and the travel browsing information comprises a travel scenic spot area, a travel rest area and a travel food area.
Generating a travel planning video based on travel duration data and travel consumption data of the first user may include: comparing the travel duration data of the first user with the browsing duration of each adjacent scenic spot, and comparing the travel consumption data of the first user with the ticket cost, trip cost, accommodation cost and diet cost of each scenic spot, selecting a plurality of suitable scenic spots, rest areas, food areas and the like, arranging the display sequence of the scenic spots, the rest areas and the food areas based on the position of each scenic spot, and sequentially manufacturing the image/video data corresponding to the scenic spots, the rest areas and the food areas into a travel planning video based on the display sequence. The scenic spot area, the rest area or the food area can be arranged in the same frame image.
In some embodiments, generating a travel planning video based on travel duration data and travel consumption data of a first user includes:
based on the travel duration data and the travel consumption data of the first user, selecting and combining all scenic spot data in a scenic spot database to obtain an initial travel video; acquiring historical tourist attraction data and historical tourist consumption data of a first user; based on the historical tourist attraction data of the first user, deleting the similar scenic spots in the initial travel video; determining a travel attraction and/or a travel food area which does not meet the consumption requirements of the first user based on the historical travel consumption data of the first user; and deleting the travel scenic spot and/or the travel food area in the initial travel video to obtain the travel planning video.
The historical tourist attraction data are browsing attractions in the historical travel process of the first user, and the historical travel consumption data are used for describing single attraction payment data/single food payment data of the first user in the historical travel process.
The travel duration data corresponds to a duration and the travel consumption data corresponds to an amount.
Based on the travel duration data and the travel consumption data of the first user, selecting and combining all scenic spot data in a scenic spot database to obtain an initial travel video, wherein the method comprises the following steps of: and randomly combining a plurality of scenic spot data in each scenic spot data included in the scenic spot database to obtain a plurality of groups of scenic spot combined information, selecting one scenic spot combined information corresponding to the scenic spot browsing total time length which is lower than the time length of the tourist time length data and the scenic spot consumption total amount which is lower than the amount of the tourist consumption data from the plurality of groups of scenic spot combined information, and generating an initial travel video based on the one scenic spot combined information. An initial travel video adapted to the travel needs of the first user is generated based on the travel duration data and the travel consumption data of the first user.
The similar sceneries are used to describe sceneries that have historical cultural similarities to sceneries included in the historical tourist attraction data. The historical cultural similarity is the same as the corresponding historical dynasty of the scenic spot.
Determining travel attractions and/or travel delicacies that do not meet the first user's consumption needs based on the first user's historical travel consumption data, comprising: if the amount corresponding to the single scenic spot payment data is less than the charging amount of one travel scenic spot, and/or the amount of the single food payment data is less than the charging amount of one travel food area, determining that one travel scenic spot is a travel scenic spot which does not meet the consumption requirement of the first user, and/or one travel food area is a travel food area which does not meet the consumption requirement of the first user.
That is, if the amount corresponding to the single scenic spot payment data is less than the charged amount of one travel scenic spot, and the amount of the single food payment data is less than the charged amount of one travel food area, determining that one travel scenic spot is a travel scenic spot which does not meet the consumption requirement of the first user. If the amount corresponding to the single scenic spot payment data is less than the charged amount of one of the travel scenic spots, determining one of the travel scenic spots as the travel scenic spot which does not meet the consumption requirement of the first user. If the amount of the single food payment data is less than the charged amount of one travel food area, determining one travel scenic spot as the travel scenic spot which does not meet the consumption requirement of the first user.
The initial travel video is formulated based on the location of each attraction and the estimated number of travel people. Thus, it is convenient to show the first user the neighboring scenic spot environment while avoiding crowding during the user's travel.
S130, transmitting the tour planning video to the user side.
And sending the travel planning video to the user side so that the first user can browse the travel planning video through the user side.
S140, user browsing data of the first user in the process of browsing the tour planning video, which is sent by the user side, are obtained.
Wherein, the user browses the data and includes: browsing time length of each frame of image.
In some embodiments, obtaining user browsing data of a first user sent by a user terminal in a process of browsing a travel planning video includes:
the method comprises the steps of receiving the stay time of a first user in a display page corresponding to each frame of image and the triggering operation of the first user in the display page corresponding to each frame of image, wherein the stay time is sent by a user side; and determining the browsing time length of the first user for browsing each frame of image based on the stay time length of the first user in the corresponding display page of each frame of image and the triggering operation of the first user in the corresponding display page of each frame of image.
The triggering operation of the first user in the display page corresponding to each frame of image can be amplifying, translating, sliding and the like.
