CN113901329A - Travel accommodation recommendation method and device and computer equipment - Google Patents
Travel accommodation recommendation method and device and computer equipment Download PDFInfo
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- CN113901329A CN113901329A CN202111480546.8A CN202111480546A CN113901329A CN 113901329 A CN113901329 A CN 113901329A CN 202111480546 A CN202111480546 A CN 202111480546A CN 113901329 A CN113901329 A CN 113901329A
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Abstract
The invention relates to the technical field of travel service, and discloses a method and a device for recommending travel accommodation and a computer device, wherein the method comprises the following steps: acquiring a destination travel schedule and historical living information of a user; obtaining an accommodation set according to a destination travel schedule; analyzing the historical living information to obtain the lodging consumption grade and the lodging preference attribute; pre-screening the accommodation set to obtain an accommodation updating set; extracting travel dates of a user and sequences of a plurality of tourist attractions; re-screening the accommodation update set to obtain a check-in set; and classifying and sequencing the lodging merchants of each tourist attraction in the lodging set to form a lodging recommendation table, and displaying the lodging recommendation table on the user side. According to the method, the device and the computer equipment for recommending the travel accommodation, the accommodation merchant data of each large website are analyzed and screened so as to display the accommodation merchants most suitable for the user, the user screening time is reduced, and the user experience is improved.
Description
Technical Field
The invention relates to the technical field of travel services, in particular to a method and a device for recommending travel accommodation and computer equipment.
Background
With the continuous development of internet technology, traveling applications based on the internet technology are also endless, such as websites of which to go, donkey-mother traveling websites, pig-flying traveling and the like. These websites can provide travel-related information such as travel advisories, introduction to attractions, and the like. When the user has the travel demand, the related information of tourist attractions, hotels, restaurants and the like can be inquired through the websites, or the travel thoughts, strategies and the like of other users are referred. Meanwhile, as the number of travel websites is continuously increased, the data display of each website on the same scenic spot, hotel and restaurant is different, especially when the user inquires about the check-in merchants after the journey is scheduled, the data of each website is numerous, the user needs to check the price, position and other information of the merchants one by one and perform contrast screening so as to select the most suitable lodging merchant to check in, thus, a large amount of time is consumed for the user, the user is not favorable for finding the optimal lodging merchant, and the user experience is reduced.
Disclosure of Invention
The invention provides a method, a device and computer equipment for recommending travel accommodation, which are used for analyzing and screening accommodation merchant data of various websites according to a destination travel schedule, a consumption grade and accommodation preference attributes of a user so as to display accommodation merchants most suitable for the user, reduce user screening time and improve user experience.
The invention provides a recommendation method for tourism accommodation, which comprises the following steps:
acquiring a destination travel schedule of a user and acquiring historical living information of the user; wherein the destination itinerary arrangement table comprises a plurality of tourist attractions;
obtaining an accommodation set according to the destination travel schedule;
analyzing the historical living information to obtain the lodging consumption grade and the lodging preference attribute of the user;
pre-screening the accommodation set according to the accommodation consumption grade and the accommodation preference attribute of the user to obtain an accommodation updating set;
extracting the travel date of the user in the destination travel schedule and the sequence of a plurality of tourist attractions;
re-screening the accommodation update set according to the sequence of the plurality of tourist attractions to obtain a check-in set;
and classifying and sequencing the lodging merchants of each tourist attraction in the lodging set according to the travel date of the user and the evaluation data of all the lodging merchants in the lodging set to form a lodging recommendation table, and displaying the lodging recommendation table on the user side.
Further, the step of obtaining an accommodation set according to the destination itinerary arrangement table includes:
acquiring the positions of all tourist attractions in the destination journey schedule;
taking the position of each tourist attraction as the center of a circle and the set distance as the radius, and extracting the lodging merchants of each tourist attraction as prepared lodging points;
and combining the prepared accommodation points of all the tourist attractions and classifying the reserved accommodation points by the tourist attractions to obtain the accommodation set.
Further, before the step of analyzing the historical living information to obtain the lodging consumption level and the lodging preference attribute of the user, the method further includes:
judging whether the user has historical living information;
if the user does not have the historical living information, acquiring the historical consumption behavior of the user; wherein the historical consumption behaviors comprise catering consumption, travel consumption and shopping consumption;
searching the catering consumption level, the travel consumption level and the shopping consumption level of the user in a preset consumption level table according to the historical consumption behavior of the user;
predicting the lodging consumption level of the user according to the catering consumption level, the travel consumption level and the shopping consumption level;
and if the user has historical residence information, executing the step of analyzing the historical residence information to obtain the accommodation consumption grade and the accommodation preference attribute of the user.
