CN113505315B - Multi-user travel strategy making method and device and computer equipment - Google Patents

Multi-user travel strategy making method and device and computer equipment Download PDF

Info

Publication number
CN113505315B
CN113505315B CN202111053649.6A CN202111053649A CN113505315B CN 113505315 B CN113505315 B CN 113505315B CN 202111053649 A CN202111053649 A CN 202111053649A CN 113505315 B CN113505315 B CN 113505315B
Authority
CN
China
Prior art keywords
user
spot
scenic
target
travel
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.)
Active
Application number
CN202111053649.6A
Other languages
Chinese (zh)
Other versions
CN113505315A (en
Inventor
张卫平
张浩宇
米小武
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Global Digital Group Co Ltd
Original Assignee
Global Digital Group Co Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Global Digital Group Co Ltd filed Critical Global Digital Group Co Ltd
Priority to CN202111053649.6A priority Critical patent/CN113505315B/en
Publication of CN113505315A publication Critical patent/CN113505315A/en
Application granted granted Critical
Publication of CN113505315B publication Critical patent/CN113505315B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • 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
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F18/00—Pattern recognition
    • G06F18/20—Analysing
    • G06F18/22—Matching criteria, e.g. proximity measures
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F40/00—Handling natural language data
    • G06F40/20—Natural language analysis
    • G06F40/279—Recognition of textual entities
    • 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
    • G06Q30/00—Commerce
    • G06Q30/02—Marketing; Price estimation or determination; Fundraising
    • G06Q30/0282—Rating or review of business operators or products
    • 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 relates to the technical field of travel service, and discloses a multi-user travel strategy making method, a multi-user travel strategy making device and computer equipment, wherein the method comprises the following steps: obtaining the rank of the destination and the scenery spot; calling historical travel scenic spot data of all users; matching the historical travel sight data with all sights of the destination; collecting the target scenery with the scenic spots ranked in the first three of all the scenic spots of the destination; judging whether a user in the travel group changes or not to delete; if so, whether the weighted value is greater than a set value; if the position data is larger than the set value, deleting and acquiring the position data; adding the deleted sights to the user portrait and adding a negative tag; and locking the target scenic spot set, and formulating the travel strategy according to the position data. The invention provides a multi-user travel strategy making method, a multi-user travel strategy making device and computer equipment.