The display page corresponding to each frame of image can switch the display content in the image based on the triggering operation, for example, the display page corresponding to each frame of image can switch the display content displayed by the current page to the enlarged content (i.e. the associated content) of the local image in the current page based on the enlarging operation, and the display page corresponding to each frame of image can switch the display content displayed by the current page to other content corresponding to the display content based on the sliding/shifting operation.
The browsing time length of the first user for browsing each frame of image is the sum of the stay time length of the first user in the corresponding display page of each frame of image and the stay time length of other pages generated by triggering operation in the corresponding display page of each frame of image.
S150, determining the travel interest point information of the first user based on the user browsing data.
The travel interest point information comprises the following steps: intent scenic spot data. The travel point of interest information may include a plurality of intent scenic spot data, which may be represented as intent scenic spot identifications, such as scenic spot names, scenic spot types, scenic spot aliases, and the like.
In some embodiments, determining travel point of interest information for the first user based on the user browsing data includes:
Extracting interest scenic spots of a first user based on user browsing data; matching associated scenic spots corresponding to the interesting scenic spots from other travel planning videos; travel point of interest information for the first user is determined based on the points of interest and the associated points of interest.
Wherein, based on the user browsing data, extracting the interest scenic spot of the first user may include: and determining the scenic spot corresponding to the browsing time length of each frame of image browsed by the first user being longer than or equal to the preset time length as the interested scenic spot.
The associated scenic spot is a position association relationship or a scenic spot association relationship between the associated scenic spot and the interested scenic spot, wherein the position relationship indicates that the distance between the associated scenic spot and the interested scenic spot is smaller than or equal to a preset distance threshold value, and the scenic spot association relationship indicates that the associated scenic spot and the interested scenic spot have historical association (such as the same historical period to which scenic spot culture belongs, the same historical period to which scenic spot buildings belong, and the like).
Therefore, the travel interest point information of the first user is determined based on the interest point of the first user and the associated scenic spot, so that the scenic spot associated with the interest point of the user can be found out to make a travel plan, the requirements of the user are more adapted, and meanwhile, the travel culture can be known.
S160, determining travel time of the first user based on the travel interest point information, and generating travel planning information matched with the first user based on the travel interest point information, the travel time, the travel duration data and the travel consumption data of the first user.
In some embodiments, determining the travel time of the first user based on the travel point of interest information includes:
acquiring the current optimal browsing time period and the current travel adaptation time of each intention scenic spot in the travel interest point information; matching the current optimal browsing time period, the travel duration data and the current travel adaptation time of each intention scenic spot, and removing the unmatched scenic spots from the travel interest point information; and planning the travel time of the first user based on the current optimal browsing time period of the rest intention scenic spot.
The current optimal browsing time period is the optimal browsing time period of the scenic spot under the current moment when the first user initiates the travel planning request. The current travel adaptation travel time is the time suitable for traveling in the current seasonal environment.
Therefore, under the travel time of the first user, an adaptive tourist attraction is selected for the first user so as to plan travel time, and the problem that the user travel experience is affected when the first user directly arrives at a scenic spot which is not suitable for current time travel is avoided.
In some embodiments, generating travel planning information matching the first user based on travel point of interest information, travel time, travel duration data, and travel consumption data of the first user includes:
acquiring historical trip consumption data of a first user; determining travel planning information corresponding to the first user based on the historical travel consumption data, travel time, travel interest point information and travel duration data of the first user; and planning the travel browsing sequence of each intention scenic spot in the travel interest point information based on the travel planning information to obtain the travel planning information matched with the first user.
Wherein the historical trip consumption data is used to describe ride payment data, such as ride payment amounts, of the first user during the historical trip.
The travel planning information is used for describing the vehicle identification and the vehicle transfer time when the first user goes out.
Therefore, the adapted travel planning information is planned for the first user based on the consumption habit/consumption requirement of the first user, so that the travel expense of the user is effectively saved, and the user can browse the interested places.
S170, acquiring a second user with travel related information from the user database, and adjusting the travel planning information corresponding to the first user based on the travel planning information corresponding to the second user.
The travel related information indicates that the second user and the first user have at least one of the following information, wherein the at least one of the following information comprises: travel duration data, travel consumption data, travel point of interest information, user browsing data, travel time, historical travel point data, and historical travel consumption data.
The travel planning information corresponding to the second user comprises: historical interest point information, based on travel planning information corresponding to a second user, adjusts travel planning information corresponding to a first user, including: and adding historical interest point information into the travel planning information corresponding to the first user. Meanwhile, the travel duration data and the travel consumption data in the travel planning information can be adjusted based on the browsing time and the browsing duration of the added historical interest point information.
S180, the adjusted travel planning information of the first user is sent to the user side.
And sending the adjusted travel planning information of the first user to the user side, so that the first user can view the travel planning information through the user side.