Further, the step of analyzing the historical living information to obtain the lodging consumption level and the lodging preference attribute of the user comprises:
extracting historical residential rooms of the user, prices of the historical residential rooms, and historical residential merchants of the user;
counting the room types of the historical residential rooms, and calculating the historical average residential price of each room type;
searching a house type consumption grade matched with the historical average residential price of each house type in a preset lodging consumption grade comparison table;
combining the house type, the historical average residential price and the house type consumption grade to form a lodging consumption table indicating the lodging consumption grade of the user;
counting the types of the historical residential merchants, and counting the number of the historical residential merchants contained in each type; wherein the types of the historical residential merchants comprise hotels, apartments and hospices;
and taking the type with the largest number of the historical residential merchants as the lodging preference attribute of the user.
Further, the step of re-screening the accommodation update set according to the sequence of the plurality of tourist attractions to obtain a check-in set includes:
determining a last tourist attraction of each daily trip in the sequence of the plurality of tourist attractions; the tourist attractions of each day journey are determined according to the playing time lengths and the traffic time lengths of the plurality of tourist attractions, or are specified according to the instruction of the user;
the accommodation merchants of the last tourist attraction of each day journey in the accommodation updating set are extracted as merchants to be selected;
and combining a plurality of the merchants to be selected to obtain the check-in set.
Further, the step of forming a check-in recommendation table by sorting the lodging merchants of each tourist attraction in the check-in set according to the travel date of the user and the evaluation data of all the lodging merchants in the check-in set includes:
extracting one accommodation merchant in the check-in set as a target merchant;
obtaining an evaluation picture in the evaluation data of the target merchant and obtaining a room picture uploaded by the target merchant;
calculating the initial similarity of each evaluation picture and each room picture, and calculating the total similarity value of the evaluation picture of a target merchant and the room picture according to the initial similarity;
and classifying all accommodation merchants in the accommodation set according to tourist attractions, and sequencing the accommodation merchants of each tourist attraction according to the total similarity value to form the check-in recommendation table.
Further, after the step of classifying all accommodation merchants in the accommodation set according to tourist attractions, and sorting the accommodation merchants of each tourist attraction according to the total similarity value to form the accommodation recommendation table, the method further comprises:
acquiring house type prices of all accommodation merchants in the lodging set according to the trip date of the user; wherein the house-type price comprises prices for a plurality of platforms;
calculating the total scores of all accommodation merchants in the accommodation set according to the scores of the platforms of all accommodation merchants in the accommodation set;
and adding the total score and the house type price into the check-in recommendation table.
The invention also provides a recommendation device for tourism accommodation, which comprises:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring a destination travel schedule of a user and acquiring historical living information of the user; wherein the destination itinerary arrangement table comprises a plurality of tourist attractions;
the collection module is used for obtaining an accommodation collection according to the destination travel schedule;
the analysis module is used for analyzing the historical living information to obtain the lodging consumption grade and the lodging preference attribute of the user;
the pre-screening module is used for pre-screening the accommodation set according to the accommodation consumption grade and the accommodation preference attribute of the user to obtain an accommodation updating set;
the extraction module is used for extracting the travel date of the user in the destination travel schedule and the sequence of a plurality of tourist attractions;
the rescreening module is used for rescreening the accommodation updating set according to the sequence of the plurality of tourist attractions to obtain a check-in set;
and the recommending module is used for classifying and sequencing the lodging merchants of each tourist attraction in the lodging set according to the travel date of the user and the evaluation data of all the lodging merchants in the lodging set to form a lodging recommending table and displaying the lodging recommending table on the user side.