Description

Multi-user travel strategy making method and device and computer equipment
Technical Field
The invention relates to the technical field of travel services, in particular to a multi-user travel strategy making method, a multi-user travel strategy making device and computer equipment.
Background
At present, tourism has become the important mode of people's amusement and recreation, and the mode of tourism also divide into with group's trip and free line, can make the user save worry laborsaving with group's trip, but can't make the user go to the scenic spot that oneself is satisfied with all the time, also can make the user can not be in the same direction as long as the tourism and the scheduling simultaneously. Therefore, people can choose a free-running mode to travel, free-running can reasonably arrange own time without limitation of departure time and scenic spot time of a travel group, but users are unfamiliar with destinations and consume a great amount of time and energy in journey making. Therefore, a large number of travel strategies are gathered in websites and applications related to travel in the market, and users can search the related strategies before traveling, but the searched strategies are also possibly not suitable for the users, and particularly under the condition that multiple users accompany traveling, the searched strategies cannot meet the requirements of each user, and the users still need to set the related strategies according to the conditions, so that the time and the labor are wasted.
Disclosure of Invention
The invention provides a multi-user travel strategy making method, a multi-user travel strategy making device and computer equipment.
The invention provides a multi-user travel strategy making method, which comprises the following steps:
obtaining a destination selected by any user in a travel group, and obtaining all scenic spots of the destination and the ranking of the scenic spots;
calling user figures of all users in the travel group from a travel picture database to obtain historical travel scenic spot data of all users;
matching historical travel scenic spot data with positive labels in the user portrait with all scenic spots of the destination to obtain a plurality of target scenic spots;
collecting a plurality of target scenic spots and scenic spots ranked in the top three of all the scenic spots of the destination to obtain a target scenic spot set;
judging whether a change user deletes the scenic spots in the target scenic spot set or not in the travel group;
if the scenic spots in the target scenic spot set are deleted by the change user in the travel group, calculating the weight value of the deleted target scenic spot, and judging whether the weight value of the deleted target scenic spot is larger than a set value or not;
if the weight value of the deleted target scenic spot is larger than the set value, refusing to change the deletion of the user and acquiring the position data of the deleted target scenic spot, matching with the rest places in the preset range of the deleted target scenic spot, and defining the rest places as the current deleted scenic spot of the change user;
adding the deleted sight to the user representation of the modifying user and adding a negative tag to the sight in the user representation of the modifying user;
and locking the target sight spot set, and formulating the travel strategy of the destination according to the position data of all the target sight spots in the target sight spot set.
Further, before the step of retrieving user figures of all users in the travel group from the travel picture database to obtain historical travel spot data of all users, the method further comprises:
determining whether all users in the travel group have a user representation;
if yes, executing the step of obtaining user figures of all users in the travel group to obtain historical travel scenic spot data of all users;
if not, defining the user without the user image as a first user, and acquiring the chat content of the first user; the chat content is the chat content of the first user and other users in the travel group;
matching the chat content with all scenic spots of the destination to obtain a plurality of first scenic spots and tags of the first scenic spots;
associating the plurality of first scenes with user information of a first user to form a user portrait of the first user;
adding the user representation of the first user to the travel representation database.
Further, the step of matching the chat content with all the attractions of the destination to obtain a plurality of first attractions and the tags of the first attractions comprises:
extracting one scenery spot from all scenery spots of the destination as a scenery spot to be confirmed, wherein when the scenery spot to be confirmed appears in the chat content, the scenery spot to be confirmed is a first scenery spot;
searching for the sentence with the first sight spot in the chat content to obtain a target sentence;
performing word segmentation on the target sentence to obtain a first emotion keyword in the target sentence;
screening out the voices of the scenic spots of the destination in the chat content to obtain target voices;
performing character recognition and word segmentation on the target voice to obtain a second emotion keyword in the target voice;
performing tone recognition on the target voice to obtain tone information corresponding to the second emotion keyword, and adding the tone information to the second emotion keyword;
inputting the first emotion keyword and the second emotion keyword into a preset neural network model to obtain the emotion state of the user;
and adding the emotional state of the user as a label of the first sight spot into the first sight spot.
Further, the step of matching the historical travel sight data, which is labeled as an active label in the user portrait, with all sights of the destination to obtain a plurality of target sights includes:
acquiring all scenic spots of which the labels are active labels in the user portrait as associated scenic spots;
crawling attributes of the associated sight and all sights of the destination from a travel website;
and extracting the scenic spots with the associated scenic spot attributes from all the scenic spots of the destination to be used as target scenic spots.
Further, the step of formulating a travel strategy for the destination according to the location data of all target sights in the set of target sights includes:
acquiring the positions of all target scenic spots in the target scenic spot set and the tour duration;
collecting target scenic spots located in the same county-level administrative district to obtain a plurality of combinations;
acquiring the traffic time between every two scenic spots in each combination; wherein the traffic duration is a public traffic duration;
taking any one of two target scenic spots with the closest distance as a starting scenic spot, setting the target scenic spot with the closest distance to the starting scenic spot as a second scenic spot, setting the target scenic spot with the closest distance to the second scenic spot as a third scenic spot, and arranging by analogy until the arrangement of all the target scenic spots in one combination is completed to form a tour list;
according to the arrangement sequence in the tour list, the scenic spots with the tour duration and the traffic duration not exceeding the set duration are classified as one-day scenic spots, and when a plurality of one-day scenic spots exist, the plurality of one-day scenic spots are arranged according to the sequence of the tour list;
after finishing the arrangement of the scenic spots of each combination, arranging a plurality of combinations to obtain a travel route;
and matching the hotel according to the travel route and a set rule to obtain the travel strategy of the destination.
Further, the step of matching the hotel according to the travel route and the set rule comprises the following steps:
obtaining a sight spot of a first day in a travel route;
matching the hotel in the set range of the first scenic spot in the scenic spots of the first day as a hotel for arriving at a residence, and matching the hotel in the set range of the last scenic spot as a hotel of the first day;
matching the hotel in the set range of the last scenic spot in the scenic spots on the last day as a return-trip check-in hotel;
sequentially judging whether the distance between the hotel on the previous day and the last scenic spot in the scenic spots on the current day exceeds a set distance from the second day;
if not, taking the hotel on the previous day as the hotel on the current day;
if yes, matching the hotel in the set range of the last scenic spot in the scenic spots of the current day with the hotel of the current day;
when the hotels in two adjacent days are different, matching a plurality of baggage storage service points between the position of the hotel in the previous day and the position of the first scenic spot in the next day;
and setting the baggage registration service point closest to the hotel position on the next day as a final registration service point.
Further, after the step of locking the target sight point set and formulating the travel strategy of the destination according to the position data of all the target sight points in the target sight point set, the method further comprises the following steps:
after the travel is finished, an evaluation request is sent to each user in the travel group so as to evaluate the scenic spots contained in the travel strategy;
obtaining the evaluation of any scenic spot in the travel strategy by any user;
judging whether the user portrait of the current user has the scenery spot or not;
if the user portrait of the current user has the scenery spot, updating the user portrait of the current user according to the evaluation of the current scenery spot;
if the user image of the current user does not have the scenery spot, judging whether the evaluation of the current scenery spot is a positive evaluation;
if the evaluation of the current scenery spot is positive evaluation, adding the current scenery spot in the portrait of the current user, setting the label of the current scenery spot as a positive label, and increasing the weight value of the scenery spot setting value associated with the current scenery spot;
and if the evaluation of the current scenery spot is negative evaluation, adding the current scenery spot in the portrait of the current user, setting the label of the current scenery spot as a negative label, and simultaneously reducing the weight value of the scenery spot setting value associated with the current scenery spot.
The invention also provides a multi-user travel strategy making device, which comprises:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring a destination selected by any user in a travel group and acquiring all scenic spots of the destination and ranks of the scenic spots;
the calling module is used for calling user figures of all users in the travel group from a travel picture database to obtain historical travel scenic spot data of all the users;
the matching module is used for matching the historical travel scenic spot data with positive labels in the user portrait with all scenic spots of the destination to obtain a plurality of target scenic spots;
the collecting module is used for collecting a plurality of target scenic spots and scenic spots ranked in the top three of all the scenic spots of the destination to obtain a target scenic spot set;
the judging module is used for judging whether a change user deletes the scenic spots in the target scenic spot set in the travel group;