In some embodiments, after sending the adjusted travel planning information of the first user to the user side, the method further includes:
Sending a planning evaluation request of the travel planning information to a user; receiving planning evaluation data sent by a first user through a user side; generating planning information update data based on the time evaluation data and the scenic spot evaluation data; updating the travel planning information based on the planning information update data; and sending updated travel planning information and planning information updating data to the user side.
Wherein, the planning evaluation data comprises: the time evaluation data and scenic spot evaluation data can be used for describing scoring values respectively corresponding to browsing time, browsing duration, resting time, resting duration, riding time and riding duration of each scenic spot in the travel planning information by the first user. The attraction evaluation data may be used to describe a scoring value for the first user's satisfaction with each attraction planned.
Generating planning information update data based on the time evaluation data and the scenic spot evaluation data may include: and if any score value in the time evaluation data is lower than the preset score threshold, changing the corresponding planning content, and if any score value in the scenic spot evaluation data is lower than the preset score threshold, changing the corresponding planning scenic spot to obtain the planning information updating data. The planning information update data may include: to be changed and replaced, such as replacing an a scenic spot with a B scenic spot.
Therefore, the updated travel planning information and the updated planning information data are sent to the user side, so that the user can clearly know the modified data while viewing the travel planning information.
According to the intelligent travel method based on big data sharing, a travel planning request sent by a first user through a user side is received, wherein the travel planning request comprises: travel duration data and travel consumption data, the travel consumption data describing payment planning data for travel trips; responding to a travel planning request, generating a travel planning video based on travel duration data and travel consumption data of a first user, wherein the travel planning video comprises multiple frames of images, each frame of image corresponds to one travel browsing information, and the travel browsing information comprises a travel scenic spot area, a travel rest area and a travel food area; transmitting the travel planning video to a user side so that a first user browses the travel planning video through the user side; user browsing data of a first user in the process of browsing the travel planning video, which is sent by a user side, are obtained, wherein the user browsing data comprises: browsing time length of each frame of image; determining travel interest point information of the first user based on the user browsing data, wherein the travel interest point information comprises: intent scenic spot data; determining travel time of the first user based on the travel interest point information; generating travel planning information matched with the first user based on the travel interest point information, travel time, travel duration data and travel consumption data of the first user; acquiring a second user with travel association information with the first user from a user database; based on the travel planning information corresponding to the second user, the travel planning information corresponding to the first user is adjusted, wherein the travel planning information corresponding to the second user comprises: historical interest point information, based on travel planning information corresponding to a second user, adjusts travel planning information corresponding to a first user, including: adding historical interest point information into travel planning information corresponding to a first user; and sending the adjusted travel planning information of the first user to the user side. Therefore, the user can quickly generate the viewable travel planning video by only providing travel duration data and travel consumption data, the user can conveniently browse and view the video, the travel interest points of the user are captured in the process of viewing the video by the user, travel planning information is generated by combining the user demands, travel planning information adjustment is performed by combining the travel planning information of other related users, the travel planning information of the user is obtained, excessive operations are not needed by the user in the whole process, the travel planning information matched with the interest points of the user is provided while the time of the user is saved, and the travel of the user is effectively promoted.
Fig. 2 is a schematic structural diagram of an intelligent tourism system based on big data sharing according to the present embodiment. The intelligent travel system based on big data sharing can comprise: the device comprises a receiving module 210, a first generating module 220, a first transmitting module 230, a first acquiring module 240, a determining module 250, a second generating module 260, a second acquiring module 270, an adjusting module 280 and a second transmitting module 290.
The receiving module 210 is configured to receive a travel planning request sent by a first user through a user side, where the travel planning request includes: travel duration data and travel consumption data describing payment planning data for travel trips.
The first generation module 220 is configured to generate, in response to the travel planning request, a travel planning video based on travel duration data and travel consumption data of the first user, where the travel planning video includes multiple frames of images, each frame of image corresponds to one travel browsing information, and the travel browsing information includes a travel scenic spot area, a travel rest area, and a travel food area.
The first sending module 230 is configured to send the travel planning video to the user side, so that the first user browses the travel planning video through the user side.
The first obtaining module 240 is configured to obtain user browsing data of the first user in the process of browsing the travel planning video, where the user browsing data includes: browsing time length of each frame of image.
The determining module 250 is configured to determine, based on the user browsing data, travel point of interest information of the first user, where the travel point of interest information includes: intent scenic spot data; based on the travel point of interest information, a travel time of the first user is determined.
The second generation module 260 is configured to generate travel planning information matched with the first user based on the travel interest point information, travel time, travel duration data, and travel consumption data of the first user.
A second obtaining module 270 is configured to obtain, from the user database, a second user having travel-related information with the first user.
The adjustment module 280 is configured to adjust the travel planning information corresponding to the first user based on the travel planning information corresponding to the second user, where the travel planning information corresponding to the second user includes: the historical interest point information adjusting module 280 is specifically configured to: and adding historical interest point information into the travel planning information corresponding to the first user.