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:
the method comprises the steps of obtaining a plurality of tourist attractions of a user according to a destination travel schedule of the user, collecting accommodation merchants in a set range of the plurality of tourist attractions to form an accommodation set, pre-screening the accommodation set according to consumption levels and accommodation preference attributes of the user to obtain an accommodation update set, obtaining the last tourist attraction of each day travel according to travel dates of the user in the destination formation schedule and a plurality of tourist attraction sequences to obtain a check-in set of the user, sorting and sequencing all accommodation merchants in the check-in set according to evaluation data of the accommodation merchants in the check-in set, adding multi-platform price and comprehensive score information to form a check-in recommendation table, enabling the user to directly see prices and total comprehensive scores of a plurality of tourist websites of the accommodation merchants which are possibly needed, and facilitating the user to directly perform room reservation, the user screening time is reduced, and the user experience 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 recommendation method for travel accommodation, including:
s1, acquiring a destination travel schedule of the user and acquiring historical living information of the user; wherein the destination itinerary arrangement table comprises a plurality of tourist attractions;
s2, obtaining an accommodation set according to the destination travel schedule;
s3, analyzing the historical living information to obtain the lodging consumption level and the lodging preference attribute of the user;
s4, pre-screening the accommodation set according to the accommodation consumption level and the accommodation preference attribute of the user to obtain an accommodation update set;
s5, extracting travel dates and sequences of a plurality of tourist attractions of the user in the destination travel schedule;
s6, re-screening the accommodation update set according to the sequence of the tourist attractions to obtain a check-in set;
s7, sorting and sequencing the lodging merchants of each tourist attraction in the lodging set according to the travel date of the user and the evaluation data of all the lodging merchants in the lodging set to form a lodging recommendation table, and displaying the lodging recommendation table on the user side.
As described in the step S1, the destination itinerary arrangement table may include only a plurality of tourist attractions, or may include the sequence of the tourist attractions, and the tourist attractions distributed in the itinerary of the day; that is, the destination itinerary arrangement table may be a complete itinerary arrangement table or a partially planned itinerary arrangement table.
As described in step S2, accommodation merchants near a plurality of tourist attractions can be obtained from the plurality of tourist attractions in the destination itinerary schedule. When the destination travel schedule is a schedule formed by partial planning, as the sequence of a plurality of tourist attractions in the destination travel schedule has uncertainty, which tourist attraction is the last attraction every day of the user cannot be determined, the accommodation merchants near all attractions are all regarded as accommodation merchants to be selected; and finally, gathering the accommodation merchants together to form an accommodation set so as to carry out screening.
As described in step S3, when the user has the historical living information, the house type and the price of the historical living of the user are calculated and analyzed, so that the living consumption level and the living preference attribute of the user, that is, which of the hotel, the hotel and the apartment the user habitually lives in, can be obtained, so as to filter the merchants in the living set according to the living consumption level and the living preference attribute, and save the time for the user to actively filter.
As described in step S4, the lodging merchants are screened according to the lodging preference attribute of the user, that is, when the lodging preference attribute of the user is apartment, only the merchants whose attribute is apartment are extracted, and meanwhile, the merchants which do not belong to the consumption level of the user are removed according to the consumption level of the user, and finally, the remaining merchants are aggregated to form an lodging update aggregation, and the lodging merchants in the lodging update aggregation can better meet the needs of the user for lodging.
As described in the foregoing steps S5-S6, the sequence of the plurality of scenic spots may be a planned sequence of scenic spots on each day, or may be a planned sequence of the entire scenic spots throughout the whole day (which scenic spots are not divided into which day), and when the sequence of the plurality of scenic spots is the entire sequence (i.e., the scenic spots on each day are not planned), which scenic spots are listed as scenic spots on the same day are determined according to the playing time length of the scenic spots and the traffic time length between the scenic spots, so that the last scenic spot on each day in the travel date can be obtained, and then lodging merchants near the last scenic spot on each day are screened out to form a lodging set for the user to select; because the user needs to return to the accommodation place for rest as soon as possible after playing for one day, accommodation merchants who live in the set have higher possibility of being selected by the user, the time for the user to actively screen is saved, and the user experience degree is improved.
As described in step S7, since there may be many lodging merchants near each tourist attraction and the evaluation of each lodging merchant on each tourist site is different, the lodging merchants of each tourist attraction in the lodging collection are sorted according to the evaluation data of all the lodging merchants in the lodging collection, and the evaluation data is the comprehensive evaluation data of each large tourist site, and the lodging merchant with the best evaluation is displayed at the top, so that the user can visually see the most preferred lodging merchant, thereby saving the time for the user to perform screening comparison on multiple tourist sites and improving the user experience.
In one embodiment, the step of obtaining an accommodation set according to the destination itinerary schedule includes:
s21, acquiring the positions of all tourist attractions in the destination journey schedule;
s22, taking the position of each tourist spot as the center of a circle and the set distance as the radius, extracting the lodging merchants of each tourist spot as prepared lodging points;
and S23, combining the prepared accommodation points of all the tourist attractions and classifying the prepared accommodation points by the tourist attractions to obtain the accommodation set.