the calculation module is used for calculating the weight value of the deleted target scenic spot when the scenic spot in the target scenic spot set is deleted by the change user in the travel group, and judging whether the weight value of the deleted target scenic spot is larger than a set value or not;
the rejection module is used for rejecting the change user to delete and acquiring the position data of the deleted target scenic spot when the weight value of the deleted target scenic spot is larger than a set value, matching the rest places in the preset range of the deleted target scenic spot, and defining the rest places as the current deleted scenic spot of the change user;
the adding module is used for adding the deleted scenic spots to the user portrait of the modifying user and adding negative labels to the scenic spots in the user portrait of the modifying user;
and the locking module is used for locking the target scenery spot set and formulating the travel strategy of the destination according to the position data of all the target scenery spots in the target scenery spot set.
The invention also provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method when executing the computer program.
The invention also provides a computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the above-mentioned method.
The invention has the beneficial effects that: by obtaining a destination selected by any user in a travel group, when the user in the travel group has a user portrait, scenic spots which the user may be interested in are automatically matched, when the user in the travel group does not have the user portrait, scenic spots which the user may want to go to are matched through chat contents of the user and other users in the travel group, a target scenic spot set is formed by combining the three places before the destination scenic spot ranking, then travel strategies of the destination are formulated according to position data of the target scenic spot set, after travel is finished, evaluations of all scenic spots in the travel strategies by the user in the travel group are obtained, and the user portrait is updated according to the evaluations, so that the subsequent processes of formulation of the strategies by using the portrait; the user does not need to search for the Internet and make a journey, which wastes time and labor, the time of the user is greatly saved, and the trip experience of the user is improved.
Drawings
Fig. 1 is a schematic flow chart of a method according to an embodiment of the present invention.
Fig. 2 is a schematic structural diagram of an apparatus according to an embodiment of the present invention.
Fig. 3 is a schematic diagram of an internal structure of a computer device according to an embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As shown in FIG. 1, the present invention provides a multi-user travel strategy making method, comprising:
s1, obtaining a destination selected by any user in the travel group, and obtaining all scenic spots of the destination and the ranking of the scenic spots;
s2, calling user figures of all users in the travel group from a travel picture database to obtain historical travel scenic spot data of all users;
s3, matching historical travel sight data with positive labels in the user portrait with all sights of the destination to obtain a plurality of target sights;
s4, collecting a plurality of target scenic spots and scenic spots ranked in the top three of all the scenic spots of the destination to obtain a target scenic spot set;
s5, judging whether a change user deletes the scenic spots in the target scenic spot set or not in the travel group;
s6, if the scenic spots in the target scenic spot set are deleted by the change user in the travel group, calculating the weight value of the deleted target scenic spot, and judging whether the weight value of the deleted target scenic spot is larger than a set value or not;
s7, if the weight value of the deleted target sight spot is larger than the set value, refusing to change the deletion of the user and acquiring the position data of the deleted target sight spot, matching the rest places in the preset range of the deleted target sight spot, and defining the rest places as the current deleted sight spot of the change user;
s8, adding the deleted scenery spot to the user image of the modifying user and adding a negative label to the scenery spot in the user image of the modifying user;
s9, locking the target sight spot set, and making the travel strategy of the destination according to the position data of all the target sight spots in the target sight spot set.
As described in the above step S1, a travel group is created in advance, and more than two users are present in a travel group, and the users in the travel group are users traveling along with the destination. After the users in the travel group have determined a destination, any user in the travel group may select the destination, which is the destination of the travel group. After the destination selected by the user is obtained, crawling all scenic spots of the destination and ranks among the scenic spots from the tourist websites, wherein the ranks among the scenic spots are different in each tourist website, the ranks of all the tourist websites can be comprehensively ranked, namely ranking is performed according to the number of times of ranking, for example, 5 tourist websites are used in total, the scenic spot 1 is ranked first in 4 tourist websites, and finally the rank of the scenic spot 1 is taken as the first name, and the like; and one tourist website can be selected, and the ranking of the tourist website can be directly applied as the ranking of destination scenic spots.
As described in step S2, a database of travel pictures is created in advance, where a user profile of each user who has finished traveling is stored in the database, where the user profile is composed of user information and scenic spots, the user information includes, but is not limited to, a user name, real name information, a telephone, an address, etc., the scenic spots may be scenic spots already visited by the user or scenic spots about to visit by the user, each scenic spot has a label, the category of the label is divided into an active label and a passive label, and the active label and the passive label may be represented by a series of words with reverse meanings, such as like/dislike, positive/negative, black/white, etc. After all scenic spots of the destination of travel of the travel group are obtained, if a user in the travel group has a user portrait, the scenic spots in the user portrait are scenic spots already visited (namely historical travel scenic spot data), and the destination scenic spots with the same attributes among the scenic spots are matched according to the scenic spots already visited; if the user in the travel group does not have a user representation, the user representation is created, at the moment, the scenic spots in the user representation are scenic spots of an upcoming destination, and the scenic spots can be obtained through chat contents of the user or can be obtained through active selection of the user.
As described in step S3, the historical travel scene data labeled with positive labels in the user portrait is the favorite and satisfactory scene of the user, which indicates that the user does not have a repulsive mind, and the sequentially matched scenes of the destination can be accepted by the user; during matching, historical travel data in the user portrait of each user in the travel group are matched, if two users are matched with one scenic spot at the same time, the two users are combined, the scenic spot is displayed finally, but the situation that the two users are matched with the scenic spot can be marked.
As described in step S4, the sights matched by the user portrait of the travel group include sights that may be of interest to the user, and since the sight of the top three of the destination sights is the most representative sight of travel, which is generally called as a must-go sight, one of the sights is added to the target sight set, if the sight matched by the user portrait already includes or partially includes the sight of the top three, the sight already included does not need to be added again, and if the matched sight does not include the sight of the top three, the sight of the top three of the destination is added to the target sight set.
As described in the above steps S5-S6, when there is a user in the travel group who is not satisfied with the sights in the target sight collection, the user may perform a deletion operation, and the user performing the deletion operation is a change user; because the scenic spots in the target scenic spot set are scenic spots about to travel by the travel group, the change user cannot delete the scenic spots at will, and therefore when the change user performs the deletion operation, the weight value of the deleted target scenic spot is calculated, and the calculation mode of the weight value is as follows: the weight value of the sight spot = the number of times the sight spot is selected or matched ÷ the number of users in the travel group; when the user has the user portrait, the scenic spot is matched, the times are +1, and when the user does not have the user portrait, the user selects the scenic spot, the times are + 1; wherein, the sights of the top three in the target set can not be deleted.
As described in step S7, when the weight value of the deleted scenery spot is greater than the set value, such as 50%, 60%, etc., it indicates that most users in the travel group are willing to go to the scenery spot, and the scenery spot cannot be deleted, so the change user cannot delete the scenery spot, and at the same time, the position data of the scenery spot is obtained, the rest places in the preset range of the scenery spot (set according to specific needs, but not limited thereto) are matched, and the rest places are defined as the current deleted scenery spots of the change user, so that when planning the route, the scenery spots of each user in the travel group are kept consistent, and confusion is avoided.
As described above in step S8, because the delete operation of the modifying user indicates that the modifying user may be dissatisfied or disliked with the deleted attraction, indicating a negative status of the user, the attraction may be added to the user representation and a negative label may be added to the attraction so that when a match is made with a user representation using the modifying user subsequently, no attraction with the same attributes of the attraction is matched.
As described in step S9, after the destination scenic spot is determined, the target scenic spot set is locked, the scenic spots in the target scenic spot set are the scenic spots that the travel team finally determines to go to, the location data of all the target scenic spots in the scenic spot set is followed, the distance between the target scenic spots, the traffic duration and the visit duration are determined, the hotel is determined according to the distance between the scenic spots, the traffic duration and the visit duration, and the formulation of the travel strategy of the destination is finally completed.
In one embodiment, before the step of retrieving user images of all users in the travel group from the travel image database to obtain historical scenic spot data of all users, that is, before the step S2, the method further includes:
s021, judging whether all users in the travel group have user images or not;
s022, if yes, executing a step of obtaining user portraits of all users in the travel group to obtain historical travel scenic spot data of all users;
s023, if not, defining the user without the user picture as a first user and acquiring the chat content of the first user; the chat content is the chat content of the first user and other users in the travel group;