The second sending module 290 is further configured to send the adjusted travel planning information of the first user to the user side.
In this embodiment, optionally, the first generating module 220 includes:
the combination unit is used for selecting and combining all scenic spot data in the scenic spot database based on the travel duration data and the travel consumption data of the first user so as to obtain an initial travel video, and is specifically used for: and randomly combining a plurality of scenic spot data in each scenic spot data included in the scenic spot database to obtain a plurality of groups of scenic spot combined information, selecting one scenic spot combined information corresponding to the scenic spot browsing total time length which is lower than the time length of the tourist time length data and the scenic spot consumption total amount which is lower than the amount of the tourist consumption data from the plurality of groups of scenic spot combined information, and generating an initial travel video based on the one scenic spot combined information.
The acquisition unit is used for acquiring historical tourist attraction data and historical tourist consumption data of the first user, wherein the historical tourist consumption data is used for describing single attraction payment data or single food payment data of the first user in the historical travel process.
And the first deleting unit is used for deleting similar sceneries in the initial travel video based on the historical tourist attraction data of the first user, wherein the similar sceneries are used for describing sceneries with historical cultural similarity with sceneries included in the historical tourist attraction data.
The determining unit is used for determining a travel scenic spot and/or a travel food area which do not meet the consumption requirement of the first user based on the historical travel consumption data of the first user, and is specifically used for: if the amount corresponding to the single scenic spot payment data is less than the charging amount of one travel scenic spot, and/or the amount of the single food payment data is less than the charging amount of one travel food area, determining that one travel scenic spot is a travel scenic spot which does not meet the consumption requirement of the first user, and/or one travel food area is a travel food area which does not meet the consumption requirement of the first user.
And the second deleting unit is used for deleting the travel scenic spot and/or the travel food area in the initial travel video to obtain the travel planning video.
In this embodiment, the optional second generating module 260 is specifically configured to:
acquiring historical trip consumption data of a first user, wherein the historical trip consumption data is used for describing riding payment data of the first user in a historical trip process; determining travel planning information corresponding to the first user based on the historical travel consumption data, travel time, travel interest point information and travel duration data of the first user, wherein the travel planning information is used for describing a riding vehicle identifier and a vehicle transfer time when the first user goes out; and planning the travel browsing sequence of each intention scenic spot in the travel interest point information based on the travel planning information to obtain the travel planning information matched with the first user.
In this embodiment, the optional determining module 250 is specifically configured to:
extracting interest scenic spots of a first user based on user browsing data; matching associated scenic spots corresponding to the interesting scenic spots from other tour planning videos, wherein the associated scenic spots have position association relations or scenic spot association relations with the interesting scenic spots; travel point of interest information for the first user is determined based on the points of interest and the associated points of interest.
In this embodiment, optionally, the first obtaining module 240 is specifically configured to:
receiving the stay time of a first user in a display page corresponding to each frame of image and the triggering operation in the display page corresponding to each frame of image, wherein the display page corresponding to each frame of image can switch the display content in the image based on the triggering operation; and determining the browsing time length of the first user for browsing each frame of image based on the stay time length of the first user in the corresponding display page of each frame of image and the triggering operation of the first user in the corresponding display page of each frame of image.
In this embodiment, the optional determining module 250 is specifically configured to:
acquiring the current optimal browsing time period and the current travel adaptive travel time of each intention scenic spot in the travel interest point information, wherein the current travel adaptive travel time is the time suitable for traveling in the current seasonal environment; matching the current optimal browsing time period, the travel duration data and the current travel adaptation time of each intention scenic spot, and removing the unmatched scenic spots from the travel interest point information; and planning the travel time of the first user based on the current optimal browsing time period of the rest intention scenic spot.
In this embodiment, optionally, the method further includes: the device comprises a third sending module, a third generating module and an updating module.
And the third sending module is used for sending a planning evaluation request of the travel planning information to the user side.
The receiving module 210 is further configured to receive planning evaluation data sent by the first user through the user side, where the planning evaluation data includes: time assessment data and scenic spot assessment data.
And the third generation module is used for generating planning information updating data based on the time evaluation data and the scenic spot evaluation data.
And the updating module is used for updating the data based on the planning information and updating the travel planning information.
And the third sending module is also used for sending updated travel planning information and planning information updating data to the user side.
The intelligent tourism system based on big data sharing provided by the disclosure can execute the method embodiment, and the specific implementation principle and technical effects of the method embodiment can be seen, and the disclosure is not repeated here.
The embodiment of the application also provides computer equipment. Referring specifically to fig. 3, fig. 3 is a basic structural block diagram of a computer device according to the present embodiment.