As described in the above steps S21-S23, the positions of all tourist attractions in the destination itinerary arrangement table are obtained, and the positions are used as the center of a circle, a distance (generally set as a length distance that can be reached by walking, or adjusted according to specific situations) is set as a radius, and the accommodation merchants in the circle are extracted as reserve accommodation points, each tourist attraction in the destination itinerary arrangement table has a plurality of reserve accommodation points, and the reserve accommodation points are collected together and classified by the tourist attractions to obtain an accommodation set.
In one embodiment, before the step of analyzing the historical living information to obtain the lodging consumption level and the lodging preference attribute of the user, the method further includes:
s031, judge whether the user has historical residential information;
s032, if the user does not have historical living information, acquiring historical consumption behaviors of the user; wherein the historical consumption behaviors comprise catering consumption, travel consumption and shopping consumption;
s033, searching a catering consumption level, a trip consumption level and a shopping consumption level of the user in a preset consumption level table according to the historical consumption behaviors of the user;
s034, predicting the lodging consumption level of the user according to the catering consumption level, the travel consumption level and the shopping consumption level;
s035, if the user has historical residence information, executing the step of analyzing the historical residence information to obtain the accommodation consumption grade and the accommodation preference attribute of the user.
As described in the above steps S031-S035, before analyzing the historical living information of the user, it is necessary to determine whether the user has the historical living information; when the user has historical residence information, the analysis can be performed to obtain the accommodation consumption level and the accommodation preference attribute. When the user does not have historical living information, predicting the lodging consumption level of the user according to the consumption habits of the user in other aspects in the past, thus obtaining the historical consumption behaviors of the user, wherein the historical consumption behaviors of the user comprise catering consumption, trip consumption, shopping consumption and the like, after the catering consumption, trip consumption and shopping consumption are obtained, calculating the average value of the catering consumption, trip consumption level and shopping consumption level, and then searching the catering consumption level, trip consumption level and shopping consumption level of the user in a preset consumption registration table, wherein the preset consumption level table is preset according to popular consumption, for example, the catering consumption is a first level below 10 yuan, the 10-30 yuan is a second level, the 30-60 is a third level and the like; the first grade is below 100 Yuan for shopping consumption, the second grade is 100-300 Yuan, the third grade is 300-800 Yuan, and so on; the first grade is below 10 yuan, the second grade is 10-30 yuan, the third grade is above 30 yuan and the like; after the average value of the catering consumption, the trip consumption and the shopping consumption of the user is obtained, the catering consumption grade, the trip consumption grade and the shopping consumption grade of the user can be found in the preset consumption grade table, the lodging consumption grade of the user is predicted according to the catering consumption grade, the trip consumption grade and the shopping consumption grade, namely, the median or average of the catering consumption grade, the trip consumption grade and the shopping consumption grade is taken as the lodging consumption grade of the user, and the house type suitable for the lodging price of the user can be recommended according to the corresponding relation of the lodging consumption grades.
In one embodiment, the step of analyzing the historical living information to obtain the lodging consumption level and the lodging preference attribute of the user comprises:
s31, extracting the historical residential rooms of the user, the prices of the historical residential rooms and the historical residential merchants of the user;
s32, counting the room types of the historical residential rooms, and calculating the historical average residential price of each room type;
s33, searching a room type consumption grade matched with the historical average residential price of each room type in a preset lodging consumption grade comparison table;
s34, combining the house type, the historical average residential price and the house type consumption grade to form a lodging consumption table indicating the lodging consumption grade of the user;
s35, counting the types of the historical residential merchants, and counting the number of the historical residential merchants contained in each type; wherein the types of the historical residential merchants comprise hotels, apartments and hospices;
and S36, taking the type with the largest number of the historical residential merchants as the lodging preference attribute of the user.