s024, matching the chat content with all scenic spots of the destination to obtain a plurality of first scenic spots and labels of the first scenic spots;
s025, associating the plurality of first scenes with user information of a first user to form a user portrait of the first user;
s026, adding the user portrait of the first user to the travel portrait database.
As described in the above steps S021 to S026, before retrieving the user portrait from the travel picture database, it is also necessary to determine whether the user has the user portrait, and the user portrait can be retrieved when the user has the user portrait, so that the matching is performed using the historical travel data. When the user does not have the user portrait, the user portrait needs to be created, at this time, the user is defined as a first user, user information of the first user is obtained, and then a plurality of first scenic spots in which the user is interested are obtained through chat contents of the first user and other users in a travel group, wherein the chat contents can be local chat contents or chat contents accessed into social software such as WeChat and QQ; judging whether the emotion of the user to the current first scenery spot is positive or negative through the chat content, when the user attitude is positive, marking a positive label on the current first scenery spot, when the emotion of the user to the current first scenery spot is negative, marking a negative label on the current first scenery spot, associating a plurality of first scenery spots with labels with user information to form a user portrait, and finally storing the user portrait into a travel portrait database for subsequent matching use.
In one embodiment, the step S024 of matching the chat content with all sights of the destination to obtain a plurality of first sights and tags of the first sights includes:
s0241, extracting one scenery spot from all scenery spots of the destination as a scenery spot to be confirmed, wherein when the scenery spot to be confirmed appears in the chat content, the scenery spot to be confirmed is a first scenery spot;
s0242, searching sentences of the first scenic spot in the chat content to obtain target sentences;
s0243, performing word segmentation on the target sentence to obtain a first emotion keyword in the target sentence;
s0244, screening out voices of scenic spots of the destination in the chat content to obtain target voices;
s0245, performing character recognition and word segmentation on the target voice to obtain a second emotion keyword in the target voice;
s0246, performing tone recognition on the target voice to obtain tone information corresponding to the second emotion keyword, and adding the tone information into the second emotion keyword;
s0247, inputting the first emotion keywords and the second emotion keywords into a preset neural network model to obtain the emotion state of the user;
s0248, adding the emotional state of the user into the first attraction as a label of the first attraction.
As described in the foregoing steps S0241-S0248, the chat content is searched in the chat content, and is a chat content between users of the travel team, which may be a chat content of private chat or a chat content of group chat, and as long as a destination sight spot appears in the chat content, the sight spot is a first sight spot, so as to obtain a destination sight spot that may be interested by the user from the chat content. Meanwhile, a sentence with a first sight spot is searched in the chat content to obtain a target sentence, the target sentence is a text sentence, the target sentence is segmented, emotional words in the segmentation are extracted, and then a first emotional keyword in the target sentence is obtained; searching the voice of the first scenic spot in the chat content to obtain a target voice, firstly carrying out character recognition on the target voice to obtain a target character, then carrying out word segmentation on the target character, extracting emotional words from the segmented words, and further obtaining a second emotional keyword from the target voice; then, tone recognition is carried out on the target voice to obtain tone information of each second keyword, and the tone information is added to the second keywords; and finally, inputting the first emotion keyword and the second emotion keyword into a pre-trained neural network model, finally outputting the emotion state of the user, wherein the emotion state is expressed as a positive state or a negative state, and the emotion state of the user is added into the first scenic spot as a tag of the first scenic spot, wherein the positive state corresponds to the positive tag, and the negative state corresponds to the negative tag.
A neural network model: acquiring a first emotion keyword and a second emotion keyword, and preprocessing the first emotion keyword and the second emotion keyword to obtain a training sample set; inputting the training sample set into an initialized emotional state neural network for training, and acquiring the accuracy of a training output result; and if the accuracy rate is greater than a preset threshold value, stopping training to obtain the emotional state neural network model. The emotional state neural network model needs a large amount of historical data to train, the data size determines the accuracy of the model, the emotional state neural network model can train by taking a first emotional keyword and a second emotional keyword which are acquired by historical chat content as input to improve the accuracy of the model, and when the accuracy is higher than a preset accuracy threshold, the training is stopped to obtain the emotional state neural network model, wherein the accuracy threshold can be set to be 85%, 90% and the like.
In an embodiment, the step of matching the historical travel sight data labeled as active labels in the user portrait with all sights of the destination to obtain a plurality of target sights, that is, the step S3 includes:
s31, acquiring all scenic spots of which the labels are positive labels in the user portrait as associated scenic spots;
s32, crawling the attributes of the associated scenic spots and all scenic spots of the destination from a tourism website;
and S33, extracting the scenic spots with the associated scenic spot attributes from all the scenic spots of the destination to be used as target scenic spots.
As described in the above steps S31-S33, all the scenic spots in the user portrait labeled as positive labels are scenic spots in the user portraits of multiple users in the travel group, the obtained associated scenic spots include all the scenic spots in the travel group that are interested by the users with the user portraits, and the attributes of the associated scenic spots and the attributes of all the scenic spots in the destination are crawled from the travel website, and the attributes include suitability for lover tour, parent-child tour, landscape scenery, cultural fumigation, immersion experience, and the like. And extracting the scenic spots with the associated scenic spot attributes from all the scenic spots of the destination as target scenic spots, for example, if the associated scenic spot 1 has a culture pottery attribute, and the destination scenic spot 1 also has a culture pottery attribute, the destination scenic spot 1 is the target scenic spot.
In one embodiment, before the step of determining whether the change user deletes the attraction in the target attraction set in the travel team, that is, before the step S5, the method further includes:
s051, crawling evaluation data of all target scenic spots in the target scenic spot set from the tourism website;
s052, judging whether the poor evaluation of each target scenic spot accounts for one half of the sum of the good evaluation and the medium evaluation one by one;
and S053, if so, displaying the target scenic spot and the poor evaluation data of the target scenic spot to all users in the tourist group.
As described in the above steps S051-S053, before the user performs the deletion operation on the target spot in the target spot set, the evaluation data of all the target spots in the target spot set is crawled from the tourist website, and the target spots with the bad comments accounting for more than one half of the sum of the good comments and the medium comments of the target spots are displayed to the user in the tourist group, and meanwhile, the marking can be performed in the target spot set to provide the reference data before the deletion operation for the user, thereby avoiding the occurrence of the situation that the user performs the wrong deletion to cause the missed spot.
In one embodiment, the step of formulating a travel strategy for the destination according to the location data of all target sights in the set of target sights, namely step S9, comprises:
s91, acquiring the positions of all target scenic spots in the target scenic spot set and the tour duration;
s92, collecting target scenic spots located in the same county-level administrative district to obtain a plurality of combinations;
s93, acquiring the traffic time length between every two scenic spots in each combination; wherein the traffic duration is a public traffic duration;
s94, taking any one of two target scenic spots with the nearest distance as an initial scenic spot, setting the target scenic spot with the nearest distance to the initial scenic spot as a second scenic spot, setting the target scenic spot with the nearest distance to the second scenic spot as a third scenic spot, and arranging by analogy until the arrangement of all the target scenic spots in a combination is completed to form a tour list;
s95, according to the arrangement sequence in the tour list, the scenic spots with the tour duration and the traffic duration not exceeding the set duration are classified as one-day scenic spots, and when a plurality of one-day scenic spots exist, the plurality of one-day scenic spots are arranged according to the sequence of the tour list;
s96, after arrangement of the scenic spots of each combination is completed, arranging a plurality of combinations to obtain a travel route;
and S97, matching the hotel according to the travel route and a set rule to obtain the travel strategy of the destination.
As described in the foregoing steps S91-S97, the positions and the visit durations of all target sights in the target sight spot set are obtained, where the visit durations are calculated according to the longest time period in the recommended visit durations of the tourist sites, for example, when the recommended duration of the sight spot 1 on a certain tourist site is 1-2 hours, the visit duration of the sight spot 1 is 2 hours; after the positions of the target scenic spots are obtained, the positions of the target scenic spots in the same county-level administrative district are collected into a combination because the scenic spot distances of the same county-level administrative district are short, and the target scenic spot collection is divided into a plurality of combinations; in one combination, the traffic time length of every two scenic spots is obtained, and the traffic time length is the time length of public traffic, so that a user can have sufficient time to arrive at the scenic spots; and then any sight spot in the two target sight spots with the closest distance is taken as a starting sight spot, the sight spot with the closest distance to the starting sight spot is taken as a second sight spot, the sight spot with the closest distance to the second sight spot is taken as a third sight spot, and the arrangement of all the target sight spots of one combination is completed by the arrangement of the sight spots so as to form a combined tour list. According to the sequence of the tour list, starting from the first sight spot in the tour list, the sight spots with the tour duration and the traffic duration not exceeding the set duration (adjusted according to specific conditions and preferably set to 10 hours) are classified as one-day sight spots, when a plurality of one-day sight spots exist, the plurality of one-day sight spots are arranged according to the sequence of the tour list, for example, when the target sight spot tour duration and the traffic duration in the combination 1 are 17 hours, the sight spots in the first 10 hours are one-day sight spots, the sight spots in the last 7 hours are one-day sight spots, two one-day sight spots are arranged according to the sequence of the tour list, the one-day sight spot in 10 hours is in the front, and the one-day sight spot in 7 hours is in the back. After the daily scenic spots of each combination in the target scenic spot set and the arrangement sequence of the daily scenic spots are obtained according to the rules, the multiple combinations are randomly ordered to obtain travel routes, the travel routes are displayed to each user in a travel group, the user can sequentially adjust the combination or the daily scenic spots or the sequence of the scenic spots in the daily scenic spots, and finally the hotel is matched according to the travel routes according to the set rules to obtain the travel strategy of the destination.