The computer device includes a memory 310 and a processor 320 communicatively coupled to each other via a system bus. It should be noted that only computer devices having components 310-320 are shown in the figures, but it should be understood that not all of the illustrated components are required to be implemented and that more or fewer components may be implemented instead. It will be appreciated by those skilled in the art that the computer device herein is a device capable of automatically performing numerical calculations and/or information processing in accordance with predetermined or stored instructions, the hardware of which includes, but is not limited to, microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASICs), programmable gate arrays (fields-Programmable Gate Array, FPGAs), digital processors (Digital Signal Processor, DSPs), embedded devices, etc.
The computer device may be a desktop computer, a notebook computer, a palm computer, a cloud server, or the like. The computer device can perform man-machine interaction with a user through a keyboard, a mouse, a remote controller, a touch pad or voice control equipment and the like.
The memory 310 includes at least one type of readable storage medium including non-volatile memory (non-volatile memory) or volatile memory, such as flash memory (flash memory), hard disk, multimedia card, card memory (e.g., SD or DX memory, etc.), random access memory (random access memory, RAM), read-only memory (ROM), erasable programmable read-only memory (erasable programmable read-only memory, EPROM), electrically erasable programmable read-only memory (electrically erasable programmable read-only memory, EEPROM), programmable read-only memory (programmable read-only memory, PROM), magnetic memory, RAM, optical disk, etc., which may include static or dynamic. In some embodiments, memory 310 may be an internal storage unit of a computer device, such as a hard disk or memory of the computer device. In other embodiments, the memory 310 may also be an external storage device of a computer device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, or a Flash Card (Flash Card) provided on the computer device. Of course, memory 310 may also include both internal storage units for computer devices and external storage devices. In this embodiment, the memory 310 is typically used to store an operating system installed on a computer device and various types of application software, such as program codes of the above-described methods. In addition, the memory 310 may also be used to temporarily store various types of data that have been output or are to be output.
Processor 320 is typically used to perform the overall operations of the computer device. In this embodiment, the memory 310 is used for storing program codes or instructions, the program codes include computer operation instructions, and the processor 320 is used for executing the program codes or instructions stored in the memory 310 or processing data, such as the program codes for executing the above-mentioned method.
Herein, the bus may be an industry standard architecture (Industry Standard Architecture, ISA) bus, a peripheral component interconnect (Peripheral Component Interconnect, PCI) bus, or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, among others. The bus system may be classified as an address bus, a data bus, a control bus, etc. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting thereof; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the corresponding technical solutions.
Claims (10)
1. An intelligent tour method based on big data sharing is characterized by comprising the following steps:
receiving a travel planning request sent by a first user through a user side, wherein the travel planning request comprises the following steps: travel duration data and travel consumption data describing payment planning data for travel trips;
responding to the travel planning request, and generating a travel planning video based on the travel duration data and the travel consumption data of the first user, wherein the travel planning video comprises multiple frames of images, each frame of image corresponds to one travel browsing information, and the travel browsing information comprises a travel scenic spot area, a travel rest area and a travel food area;
the travel planning video is sent to the user side, so that the first user browses the travel planning video through the user side;
obtaining user browsing data of the first user in the process of browsing the travel planning video, wherein the user browsing data are sent by the user side and comprise: browsing time length of each frame of image;
determining travel point of interest information of the first user based on the user browsing data, wherein the travel point of interest information comprises: intent scenic spot data;
Determining travel time of the first user based on the travel point of interest information;
generating travel planning information matched with the first user based on the travel interest point information, the travel time, the travel duration data and the travel consumption data of the first user;
acquiring a second user with travel associated information from a user database;
based on the travel planning information corresponding to the second user, adjusting the travel planning information corresponding to the first user, wherein the travel planning information corresponding to the second user comprises: historical interest point information, wherein the adjusting the travel planning information corresponding to the first user based on the travel planning information corresponding to the second user includes: adding the historical interest point information into the travel planning information corresponding to the first user;
and sending the adjusted travel planning information of the first user to the user side.
2. The method of claim 1, wherein the generating a travel planning video based on the travel duration data and the travel consumption data of the first user comprises:
Selecting and combining all scenic spot data in a scenic spot database based on the travel duration data and the travel consumption data of the first user to obtain an initial travel video, selecting and combining all scenic spot data in the scenic spot database based on the travel duration data and the travel consumption data of the first user to obtain the initial travel video, including: randomly combining a plurality of scenic spot data in each scenic spot data included in a scenic spot database to obtain a plurality of groups of scenic spot combination information, selecting one scenic spot combination information corresponding to the scenic spot browsing total duration being lower than the duration of the tourist duration data and the scenic spot consumption total amount being lower than the amount of the tourist consumption data from the plurality of groups of scenic spot combination information, and generating the initial travel video based on the one scenic spot combination information;
acquiring historical tourist attraction data and historical tourist consumption data of the first user, wherein the historical tourist consumption data is used for describing single attraction payment data or single food payment data of the first user in a historical travel process;
based on the historical tourist attraction data of the first user, deleting similar sceneries in the initial travel video, wherein the similar sceneries are used for describing sceneries with historical cultural similarity with sceneries included in the historical tourist attraction data;
Determining travel attractions and/or travel cuisines that do not meet the first user consumption demand based on the historical travel consumption data of the first user, the determining travel attractions and/or travel cuisines that do not meet the first user consumption demand based on the historical travel consumption data of the first user, comprising: if the amount corresponding to the single scenic spot payment data is smaller than the charging amount of one travel scenic spot, and/or the amount of the single food payment data is smaller than the charging amount of one travel food area, determining that the one travel scenic spot is a travel scenic spot which does not meet the consumption requirement of the first user, and/or the one travel food area is a travel food area which does not meet the consumption requirement of the first user;
and deleting the travel scenic spot and/or the travel food area in the initial travel video to obtain the travel planning video.