As described in the above steps S31-S36, when the user has the history residential information, the history residential room of the user and the prices, history residential merchants of the history residential room are extracted; the method comprises the steps that the house types of historical residential rooms can be counted according to the historical residential rooms of users, wherein the house types comprise small single rooms, large bed rooms, standard rooms, suite rooms and the like, each house type corresponds to a plurality of rooms in which the users live historically, after the house types are obtained, the historical average residential price of the users under each house type is calculated, for example, if the users live 10 times under the standard rooms, the historical average residential price of the standard rooms is obtained by dividing the total price of the users who live 10 times by 10; searching a house type consumption grade matched with the historical average residential price of each house type in a preset accommodation consumption grade comparison table, setting the preset accommodation consumption grade table by referring to the preset consumption grade table, and obtaining a house type consumption range accepted by a user according to the house type consumption grade, wherein the house type consumption grade of the user is the second grade, and the corresponding range is 400 yuan; and (3) taking the house type, the historical average residential price and the house type consumption grade as fields, and combining each piece of data of the user as a line into a table to form an accommodation consumption table indicating the accommodation consumption grade of the user, wherein one piece of data of the user is the standard room, 248 units and the second grade (200-) -400 units. Counting the types of historical residential merchants of the user, counting the number of the historical residential merchants contained in each type, and taking the type with the largest number of the historical residential merchants as the lodging preference attribute of the user; for example, the counted types of the historical residential merchants include a hotel and an apartment, the historical residential merchant corresponding to the hotel is 15, the historical residential merchant corresponding to the apartment is 9, and the lodging preference attribute of the user is the hotel.
In one embodiment, the step of re-screening the accommodation update set according to the sequence of the plurality of tourist attractions to obtain a check-in set includes:
s61, determining the last tourist attraction of each day journey in the sequence of the plurality of tourist attractions; the tourist attractions of each day journey are determined according to the playing time lengths and the traffic time lengths of the plurality of tourist attractions, or are specified according to the instruction of the user;
s62, extracting the lodging merchant of the last tourist attraction of each day journey in the lodging update set as the merchant to be selected;
and S63, combining the multiple merchants to be selected to obtain the check-in set.
As described in steps S61-S63, when the sequence of tourist attractions includes the plan for tourist attractions on each day, the last tourist attraction on each day' S journey in the sequence of tourist attractions is extracted; when the sequence of the tourist attractions does not comprise the planning of the tourist attractions of each day, determining the tourist attractions of each day according to the playing time length and the traffic time length of the tourist attractions, namely listing the tourist attractions with the sum of the playing time length and the traffic time length not more than eight hours (which can be adjusted according to specific needs) as the tourist attractions of the same day, or displaying the sequence of the tourist attractions to a user, and selecting the last tourist attraction of each day of travel by the user; after the last tourist attraction of each travel is obtained, the accommodation merchants near the tourist attractions are merchants needing to check in by the user, so that the accommodation merchants of the last tourist attraction of each travel are extracted from the accommodation update set as merchants to be selected, the merchants to be selected are combined to obtain a check-in set, the accommodation merchants in the check-in set are sorted and displayed to the user, and the user can select the accommodation merchants conveniently.
In one embodiment, the step of forming a check-in recommendation table by sorting the lodging merchants of each tourist attraction in the check-in set according to the travel date of the user and the evaluation data of all the lodging merchants in the check-in set includes:
s71, extracting one accommodation merchant in the lodging set as a target merchant;
s72, obtaining an evaluation picture in the evaluation data of the target merchant, and obtaining a room picture uploaded by the target merchant;
s73, calculating the initial similarity of each evaluation picture and each room picture, and calculating the total similarity value of the evaluation picture and the room picture of the target merchant according to the initial similarity;
s74, classifying all accommodation merchants in the accommodation set according to tourist attractions, and sequencing the accommodation merchants of each tourist attraction according to the total similarity value to form the accommodation recommendation table.
As described in the above steps S71-S74, after the check-in set is obtained, the merchants to be selected in the check-in set need to be sorted and sorted, so that the user can visually check the optimal lodging merchant. Therefore, one accommodation merchant in the accommodation set is extracted as a target merchant, evaluation pictures in evaluation data of the target merchant and room pictures uploaded by the target merchant are extracted, an initial similarity value of each evaluation picture and each room picture is calculated (the calculation method of the similarity is a calculation method in the prior art, for example, ssim (structural similarity) structural similarity is not repeated here), and a plurality of initial similarity values are obtained, for example, if 10 evaluation pictures and 10 merchant pictures are shared, 100 similarity values are obtained; further, calculating a total similarity value between the evaluation picture of the target merchant and the room picture according to the plurality of initial similarity values, namely the total similarity value = the sum of the plurality of similarity values/the number of the similarity values; and finally, classifying all accommodation merchants entering the accommodation set according to the tourist attractions, sequencing the accommodation merchants of each tourist attraction according to the total similarity value to form an accommodation recommendation table, and displaying the accommodation recommendation table to the user, so that the user can visually check the optimal accommodation merchants, and the time for comparing and screening the user is saved.