In one embodiment, the step of matching hotels according to the set rules according to the travel routes, namely the step S97, includes:
s971, obtaining a scenic spot of a first day in a travel route;
s972, matching hotels in a set range of a first scenic spot in the scenic spots of the first day to get into a hotel, and matching hotels in a set range of the last scenic spot to get into a hotel of the first day;
s973, matching the hotel in the set range of the last scenic spot in the scenic spots on the last day as a return-trip check-in hotel;
s974, starting from the second day, sequentially judging whether the distance between the hotel on the previous day and the last scenic spot in the scenic spots on the current day exceeds a set distance;
s975, if not, taking the hotel in the previous day as the hotel in the current day;
s976, if yes, matching the hotel in the set range of the last scenic spot in the scenic spot of the current day with the hotel of the current day;
s977, when the hotels in two adjacent days are different, matching a plurality of luggage deposit service points between the position of the hotel in the previous day and the position of the first scenic spot in the next day;
and S978, setting the baggage registration service point closest to the hotel position on the next day as a final registration service point.
As described in the above steps S971-S978, after the combination of the target attraction sets is arranged, an order of a plurality of sights of one day is formed, and sights of the first day, sights of the second day, sights of the third day, and the like are obtained in the order. The scenic spots on the first day are obtained, and the scenic spot visited first after the user arrives at the destination is the first scenic spot in the scenic spots on the first day, so that hotels in a set range (adjusted according to specific conditions and preferably set to be 3 kilometers) of the first scenic spot in the scenic spots on the first day are matched to be hotel arrivals and hotels in a set range of the last scenic spot on the first day are matched to be hotels on the first day, and the user can go out conveniently. Since the user will return after visiting the last sight spot on the last day, the hotel in the set range (adjusted according to the specific situation, preferably set to 3 km) matched with the last sight spot in the sight spot on the last day is the back-trip hotel. In addition, whether the estimated time point of the last scenic spot of the last day after the visit is finished exceeds 15:00 can be judged, if yes, the hotel is matched, and if not, the user can be recommended to directly buy a return ticket for travel on the same day. When the hotels on the first day and the last day are matched, starting from the second day, and when the distance between the hotel on the current day and the last scenic spot in the scenic spots on the current day does not exceed a set distance (adjusted according to specific conditions, preferably set to be 5 kilometers), the hotel on the previous day is taken as the hotel on the current day, so that a user is prevented from spending a large amount of time on the way to return to the hotel; when the distance between the hotel on the previous day and the last scenic spot in the scenic spots on the current day exceeds a set distance (adjusted according to specific conditions, preferably set to 5 kilometers), the user is tired after visiting the scenic spots on the day, so that the hotel in the set range of the last scenic spot in the scenic spot on the current day is matched as the hotel on the current day; the method comprises the following steps that a baggage transfer problem occurs in the process of hotel replacement, so that when hotels on two adjacent days are different, a plurality of baggage registration service points between the hotel position on the previous day and the first scenic spot position on the next day are matched, and the baggage registration service point closest to the hotel position on the next day is set as a final baggage registration service point; the hotel position on the previous day to the first scenic spot position on the next day is a necessary path for the user to go to the scenic spot, so that the user can conveniently deposit luggage, the time of the user is saved, and worries of the user are solved.
In one embodiment, after the step of locking the target sight set and formulating the travel strategy of the destination according to the position data of all the target sights in the target sight set, that is, after the step S9, the method further includes:
s10, after the travel is finished, sending an evaluation request to each user in the travel group to evaluate scenic spots contained in the travel strategy;
s11, obtaining the evaluation of any attraction in the travel strategy by any user;
s12, judging whether the user portrait of the current user has the scenery spot;
s13, if the user portrait of the current user has the scenery spot, updating the user portrait of the current user according to the evaluation of the current scenery spot;
s14, if the user image of the current user does not have the sight spot, judging whether the evaluation of the current sight spot is a positive evaluation;
s15, if the evaluation of the current scenery spot is positive evaluation, adding the current scenery spot in the portrait of the current user, setting the label of the current scenery spot as an active label, and increasing the weight value of the scenery spot setting value associated with the current scenery spot;
and S16, if the evaluation of the current scenery spot is negative evaluation, adding the current scenery spot in the portrait of the current user, setting the label of the current scenery spot as a negative label, and simultaneously reducing the weight value of the scenery spot setting value associated with the current scenery spot.
After the travel strategy of the destination is established, as described in the above steps S10-S16, the travel team travels according to the established strategy, and after the travel is finished, an evaluation request is sent to each user in the travel team to evaluate the scenic spots included in the travel strategy, so that the user image of each user in the travel team can be updated according to the evaluation, and the strategy can be established by using the user image next time. The user portrait updating method of a certain user in the travel group comprises the following steps: the method comprises the steps of obtaining evaluation of a user (any selected user in a travel group) on any scenic spot in the travel strategy, judging whether the user portrait of the user has the scenic spot (when the travel strategy is determined, if the user has the user portrait, user historical travel data are adopted for matching, so the scenic spot of a destination is not in the user portrait), when the travel strategy is determined, if the user does not have the user portrait, the user portrait created by the scenic spot of the destination is adopted when the user portrait is created, so the scenic spot of the destination is in the user portrait, if the user portrait of the user has the scenic spot, the user portrait of the user is updated according to the evaluation of the user on the current scenic spot, namely if the user evaluates positively (such as likes, satisfies, and the like) during the evaluation, the scenic spot is an active tag (if the scene tag of the scenic spot originally is the active tag, the scene tag is not changed, if the scene tag is the passive tag, a change to a positive tag) if the user's rating is negative (e.g., dislike or dissatisfaction), the tag of the spot is a negative tag (if the tag of the spot is a negative tag, the tag is not changed, and if the tag is a positive tag, the tag is changed to a negative tag).
If the situation that the scenery spot does not exist in the user image of the user is detected, when the evaluation of the user is positive evaluation, the scenery spot is added into the user image, a positive label is added to the scenery spot, meanwhile, a weight value of a set numerical value (adjusted according to specific conditions and not limited) of the scenery spot associated with the current scenery spot is added, the associated scenery spot is a scenery spot contained in the user image matched with the scenery spot when the travel strategy is determined, and the user evaluation of the scenery spot is positive evaluation, which indicates that the matching result is satisfied by the user, so that the weight value of the associated scenery spot is increased, the associated scenery spot is adopted for matching in the following process, and the satisfaction degree of the user is ensured. When the evaluation of the user is negative evaluation, the scenery spot is added in the user portrait, a negative label is added to the scenery spot, and meanwhile, the weight value of a numerical value (adjusted according to specific conditions and not limited) set for the scenery spot associated with the current scenery spot is reduced, so that the situation that the result of the matching of the associated scenery spot is unsatisfactory by the user and has deviation is shown as the evaluation of the user to the scenery spot is negative evaluation, the weight value of the associated scenery is reduced, and when the weight value of the associated scenery is reduced to 0, the label of the associated scenery is changed into a negative label, so that the scenery which is satisfactory by the user can be matched more accurately when the associated scenery is used for matching subsequently.
As shown in fig. 2, the present invention also provides a multi-user travel strategy making device, comprising:
the system comprises an acquisition module 1, a display module and a display module, wherein the acquisition module is used for acquiring a destination selected by any user in a travel group and acquiring all scenic spots of the destination and ranks of the scenic spots;
the calling module 2 is used for calling user figures of all users in the travel group from a travel picture database to obtain historical travel scenic spot data of all the users;
the matching module 3 is used for matching the historical travel scenic spot data with positive labels in the user portrait with all scenic spots of the destination to obtain a plurality of target scenic spots;