3. The method of claim 1, wherein the generating travel planning information matching the first user based on the travel point of interest information, the travel time, the travel duration data, and the travel consumption data of the first user comprises:
Acquiring historical travel consumption data of the first user, wherein the historical travel consumption data is used for describing riding payment data of the first user in a historical travel process;
determining travel planning information corresponding to the first user based on the historical travel consumption data, the travel time, the travel interest point information and the travel duration data of the first user, wherein the travel planning information is used for describing a vehicle identifier and a vehicle transfer time when the first user goes out;
and planning the travel browsing sequence of each intention scenic spot in the travel interest point information based on the travel planning information to obtain the travel planning information matched with the first user.
4. The method of claim 1, wherein the determining travel point of interest information for the first user based on the user browsing data comprises:
extracting interest scenic spots of the first user based on the user browsing data;
matching associated scenic spots corresponding to the interesting scenic spots from other travel planning videos, wherein the associated scenic spots are in position association relation or scenic spot association relation with the interesting scenic spots;
The travel point of interest information for the first user is determined based on the point of interest and the associated point of interest.
5. The method of claim 1, wherein the obtaining the user browsing data of the first user transmitted by the user terminal during browsing the travel planning video includes:
receiving the stay time of the first user in the display page corresponding to each frame of image and the triggering operation in the display page corresponding to each frame of image, wherein the display page corresponding to each frame of image can switch the display content in the image based on the triggering operation;
and determining the browsing time length of the first user for browsing each frame of image based on the stay time length of the first user in the display page corresponding to each frame of image and the triggering operation in the display page corresponding to each frame of image.
6. The method of claim 1, wherein the determining the travel time of the first user based on the travel point of interest information comprises:
acquiring the current optimal browsing time period and the current travel adaptive travel time of each intention scenic spot in the travel interest point information, wherein the current travel adaptive travel time is the time suitable for traveling in the current seasonal environment;
Matching the current optimal browsing time period of each intention scenic spot, the travel duration data and the current travel adaptation outgoing time, and removing the unmatched scenic spots from the travel interest point information;
and planning the travel time of the first user based on the current optimal browsing time period of the rest intention scenic spot.
7. The method of claim 1, further comprising, after the sending the adjusted travel planning information for the first user to the user side:
sending a planning evaluation request of the travel planning information to the user;
the method comprises the steps of receiving planning evaluation data sent by a first user through a user side, wherein the planning evaluation data comprises the following steps: time evaluation data and scenic spot evaluation data;
generating planning information update data based on the time evaluation data and the scenic spot evaluation data;
updating the travel planning information based on the planning information update data;
and sending the updated travel planning information and the updated planning information update data to the user side.
8. An intelligent travel system based on big data sharing, comprising:
The receiving module is used for receiving a travel planning request sent by a first user through a user side, wherein the travel planning request comprises the following components: travel duration data and travel consumption data describing payment planning data for travel trips;
the first generation module is used for responding to the travel planning request, generating a travel planning video based on the travel duration data and the travel consumption data of the first user, wherein the travel planning video comprises multiple frames of images, each frame of image corresponds to one travel browsing information, and the travel browsing information comprises a travel scenic spot area, a travel rest area and a travel food area;
the first sending module is used for sending the travel planning video to the user side so that the first user can browse the travel planning video through the user side;
the first obtaining module is configured to obtain user browsing data of the first user in the process of browsing the travel planning video, where the user browsing data is sent by the user side and includes: browsing time length of each frame of image;
the determining module is used for determining travel interest point information of the first user based on the user browsing data, wherein the travel interest point information comprises the following components: intent scenic spot data; determining travel time of the first user based on the travel point of interest information;
The second generation module is used for generating travel planning information matched with the first user based on the travel interest point information, the travel time, the travel duration data and the travel consumption data of the first user;
the second acquisition module is used for acquiring a second user with travel association information with the first user from a user database;
the adjustment module is configured to adjust the travel planning information corresponding to the first user based on the travel planning information corresponding to the second user, where the travel planning information corresponding to the second user includes: historical interest point information, the adjustment module is specifically configured to: adding the historical interest point information into the travel planning information corresponding to the first user;
and the second sending module is used for sending the adjusted travel planning information of the first user to the user side.