In one embodiment, after the step of classifying all accommodation merchants in the accommodation set according to tourist attractions, and sorting the accommodation merchants of each tourist attraction according to the total similarity value to form the accommodation recommendation table, the method further includes:
s75, acquiring house type prices of all accommodation merchants in the check-in set according to the travel date of the user; wherein the house-type price comprises prices for a plurality of platforms;
s76, calculating the total scores of all accommodation merchants in the accommodation set according to the scores of multiple platforms of all accommodation merchants in the accommodation set;
and S77, adding the total score and the house type price into the lodging recommendation table.
As described in the above steps S75-S77, after the check-in recommendation table is obtained, information such as house type and price also needs to be displayed, so as to avoid time waste caused by re-inquiry by the user; because the house type prices of the lodging merchants are different due to different dates, the house type prices of all the lodging merchants in the lodging set are obtained according to the trip date of the user, and the house type prices comprise prices of a plurality of platforms (namely a plurality of travel websites); then, calculating the total score of all accommodation merchants in the accommodation set according to the scores of the multiple platforms of all accommodation merchants in the accommodation set, namely the total score = the total score of the multiple platforms/the number of the platforms; and finally, the total score and the house type price are added into the check-in recommendation table, so that a user can visually check whether the score is consistent with the actual evaluation, and meanwhile, the house type is simultaneously shown when the house type price of one accommodation merchant is added and is displayed from low to high according to the price, so that the user can directly compare the house type and the price in the check-in recommendation table, the house type and the price do not need to be inquired again, the time is saved, and the use experience of the user is improved.
The invention also provides a recommendation device for tourism accommodation, which comprises:
the system comprises an acquisition module 1, a storage module and a processing module, wherein the acquisition module is used for acquiring a destination travel schedule of a user and acquiring historical living information of the user; wherein the destination itinerary arrangement table comprises a plurality of tourist attractions;
the collection module 2 is used for obtaining an accommodation collection according to the destination travel schedule;
the analysis module 3 is used for analyzing the historical living information to obtain the lodging consumption grade and the lodging preference attribute of the user;
the pre-screening module 4 is used for pre-screening the accommodation set according to the accommodation consumption grade and the accommodation preference attribute of the user to obtain an accommodation updating set;
the extraction module 5 is used for extracting the travel date of the user in the destination travel schedule and the sequence of a plurality of tourist attractions;
the rescreening module 6 is used for rescreening the accommodation update set according to the sequence of the plurality of tourist attractions to obtain a check-in set;
and the recommending module 7 is used for sorting and sequencing the lodging merchants of each tourist attraction in the lodging set according to the travel date of the user and the evaluation data of all the lodging merchants in the lodging set to form a lodging recommending table and displaying the lodging recommending table on the user side.
In one embodiment, aggregation module 2, includes:
the position acquisition unit is used for acquiring the positions of all tourist attractions in the destination travel schedule;
the reserved lodging point extraction unit is used for extracting lodging merchants of each tourist attraction as reserved lodging points by taking the position of each tourist attraction as the center of a circle and a set distance as a radius;
and the combination unit is used for combining the prepared accommodation points of all the tourist attractions and classifying the prepared accommodation points by the tourist attractions to obtain the accommodation set.
In one embodiment, further comprising:
the historical living information judging module is used for judging whether the user has historical living information;
the historical consumption behavior acquisition module is used for acquiring the historical consumption behavior of the user when the user does not have the historical residence information; wherein the historical consumption behaviors comprise catering consumption, travel consumption and shopping consumption;
the level searching module is used for searching the catering consumption level, the travel consumption level and the shopping consumption level of the user in a preset consumption level table according to the historical consumption behaviors of the user;
the grade prediction module is used for predicting the lodging consumption grade of the user according to the catering consumption grade, the travel consumption grade and the shopping consumption grade;
and the execution module is used for executing the step of analyzing the historical residence information to obtain the accommodation consumption grade and the accommodation preference attribute of the user when the user has the historical residence information.