the collecting module 4 is used for collecting a plurality of target scenic spots and scenic spots ranked in the top three of all the scenic spots of the destination to obtain a target scenic spot set;
the judging module 5 is used for judging whether a change user deletes the scenic spots in the target scenic spot set in the travel group;
the calculating module 6 is used for calculating the weight value of the deleted target scenic spot when the scenic spot in the target scenic spot set is deleted by the change user in the travel group, and judging whether the weight value of the deleted target scenic spot is larger than a set value or not;
the rejecting module 7 is configured to reject to modify the deletion of the user and obtain the position data of the deleted target scenic spot when the weight value of the deleted target scenic spot is greater than a set value, match a rest place within a predetermined range of the deleted target scenic spot, and define the rest place as the current deleted scenic spot of the modifying user;
an adding module 8, configured to add the deleted scenery spot to the user portrait of the modifying user and add a negative tag to the scenery spot in the user portrait of the modifying user;
and the locking module 9 is used for locking the target sight spot set and formulating the travel strategy of the destination according to the position data of all the target sight spots in the target sight spot set.
In one embodiment, further comprising:
a user representation determination module for determining whether all users in the travel group have a user representation;
the execution module is used for executing the step of obtaining the user portraits of all the users in the travel group to obtain historical travel sight data of all the users when all the users in the travel group have the user portraits;
the first user definition module is used for defining the user without the user image as the first user and acquiring the chat content of the first user when the user does not have the user image in all the users in the travel group; the chat content is the chat content of the first user and other users in the travel group;
the first scenic spot matching module is used for matching the chat content with all the scenic spots of the destination to obtain a plurality of first scenic spots and labels of the first scenic spots;
the first scenery spot association module is used for associating the plurality of first scenery spots with user information of a first user to form a user portrait of the first user;
and the user portrait adding module is used for adding the user portrait of the first user into the travel portrait database.
In one embodiment, the first sight matching module comprises:
a to-be-confirmed sight spot extraction unit, configured to extract one sight spot of all sight spots of the destination as a to-be-confirmed sight spot, where when the to-be-confirmed sight spot appears in the chat content, the to-be-confirmed sight spot is a first sight spot;
the target sentence searching unit is used for searching sentences of the first scenic spot in the chat content to obtain target sentences;
the first word segmentation unit is used for segmenting the target sentence to obtain a first emotion keyword in the target sentence;
the target voice screening unit is used for screening out the voices of the scenic spots of the destination in the chat content to obtain target voices;
the second word segmentation unit is used for carrying out character recognition and word segmentation on the target voice to obtain a second emotion keyword in the target voice;
a tone information identification unit, configured to perform tone identification on the target speech to obtain tone information corresponding to the second emotion keyword, and add the tone information to the second emotion keyword;
the emotion state unit is used for inputting the first emotion keyword and the second emotion keyword into a preset neural network model to obtain the emotion state of the user;
and the label adding unit is used for adding the emotional state of the user as the label of the first sight spot into the first sight spot.
In one embodiment, the matching module 3 includes:
the associated scenic spot obtaining unit is used for obtaining all scenic spots of which the labels are active labels in the user portrait as associated scenic spots;
the attribute acquisition unit is used for crawling the attributes of the associated scenic spots and all the scenic spots of the destination from a tourism website;
and the target sight spot unit is used for extracting the sight spots with the associated sight spot attributes from all the sight spots of the destination to be used as target sight spots.
In one embodiment, the locking module 9 comprises:
the position acquisition unit is used for acquiring the positions of all target scenic spots in the target scenic spot set and the tour duration;
the collection unit is used for collecting target scenic spots in the same county-level administrative district to obtain a plurality of combinations;
the traffic duration acquisition unit is used for acquiring the traffic duration between every two scenic spots in each combination; wherein the traffic duration is a public traffic duration;
the first arrangement unit is used for taking any one of two target scenic spots with the closest distance as a starting scenic spot, setting the target scenic spot with the closest distance to the starting scenic spot as a second scenic spot, setting the target scenic spot with the closest distance to the second scenic spot as a third scenic spot, and arranging by analogy until the arrangement of all the target scenic spots in one combination is completed to form a tour list;
the second arrangement unit is used for classifying scenic spots with the tour duration and the traffic duration not exceeding the set duration into a one-day scenic spot according to the arrangement sequence in the tour list, and arranging the plurality of one-day scenic spots according to the sequence of the tour list when the plurality of one-day scenic spots exist;
the third arrangement unit is used for arranging a plurality of combinations to obtain a travel route after finishing arrangement of the scenic spots of each combination;
and the hotel matching unit is used for matching hotels according to the travel routes and set rules to obtain the travel strategies of the destinations.
In one embodiment, a hotel matching unit includes:
the scenic spot acquisition subunit is used for acquiring a scenic spot of a first day in the travel route;
the hotel matching subunit is used for matching hotels in the set range of the first scenic spot in the scenic spots of the first day as the hotels entering the room, and matching hotels in the set range of the last scenic spot as the hotels of the first day;
the return hotel matching subunit is used for matching hotels in the set range of the last scenic spot in the scenic spots on the last day as return check-in hotels;
the judging subunit is used for sequentially judging whether the distance between the hotel on the previous day and the last scenic spot in the scenic spots on the current day exceeds a set distance from the second day;
the first sub-unit of the hotel on the day is used for taking the hotel on the previous day as the hotel on the day when the distance between the hotel on the previous day and the last scenic spot in the scenic spots on the day does not exceed the set distance;
the second subunit of the hotel on the day is used for matching the hotel in the set range of the last scenic spot in the scenic spot on the day with the hotel on the day as the hotel on the day when the distance between the hotel on the previous day and the last scenic spot in the scenic spots on the day exceeds the set distance;
the registering service point subunit is used for matching a plurality of luggage registering service points between the position of the hotel on the previous day and the position of the first scenic spot on the next day when the hotels on the two adjacent days are different;
and the final deposit service point subunit is used for setting the baggage deposit service point closest to the hotel position on the next day as the final deposit service point.
In one embodiment, further comprising:
the evaluation module is used for sending an evaluation request to each user in the travel group after the travel is finished so as to evaluate the scenic spots contained in the travel strategy;
the evaluation acquisition module is used for acquiring the evaluation of any user on any scenic spot in the travel strategy;
the scenic spot judging module is used for judging whether the user portrait of the current user has the scenic spot;
the updating module is used for updating the user portrait of the current user according to the evaluation of the current scenery spot when the user portrait of the current user has the scenery spot;
the front evaluation judging module is used for judging whether the evaluation of the current scenic spot is a front evaluation or not when the user portrait of the current user does not have the scenic spot;
the increasing module is used for adding the current scenery spot in the portrait of the current user and setting the label of the current scenery spot as an active label when the evaluation of the current scenery spot is positive evaluation, and increasing the weight value of the scenery spot setting value associated with the current scenery spot;
and the reduction module is used for adding the current scenery spot into the portrait of the current user and setting the label of the current scenery spot as a negative label when the evaluation of the current scenery spot is negative evaluation, and reducing the weight value of the scenery spot setting value associated with the current scenery spot.
The above units, modules, and sub-units are all used to correspondingly execute each step in the multi-user travel strategy making method, and the specific implementation manner thereof is described with reference to the above method embodiment, and will not be described herein again.
As shown in fig. 3, the present invention also provides a computer device, which may be a server, and the internal structure of which 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 computer designed processor is used to provide computational and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used for storing all data required by the process of the multi-user travel strategy making method. 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 implement a multi-user travel strategy.
Those skilled in the art will appreciate that the architecture shown in fig. 3 is only a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects may be applied.
An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, wherein the computer program, when executed by a processor, implements any one of the above-mentioned multi-user travel strategy planning methods.
It will be understood by those skilled in the art that all or part of the processes of the methods of the above embodiments may be implemented by hardware associated with instructions of a computer program, which may be stored on a non-volatile computer-readable storage medium, and when executed, may include processes of the above embodiments of the methods. Any reference to memory, storage, database, or other medium provided herein and used in the examples may include non-volatile and/or volatile memory. 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-rate SDRAM (SSRSDRAM), Enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, apparatus, article, or method. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, apparatus, article, or method that includes the element.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims (9)