9. The system of claim 8, wherein the first generation module comprises:
the combination unit is used for selecting and combining all scenic spot data in a scenic spot database based on the travel duration data and the travel consumption data of the first user so as to obtain an initial travel video, and is specifically used for: randomly combining a plurality of scenic spot data in each scenic spot data included in a scenic spot database to obtain a plurality of groups of scenic spot combination information, selecting one scenic spot combination information corresponding to the scenic spot browsing total duration being lower than the duration of the tourist duration data and the scenic spot consumption total amount being lower than the amount of the tourist consumption data from the plurality of groups of scenic spot combination information, and generating the initial travel video based on the one scenic spot combination information;
The acquisition unit is used for acquiring historical tourist attraction data and historical tourist consumption data of the first user, wherein the historical tourist consumption data is used for describing single attraction payment data or single food payment data of the first user in a historical travel process;
a first deleting unit, configured to perform a deleting operation on a similar scenic spot in the initial travel video based on the historical tourist attraction data of the first user, where the similar scenic spot is used to describe a scenic spot having a historical cultural similarity with a scenic spot included in the historical tourist attraction data;
a determining unit, configured to determine, based on the historical travel consumption data of the first user, a travel scenic spot and/or a travel food area that does not meet the consumption requirement of the first user, where the determining unit is specifically configured to: if the amount corresponding to the single scenic spot payment data is smaller than the charging amount of one travel scenic spot, and/or the amount of the single food payment data is smaller than the charging amount of one travel food area, determining that the one travel scenic spot is a travel scenic spot which does not meet the consumption requirement of the first user, and/or the one travel food area is a travel food area which does not meet the consumption requirement of the first user;
And the second deleting unit is used for deleting the travel scenic spot and/or the travel food area in the initial travel video to obtain the travel planning video.
10. The system according to claim 8, wherein the second generating module is specifically configured to:
acquiring historical travel consumption data of the first user, wherein the historical travel consumption data is used for describing riding payment data of the first user in a historical travel process;
determining travel planning information corresponding to the first user based on the historical travel consumption data, the travel time, the travel interest point information and the travel duration data of the first user, wherein the travel planning information is used for describing a vehicle identifier and a vehicle transfer time when the first user goes out;
and planning the travel browsing sequence of each intention scenic spot in the travel interest point information based on the travel planning information to obtain the travel planning information matched with the first user.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311787720.2A CN117495619B (en) | 2023-12-25 | 2023-12-25 | Intelligent travel method and system based on big data sharing |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311787720.2A CN117495619B (en) | 2023-12-25 | 2023-12-25 | Intelligent travel method and system based on big data sharing |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN117495619A true CN117495619A (en) | 2024-02-02 |
| CN117495619B CN117495619B (en) | 2024-04-05 |
Family
ID=89683247
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311787720.2A Active CN117495619B (en) | 2023-12-25 | 2023-12-25 | Intelligent travel method and system based on big data sharing |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117495619B (en) |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106408097A (en) * | 2016-08-31 | 2017-02-15 | 浪潮软件集团有限公司 | Travel journey planning system based on genetic algorithm |
| CN106570799A (en) * | 2016-10-20 | 2017-04-19 | 安徽大智睿科技技术有限公司 | Intelligent travel method for intelligent audio and video guide based on two-dimensional code |
| KR101886966B1 (en) * | 2017-04-18 | 2018-08-08 | 인천대학교 산학협력단 | Method for providing customized travel plan and server implementing the same |
| CN109919437A (en) * | 2019-01-29 | 2019-06-21 | 特斯联（北京）科技有限公司 | A kind of smart travel target matching method and system based on big data |
| CN109977248A (en) * | 2019-04-03 | 2019-07-05 | 海南世嘉亮科技有限公司 | A kind of mixed video file generated and stroke recommended method, device |
| CN110929180A (en) * | 2019-11-20 | 2020-03-27 | 国云科技股份有限公司 | Implementation method for intelligently recommending tourist attractions |
| CN111143679A (en) * | 2019-12-27 | 2020-05-12 | 肇庆学院 | Digital intelligent tourism control system and method based on big data |