In one embodiment, the analysis module 3 comprises:
a room extracting unit for extracting a historical residential room of the user, prices of the historical residential room, and a historical residential merchant of the user;
the house type counting unit is used for counting the house types of the historical residential rooms and calculating the historical average residential price of each house type;
the consumption grade searching unit is used for searching the house type consumption grade matched with the historical average residential price of each house type in a preset lodging consumption grade comparison table;
the accommodation consumption table unit is used for combining the house type, the historical average living price and the house type consumption grade to form an accommodation consumption table indicating the accommodation consumption grade of the user;
the historical residential merchant number counting unit is used for counting the types of the historical residential merchants and counting the number of the historical residential merchants contained in each type; wherein the types of the historical residential merchants comprise hotels, apartments and hospices;
and the unit is used for taking the type with the largest number of historical residential merchants as the lodging preference attribute of the user.
In one embodiment, the rescreening module 6 includes:
a tourist attraction determination unit for determining the last tourist attraction for each daily journey in the sequence of the plurality of tourist attractions; the tourist attractions of each day journey are determined according to the playing time lengths and the traffic time lengths of the plurality of tourist attractions, or are specified according to the instruction of the user;
the to-be-selected merchant extracting unit is used for extracting the lodging merchants of the last tourist attraction of each day journey in the lodging updating set as to-be-selected merchants;
and the check-in set unit is used for combining a plurality of the merchants to be selected to obtain the check-in set.
In one embodiment, the recommendation module 7 includes:
the target merchant extracting unit is used for extracting one accommodation merchant in the check-in set as a target merchant;
the picture acquisition unit is used for acquiring an evaluation picture in the evaluation data of the target merchant and acquiring a room picture uploaded by the target merchant;
the similarity calculation unit is used for calculating the initial similarity of each evaluation picture and each room picture and calculating the total similarity value of the evaluation picture and the room picture of a target merchant according to the initial similarity;
and the classification unit is used for classifying all accommodation merchants in the accommodation set according to tourist attractions, and sequencing the accommodation merchants of each tourist attraction according to the total similarity value to form the check-in recommendation table.
In one embodiment, further comprising:
the house type price acquisition module is used for acquiring house type prices of all accommodation merchants in the check-in set according to the travel date of the user; wherein the house-type price comprises prices for a plurality of platforms;
the total score calculation module is used for calculating the total scores of all accommodation merchants in the accommodation set according to the scores of a plurality of platforms of all accommodation merchants in the accommodation set;
and the adding module is used for adding the total score and the house type price into the lodging recommendation table.
The modules and units are used for correspondingly executing the steps in the method for recommending travel accommodation, and the specific implementation manner of the method is described with reference to the method embodiment, and is not described again here.
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 to store all the data required by the process of the travel accommodation recommendation 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 travel accommodation recommendation method.
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, and the computer program, when executed by a processor, implements any one of the methods for recommending travel accommodation.
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 (10)
1. A travel accommodation recommendation method is characterized by comprising the following steps:
acquiring a destination travel schedule of a user and acquiring historical living information of the user; wherein the destination itinerary arrangement table comprises a plurality of tourist attractions;
obtaining an accommodation set according to the destination travel schedule;
analyzing the historical living information to obtain the lodging consumption grade and the lodging preference attribute of the user;
pre-screening the accommodation set according to the accommodation consumption grade and the accommodation preference attribute of the user to obtain an accommodation updating set;
extracting the travel date of the user in the destination travel schedule and the sequence of a plurality of tourist attractions;
re-screening the accommodation update set according to the sequence of the plurality of tourist attractions to obtain a check-in set;
and classifying and sequencing the lodging merchants of each tourist attraction in the lodging set according to the travel date of the user and the evaluation data of all the lodging merchants in the lodging set to form a lodging recommendation table, and displaying the lodging recommendation table on the user side.
2. The travel accommodation recommendation method of claim 1, wherein the step of obtaining an accommodation set according to the destination itinerary schedule comprises:
acquiring the positions of all tourist attractions in the destination journey schedule;
taking the position of each tourist attraction as the center of a circle and the set distance as the radius, and extracting the lodging merchants of each tourist attraction as prepared lodging points;
and combining the prepared accommodation points of all the tourist attractions and classifying the reserved accommodation points by the tourist attractions to obtain the accommodation set.
3. The method of claim 1, wherein the step of analyzing the historical occupancy information to obtain the user's lodging consumption level and lodging preference attribute is preceded by the step of:
judging whether the user has historical living information;
if the user does not have the historical living information, acquiring the historical consumption behavior of the user; wherein the historical consumption behaviors comprise catering consumption, travel consumption and shopping consumption;
searching the catering consumption level, the travel consumption level and the shopping consumption level of the user in a preset consumption level table according to the historical consumption behavior of the user;
predicting the lodging consumption level of the user according to the catering consumption level, the travel consumption level and the shopping consumption level;
and if the user has historical residence information, executing the step of analyzing the historical residence information to obtain the accommodation consumption grade and the accommodation preference attribute of the user.
4. The travel lodging recommendation method as claimed in claim 1, wherein the step of analyzing the historical lodging information to obtain the lodging consumption level and the lodging preference attribute of the user comprises:
extracting historical residential rooms of the user, prices of the historical residential rooms, and historical residential merchants of the user;
counting the room types of the historical residential rooms, and calculating the historical average residential price of each room type;
searching a house type consumption grade matched with the historical average residential price of each house type in a preset lodging consumption grade comparison table;
combining the house type, the historical average residential price and the house type consumption grade to form a lodging consumption table indicating the lodging consumption grade of the user;
counting the types of the historical residential merchants, and counting the number of the historical residential merchants contained in each type; wherein the types of the historical residential merchants comprise hotels, apartments and hospices;
and taking the type with the largest number of the historical residential merchants as the lodging preference attribute of the user.
5. The method of claim 1, wherein the step of re-screening the updated set of lodging updates according to the sequence of the plurality of tourist attractions to obtain a lodging set comprises:
determining a last tourist attraction of each daily trip in the sequence of the plurality of tourist attractions; the tourist attractions of each day journey are determined according to the playing time lengths and the traffic time lengths of the plurality of tourist attractions, or are specified according to the instruction of the user;
the accommodation merchants of the last tourist attraction of each day journey in the accommodation updating set are extracted as merchants to be selected;
and combining a plurality of the merchants to be selected to obtain the check-in set.
6. The travel accommodation recommendation method according to claim 1, wherein the step of forming an accommodation recommendation table by sorting accommodation merchants of each tourist attraction in the accommodation set according to the travel date of the user and the evaluation data of all the accommodation merchants in the accommodation set comprises:
extracting one accommodation merchant in the check-in set as a target merchant;
obtaining an evaluation picture in the evaluation data of the target merchant and obtaining a room picture uploaded by the target merchant;
calculating the initial similarity of each evaluation picture and each room picture, and calculating the total similarity value of the evaluation picture of a target merchant and the room picture according to the initial similarity;
and classifying all accommodation merchants in the accommodation set according to tourist attractions, and sequencing the accommodation merchants of each tourist attraction according to the total similarity value to form the check-in recommendation table.
7. The travel accommodation recommendation method of claim 6, wherein after the step of classifying all accommodation merchants in the accommodation set according to tourist attractions, and sorting the accommodation merchants of each tourist attraction according to the total similarity value to form the lodging recommendation table, the method further comprises:
acquiring house type prices of all accommodation merchants in the lodging set according to the trip date of the user; wherein the house-type price comprises prices for a plurality of platforms;
calculating the total scores of all accommodation merchants in the accommodation set according to the scores of the platforms of all accommodation merchants in the accommodation set;
and adding the total score and the house type price into the check-in recommendation table.
8. A travel accommodation recommendation device, comprising:
the system comprises an acquisition module, a storage module and a processing module, wherein the acquisition module is used for acquiring a destination travel schedule of a user and acquiring historical living information of the user; wherein the destination itinerary arrangement table comprises a plurality of tourist attractions;
the collection module is used for obtaining an accommodation collection according to the destination travel schedule;
the analysis module is used for analyzing the historical living information to obtain the lodging consumption grade and the lodging preference attribute of the user;
the pre-screening module is used for pre-screening the accommodation set according to the accommodation consumption grade and the accommodation preference attribute of the user to obtain an accommodation updating set;
the extraction module is used for extracting the travel date of the user in the destination travel schedule and the sequence of a plurality of tourist attractions;
the rescreening module is used for rescreening the accommodation updating set according to the sequence of the plurality of tourist attractions to obtain a check-in set;
and the recommending module is used for classifying and sequencing the lodging merchants of each tourist attraction in the lodging set according to the travel date of the user and the evaluation data of all the lodging merchants in the lodging set to form a lodging recommending table and displaying the lodging recommending table on the user side.
9. 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 7 when executing the computer program.
10. 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 7.
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