1. A multi-user travel strategy making method is characterized by comprising the following steps:
obtaining a destination selected by any user in a travel group, and obtaining all scenic spots of the destination and the ranking of the scenic spots;
determining whether all users in the travel group have a user representation;
if yes, executing the step of obtaining user figures of all users in the travel group to obtain historical travel scenic spot data of all users;
if not, defining the user without the user image as a first user, and acquiring the chat content of the first user; the chat content is the chat content of the first user and other users in the travel group;
matching the chat content with all scenic spots of the destination to obtain a plurality of first scenic spots and tags of the first scenic spots;
associating the plurality of first scenes with user information of a first user to form a user portrait of the first user;
adding a user representation of the first user to a travel representation database;
calling user figures of all users in the travel group from a travel picture database to obtain historical travel scenic spot data of all users;
matching historical travel scenic spot data with positive labels in the user portrait with all scenic spots of the destination to obtain a plurality of target scenic spots;
collecting a plurality of target scenic spots and scenic spots ranked in the top three of all the scenic spots of the destination to obtain a target scenic spot set;
judging whether a change user deletes the scenic spots in the target scenic spot set or not in the travel group;
if the scenic spots in the target scenic spot set are deleted by the change user in the travel group, calculating the weight value of the deleted target scenic spot, and judging whether the weight value of the deleted target scenic spot is larger than a set value or not;
if the weight value of the deleted target scenic spot is larger than the set value, refusing to change the deletion of the user and acquiring the position data of the deleted target scenic spot, matching with the rest places in the preset range of the deleted target scenic spot, and defining the rest places as the current deleted scenic spot of the change user;
adding the deleted sight to the user representation of the modifying user and adding a negative tag to the sight in the user representation of the modifying user;
and locking the target sight spot set, and formulating the travel strategy of the destination according to the position data of all the target sight spots in the target sight spot set.
2. The multi-user travel strategy making method of claim 1, wherein the step of matching the chat content with all attractions of the destination to obtain a number of first attractions and the labels of the first attractions comprises:
extracting one scenery spot from all scenery spots of the destination as a scenery spot to be confirmed, wherein when the scenery spot to be confirmed appears in the chat content, the scenery spot to be confirmed is a first scenery spot;
searching for the sentence with the first sight spot in the chat content to obtain a target sentence;
performing word segmentation on the target sentence to obtain a first emotion keyword in the target sentence;
screening out the voices of the scenic spots of the destination in the chat content to obtain target voices;
performing character recognition and word segmentation on the target voice to obtain a second emotion keyword in the target voice;
performing tone recognition on the target voice to obtain tone information corresponding to the second emotion keyword, and adding the tone information to the second emotion keyword;
inputting the first emotion keyword and the second emotion keyword into a preset neural network model to obtain the emotion state of the user;
and adding the emotional state of the user as a label of the first sight spot into the first sight spot.
3. The multi-user travel strategy making method according to claim 1, wherein said step of matching historical travel spot data labeled as positive in user representation with all spots of the destination to obtain a plurality of target spots comprises:
acquiring all scenic spots of which the labels are active labels in the user portrait as associated scenic spots;
crawling attributes of the associated sight and all sights of the destination from a travel website;
and extracting the scenic spots with the associated scenic spot attributes from all the scenic spots of the destination to be used as target scenic spots.
4. The method of claim 1, wherein the step of formulating the travel strategy for the destination based on the location data of all target sights in the set of target sights comprises:
acquiring the positions of all target scenic spots in the target scenic spot set and the tour duration;
collecting target scenic spots located in the same county-level administrative district to obtain a plurality of combinations;
acquiring the traffic time between every two scenic spots in each combination; wherein the traffic duration is a public traffic duration;
taking any one of two target scenic spots with the closest distance as a starting scenic spot, setting the target scenic spot with the closest distance to the starting scenic spot as a second scenic spot, setting the target scenic spot with the closest distance to the second scenic spot as a third scenic spot, and arranging by analogy until the arrangement of all the target scenic spots in one combination is completed to form a tour list;
according to the arrangement sequence in the tour list, the scenic spots with the tour duration and the traffic duration not exceeding the set duration are classified as one-day scenic spots, and when a plurality of one-day scenic spots exist, the plurality of one-day scenic spots are arranged according to the sequence of the tour list;
after finishing the arrangement of the scenic spots of each combination, arranging a plurality of combinations to obtain a travel route;
and matching the hotel according to the travel route and a set rule to obtain the travel strategy of the destination.
5. The multi-user travel strategy making method according to claim 4, wherein the step of matching hotels according to the travel routes according to set rules comprises:
obtaining a sight spot of a first day in a travel route;
matching the hotel in the set range of the first scenic spot in the scenic spots of the first day as a hotel for arriving at a residence, and matching the hotel in the set range of the last scenic spot as a hotel of the first day;
matching the hotel in the set range of the last scenic spot in the scenic spots on the last day as a return-trip check-in hotel;
sequentially judging whether the distance between the hotel on the previous day and the last scenic spot in the scenic spots on the current day exceeds a set distance from the second day;
if not, taking the hotel on the previous day as the hotel on the current day;
if yes, matching the hotel in the set range of the last scenic spot in the scenic spots of the current day with the hotel of the current day;
when the hotels in two adjacent days are different, matching a plurality of baggage storage service points between the position of the hotel in the previous day and the position of the first scenic spot in the next day;
and setting the baggage registration service point closest to the hotel position on the next day as a final registration service point.
6. The multi-user travel strategy making method of claim 1, wherein after the step of locking the set of target sights and making the travel strategy of the destination according to the position data of all the target sights in the set of target sights, further comprising:
after the travel is finished, an evaluation request is sent to each user in the travel group so as to evaluate the scenic spots contained in the travel strategy;
obtaining the evaluation of any scenic spot in the travel strategy by any user;
judging whether the user portrait of the current user has the scenery spot or not;
if the user portrait of the current user has the scenery spot, updating the user portrait of the current user according to the evaluation of the current scenery spot;
if the user image of the current user does not have the scenery spot, judging whether the evaluation of the current scenery spot is a positive evaluation;
if the evaluation of the current scenery spot is positive evaluation, adding the current scenery spot in the portrait of the current user, setting the label of the current scenery spot as a positive label, and increasing the weight value of the scenery spot setting value associated with the current scenery spot;
and if the evaluation of the current scenery spot is negative evaluation, adding the current scenery spot in the portrait of the current user, setting the label of the current scenery spot as a negative label, and simultaneously reducing the weight value of the scenery spot setting value associated with the current scenery spot.
7. A multi-user travel strategy planning apparatus, comprising:
the system comprises an acquisition module, a display module and a display module, wherein the acquisition module is used for acquiring a destination selected by any user in a travel group and acquiring all scenic spots of the destination and ranks of the scenic spots;
a user representation determination module for determining whether all users in the travel group have a user representation;
the execution module is used for executing the step of obtaining the user portraits of all the users in the travel group to obtain historical travel sight data of all the users when all the users in the travel group have the user portraits;
the first user definition module is used for defining the user without the user image as the first user and acquiring the chat content of the first user when the user does not have the user image in all the users in the travel group; the chat content is the chat content of the first user and other users in the travel group;
the first scenic spot matching module is used for matching the chat content with all the scenic spots of the destination to obtain a plurality of first scenic spots and labels of the first scenic spots;
the first scenery spot association module is used for associating the plurality of first scenery spots with user information of a first user to form a user portrait of the first user;
the user portrait adding module is used for adding the user portrait of the first user into a travel portrait database;
the calling module is used for calling user figures of all users in the travel group from a travel picture database to obtain historical travel scenic spot data of all the users;
the matching module is used for matching the historical travel scenic spot data with positive labels in the user portrait with all scenic spots of the destination to obtain a plurality of target scenic spots;
the collecting module is used for collecting a plurality of target scenic spots and scenic spots ranked in the top three of all the scenic spots of the destination to obtain a target scenic spot set;
the judging module is used for judging whether a change user deletes the scenic spots in the target scenic spot set in the travel group;
the calculation module is used for calculating the weight value of the deleted target scenic spot when the scenic spot in the target scenic spot set is deleted by the change user in the travel group, and judging whether the weight value of the deleted target scenic spot is larger than a set value or not;
the rejection module is used for rejecting the change user to delete and acquiring the position data of the deleted target scenic spot when the weight value of the deleted target scenic spot is larger than a set value, matching the rest places in the preset range of the deleted target scenic spot, and defining the rest places as the current deleted scenic spot of the change user;
the adding module is used for adding the deleted scenic spots to the user portrait of the modifying user and adding negative labels to the scenic spots in the user portrait of the modifying user;
and the locking module is used for locking the target scenery spot set and formulating the travel strategy of the destination according to the position data of all the target scenery spots in the target scenery spot set.
8. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
CN202111053649.6A 2021-09-09 2021-09-09 Multi-user travel strategy making method and device and computer equipment Active CN113505315B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111053649.6A CN113505315B (en) 2021-09-09 2021-09-09 Multi-user travel strategy making method and device and computer equipment

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111053649.6A CN113505315B (en) 2021-09-09 2021-09-09 Multi-user travel strategy making method and device and computer equipment

Publications (2)

Publication Number Publication Date
CN113505315A CN113505315A (en) 2021-10-15
CN113505315B true CN113505315B (en) 2021-12-07

Family

ID=78016791

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111053649.6A Active CN113505315B (en) 2021-09-09 2021-09-09 Multi-user travel strategy making method and device and computer equipment

Country Status (1)

Country Link
CN (1) CN113505315B (en)

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN106886837A (en) * 2017-02-21 2017-06-23 携程旅游网络技术（上海）有限公司 Free walker stroke based on time planning recommends method
CN108369104A (en) * 2015-12-22 2018-08-03 大众汽车有限公司 Method and system for synergistically generating and managing itinerary
CN108446410A (en) * 2018-05-29 2018-08-24 科大讯飞股份有限公司 Information recommendation method, device, system, equipment and readable storage medium storing program for executing
CN111143680A (en) * 2019-12-27 2020-05-12 上海携程商务有限公司 Method and system for recommending route, electronic device and computer storage medium
CN111445308A (en) * 2020-03-26 2020-07-24 四川旅游学院 Tourist attraction recommendation method based on user portrait
CN113159415A (en) * 2021-04-19 2021-07-23 武汉亿融信科科技有限公司 Intelligent tourist attraction route recommendation method based on mobile internet and big data analysis

Family Cites Families (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105246041A (en) * 2015-10-21 2016-01-13 百度在线网络技术（北京）有限公司 Prompting method and device
CN106776774A (en) * 2016-11-11 2017-05-31 努比亚技术有限公司 Mobile terminal chooses picture device and method
JP6385416B2 (en) * 2016-12-19 2018-09-05 英幸 山本 Travel planning system, travel planning method, and program
US20210090149A1 (en) * 2019-09-24 2021-03-25 NextPlan, Inc. Integrated online travel planning system
CN112749339A (en) * 2021-01-18 2021-05-04 陕西师范大学 Tourism knowledge graph-based tourism route recommendation method and system
CN113343127B (en) * 2021-04-25 2023-03-21 武汉理工大学 Tourism route recommendation method, system, server and storage medium

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN108369104A (en) * 2015-12-22 2018-08-03 大众汽车有限公司 Method and system for synergistically generating and managing itinerary
CN106886837A (en) * 2017-02-21 2017-06-23 携程旅游网络技术（上海）有限公司 Free walker stroke based on time planning recommends method
CN108446410A (en) * 2018-05-29 2018-08-24 科大讯飞股份有限公司 Information recommendation method, device, system, equipment and readable storage medium storing program for executing
CN111143680A (en) * 2019-12-27 2020-05-12 上海携程商务有限公司 Method and system for recommending route, electronic device and computer storage medium
CN111445308A (en) * 2020-03-26 2020-07-24 四川旅游学院 Tourist attraction recommendation method based on user portrait
CN113159415A (en) * 2021-04-19 2021-07-23 武汉亿融信科科技有限公司 Intelligent tourist attraction route recommendation method based on mobile internet and big data analysis

Also Published As

Publication number Publication date
CN113505315A (en) 2021-10-15

Similar Documents

Publication Publication Date Title
CN108804633B (en) Content recommendation method based on behavior semantic knowledge network
WO2019184833A1 (en) Tourism information recommending method and device
JP5016101B2 (en) Digital photo content information service
CN103631819B (en) A kind of method and system of picture name
JP3998968B2 (en) Mobile navigation device
US20080270425A1 (en) System and method for connecting individuals in a social networking environment based on facial recognition software
CN105468580A (en) Attention point information based method and apparatus for providing service
CN102292722A (en) Generation of annotation tags based on multimodal metadata and structured semantic descriptors
KR101462348B1 (en) System and method for matching users having matter of common interest and change of talent using tag applicable to mobile messenger
CN103460238A (en) Event determination from photos
US20130051687A1 (en) Image processing system and image processing method
KR101796968B1 (en) Hash Tag recommended method using Exchangeable image file format(EXIF)
KR20150143971A (en) Mobile social network service system for processing big data for travel infomation based on location and method for processing of the same
WO2016202132A1 (en) Method and system for photo management
JP2013093015A (en) Information recommendation method, device, and program
CN102053960B (en) Method and system for constructing quick and accurate Internet of things and Internet search engine according to group requirement characteristics
CN102932321A (en) Information processing apparatus, information processing method, program, and information processing system
US20220083983A1 (en) Schedule management service system and method
CN111708929A (en) Information searching method and device, electronic equipment and storage medium
Zhong et al. Notice of Violation of IEEE Publication Principles: A Big Data Framework to Identify Tourist Interests Based on Geotagged Travel Photos
CN109614558B (en) Multi-positioning travel log automatic generation method and system
CN113505315B (en) Multi-user travel strategy making method and device and computer equipment
CN113656615A (en) Intelligent sharing method and device of travel information and computer equipment
JP4374016B2 (en) Visit spot extraction program and interest evaluation program
KR102370007B1 (en) Real-time travel information provision system based on user location

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