| CN113784108A (en) * | 2021-08-25 | 2021-12-10 | 盐城香农智能科技有限公司 | VR (virtual reality) tour and sightseeing method and system based on 5G transmission technology |
| KR20210157073A (en) * | 2020-06-19 | 2021-12-28 | 주식회사 트래블리맵 | System and method for recommending travel destination combination based on hybrid filtering |
| CN113886699A (en) * | 2021-10-12 | 2022-01-04 | 北京交通大学 | Travel and trip integrated planning method considering travel demands and preferences of user |
| CN113935547A (en) * | 2021-11-11 | 2022-01-14 | 扆林海 | Optimal-utility customized scenic spot route planning system |
| DE202023100616U1 (en) * | 2023-02-09 | 2023-02-20 | Amer Al Qassem | System for optimizing tourism planning |
-
2023
- 2023-12-25 CN CN202311787720.2A patent/CN117495619B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN106408097A (en) * | 2016-08-31 | 2017-02-15 | 浪潮软件集团有限公司 | Travel journey planning system based on genetic algorithm |
| CN106570799A (en) * | 2016-10-20 | 2017-04-19 | 安徽大智睿科技技术有限公司 | Intelligent travel method for intelligent audio and video guide based on two-dimensional code |
| KR101886966B1 (en) * | 2017-04-18 | 2018-08-08 | 인천대학교 산학협력단 | Method for providing customized travel plan and server implementing the same |
| CN109919437A (en) * | 2019-01-29 | 2019-06-21 | 特斯联（北京）科技有限公司 | A kind of smart travel target matching method and system based on big data |
| CN109977248A (en) * | 2019-04-03 | 2019-07-05 | 海南世嘉亮科技有限公司 | A kind of mixed video file generated and stroke recommended method, device |
| CN110929180A (en) * | 2019-11-20 | 2020-03-27 | 国云科技股份有限公司 | Implementation method for intelligently recommending tourist attractions |
| CN111143679A (en) * | 2019-12-27 | 2020-05-12 | 肇庆学院 | Digital intelligent tourism control system and method based on big data |
| KR20210157073A (en) * | 2020-06-19 | 2021-12-28 | 주식회사 트래블리맵 | System and method for recommending travel destination combination based on hybrid filtering |
| CN113784108A (en) * | 2021-08-25 | 2021-12-10 | 盐城香农智能科技有限公司 | VR (virtual reality) tour and sightseeing method and system based on 5G transmission technology |
| CN113886699A (en) * | 2021-10-12 | 2022-01-04 | 北京交通大学 | Travel and trip integrated planning method considering travel demands and preferences of user |
| CN113935547A (en) * | 2021-11-11 | 2022-01-14 | 扆林海 | Optimal-utility customized scenic spot route planning system |
| DE202023100616U1 (en) * | 2023-02-09 | 2023-02-20 | Amer Al Qassem | System for optimizing tourism planning |
Non-Patent Citations (2)
| Title |
|---|
| HUIMIN HU ET AL.: "Smart tourism products and services design based on user experience under the background of big data", 《SOFT COMPUTING》, 29 June 2023 (2023-06-29), pages 12711 - 12724 * |
| 张立镜;郑坤;: "大数据在现代旅游管理工作中的应用", 旅游纵览(下半月), no. 02, 23 February 2020 (2020-02-23) * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN117495619B (en) | 2024-04-05 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN110378732B (en) | Information display method, information association method, device, equipment and storage medium | |
| US20170308251A1 (en) | User Interface with Media Wheel Facilitating Viewing of Media Objects | |
| CN109241242B (en) | Live broadcast room topic recommendation method and device, server and storage medium | |
| CN110096645A (en) | Information recommendation method, device, equipment and medium | |
| CN103635903A (en) | Context-based ranking of search results | |
| TW201723896A (en) | Search assistant system and method | |
| CN104991924A (en) | Method and apparatus for determining address of new supply point | |
| CN104115180A (en) | Information processing device, information processing method, and program | |
| US10061806B2 (en) | Presenting previously selected search results | |
| JP4922814B2 (en) | Information distribution method | |
| CN110990700A (en) | Comment information display method, device, client, server and system | |
| CN112241489A (en) | Information pushing method and device, readable storage medium and computer equipment | |
| US10671943B2 (en) | Reservation management server and method that generate a new plan to be recommended to a facility | |
| WO2021164131A1 (en) | Map display method and system, computer device and storage medium | |
| CN113766016B (en) | Information pushing method and server | |
| JP7426176B2 (en) | Information processing system, information processing method, information processing program, and server | |
| CN112650946B (en) | Product information recommendation method, device, system and storage medium | |
| CN117495619B (en) | Intelligent travel method and system based on big data sharing | |
| CN104598585A (en) | Information search method and information search device | |
| CN113138677A (en) | Method and device for determining candidate words of input method, electronic equipment and storage medium | |
| JP6553829B1 (en) | Information processing apparatus, information processing method, program, and storage medium | |
| CN114428919A (en) | Method, device, equipment and medium for searching places | |
| CN111641690B (en) | Session message processing method and device and electronic equipment | |
| KR102120207B1 (en) | Mehod and system for providing reward service for inducing hashtag upload | |
| TWI451277B (en) | Search tags visualization system and method therefore |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |