Tourism companion method based on big data

Abstract

The invention relates to the field of tourism grouping, and discloses a tourism companion method based on big data, and the method comprises the steps: firstly collecting and updating the tourism consumption information of historical tourists; classifying the consumption records to obtain tourist consumption type records; obtaining a consumption item-consumption popularity curve graph from the tourist consumption type record according to historical tourist consumption times; collecting tourism plans of tourists in real time, and matching the consumption item-consumption popularity curve chart to obtain a tourist exclusive planning consumption curve; matching the tourist exclusive planning consumption curve with the tourism plan to obtain a high-matching-degree tourist group; according to different accompanying demands of tourists, tourism pairing accompanying is carried out, and tourism accompanying schemes of the tourists are obtained and dynamically adjusted; the problems that tourists are difficult to find travel lugs in the same way, the consumption concept and level of the travel lugs are different, so that the travel experience is poor, and the huddling travel is not free are solved.

Description

Technical Field

[0001] The present invention relates to the field of group travel, and in particular to a travel companion method based on big data. Background Art

[0002] As people's material lives improve, their spiritual lives are also improving. More and more people are starting to pay attention to travel and experience different regional customs and cultures. They are beginning to arrange tourist attractions and itineraries through relevant travel itinerary planning applications. In addition, many platforms have the unique feature of automatically "catering to people's tastes" and will more actively push relevant information to people who are interested in this area.

[0003] At present, more and more people are starting to travel together, but now many people want to travel but have no companions, and it is difficult to find travel companions with a suitable travel budget, travel time and duration. Now tourists who want to travel together can only do so by making an appointment with friends or joining a tour group, but the tour group experience is generally not good and not very free, so it is necessary to bring together tourists with the same travel intentions and travel budgets. Summary of the invention

[0004] The present invention is intended to provide a travel companion method based on big data to solve the problems that it is difficult for tourists to find like-minded travel companions, the different consumption concepts and levels of travel companions lead to a bad travel experience, and group travel is not free.

[0005] In order to achieve the above object, the present invention provides the following method:

[0006] A travel companion method based on big data provided by the present invention is:

[0007] S1: collect and update historical tourists’ travel consumption information in real time;

[0008] S2: Classifying the consumption records according to the types of consumption in the historical tourist's travel information to obtain tourist consumption type records;

[0009] S3: obtaining a consumption item-consumption heat curve chart based on the consumption type records of the tourists according to the historical consumption times of the tourists;

[0010] S4: collecting tourists' travel plans in real time, and matching the consumption items-consumption heat curve according to the tourists' travel plans to obtain tourists' exclusive planned consumption curve;

[0011] S5: Matching the tourist-specific planned consumption curves of different tourists and the tourist travel plans to obtain a high-matching tourist group;

[0012] S6: Pairing the high-matching tourist groups according to the different travel companion needs of different tourists to obtain a travel companion plan for tourists;

[0013] S7: Dynamically adjust the tourist travel companion plan according to the updated changes in the tourist information.

[0014] Preferably, the travel consumption information of the historical tourists is all consumption records of the historical tourists related to the travel itinerary from the start of the travel itinerary to the end of the travel itinerary, specifically including: accommodation consumption records, food consumption records, ticket consumption records, transportation fee consumption records and other consumption records.

[0015] Preferably, the step of classifying the consumption records according to the types of consumption in the travel information of the historical tourists to obtain the records of tourist consumption types includes: dividing the travel consumption information of the historical tourists into five categories of consumption information according to the accommodation consumption records, food consumption records, ticket consumption records, transportation fee consumption records and other consumption records; refining the five categories of consumption information into secondary subcategories according to the different levels of each category of consumption information and the different applicable consumer groups to obtain detailed records of tourist consumption types; counting the detailed records of tourist consumption types according to the number of times the tourists consume, removing the detailed records of tourist consumption types that are less than 10% of the number of times the tourists consume, to obtain the records of tourist consumption types.

[0016] Preferably, the step of obtaining a consumption item-consumption heat curve diagram based on the consumption type records of tourists according to the historical consumption times of tourists includes: establishing the consumption item-consumption heat curve diagram based on the consumption type records of tourists according to the historical consumption times of tourists; if the consumption heat of the consumption item in the consumption item-consumption heat curve diagram exceeds 80% of the historical consumption times of tourists, the consumption item is listed as a must-have consumption item for tourists; if the consumption heat of the consumption item in the consumption item-consumption heat curve diagram exceeds 50% of the historical consumption times of tourists, the consumption item is listed as a recommended consumption item for tourists; if the consumption heat of the consumption item in the consumption item-consumption heat curve diagram is lower than 30% of the historical consumption times of tourists, the consumption item is listed as a consumption item not recommended for tourists.

[0017] Preferably, the step of collecting tourists' travel plans in real time and matching the consumption item-consumption heat curve according to the tourists' travel plans to obtain a tourist-exclusive planned consumption curve includes: collecting tourists' travel plans in real time, specifically collecting tourists' travel budgets, intended consumption items, travel departure places, travel time and duration, number of people traveling, target number of companions, and target requirements for companions; matching the consumption item-consumption heat curve that meets the requirements according to the tourists' travel budgets and intended consumption items; if there are completely overlapping consumption item-consumption heat curves, marking the consumption item-consumption heat curve as a tourist-exclusive planned consumption curve; if there are no completely overlapping consumption item-consumption heat curves, selecting the nearest consumption item point in the non-overlapping consumption item column and connecting it with other overlapping consumption item-consumption heat curves to obtain a tourist-exclusive planned consumption curve.

[0018] Preferably, the step of matching the tourist-exclusive planned consumption curves of different tourists and the tourists' travel plans to obtain a tourist group with a high degree of matching includes: matching the tourist-exclusive planned consumption curves of different tourists, matching them from high to low according to the degree of overlap of the tourist-exclusive planned consumption curves, and obtaining a tourist-exclusive companion matching ranking table; screening tourists with high companion matching and the number of tourists in the tourist-exclusive companion matching ranking table according to the tourist's travel plan, including the travel departure place, travel time and duration, number of tourists, target number of companions, and companion target requirements, to obtain a tourist group with a high degree of matching.

[0019] Preferably, the tourist-exclusive companion matching ranking table includes: basic personal information of tourists, the tourist-exclusive planned consumption curve, the overlap of the tourist-exclusive planned consumption curves of the matching tourists and the matched tourists, the tourist's travel departure place, travel time and duration, the number of tourists traveling, the target number of companions, and the companion target requirements.

[0020] Preferably, the step of pairing the highly matched tourist groups according to the different companion needs of different tourists to obtain a tourist travel companion plan includes: performing two-way travel pairing among the highly matched tourist groups, and performing two-way travel pairing according to the tourist travel plans; if the number of travel companions does not reach the target number of travel companions after the two-way travel pairing, collecting the needs of the matched tourists and determining whether the matched tourists need to continue traveling together; if the matched tourists need to continue traveling together, determining the necessary consumption items of the tourists, the recommended consumption items of the tourists and the travel companions in the consumption item-consumption heat curve of the matched tourists. The overlap between the consumption items not recommended by the tourist and the corresponding consumption items of the matched tourist is judged. If the overlap is greater than 80%, the companionship requirement is met, and a travel companionship is carried out to obtain the tourist travel companionship plan; if the matched tourist needs to continue to travel together, the necessary consumption items of the tourist, the recommended consumption items of the tourist and the consumption items not recommended by the tourist in the consumption item-consumption heat curve diagram of the matched tourist are less than 80% overlap with the corresponding consumption items of the matched tourist, then a secondary pairing is carried out to obtain the tourist travel companionship plan; if the matched tourist does not need to continue to travel together, the travel companionship process is completed to obtain the tourist travel companionship plan.

[0021] Preferably, the secondary pairing step includes: judging the overlap between the essential consumption items of the tourists and the recommended consumption items of the tourists in the consumption item-consumption heat curve diagram of the matched tourists and the corresponding consumption items of the matched tourists, and whether the overlap is greater than 80%; if the overlap of the essential consumption items of the tourists, the recommended consumption items of the tourists and the corresponding consumption items of the matched tourists is greater than 80%, then the pairing requirement is met, and a travel pairing is carried out to obtain the travel pairing plan for the tourists; if the overlap of the essential consumption items of the tourists, the recommended consumption items of the tourists and the corresponding consumption items of the matched tourists is not greater than 80%, then the overlap requirement is reduced to 70%, and then the overlap of the essential consumption items of the tourists, the recommended consumption items of the tourists and the corresponding consumption items of the matched tourists is judged, until the pairing requirement is met, a travel pairing is carried out, and the travel pairing plan for the tourists is obtained, and then the secondary pairing step is ended.

[0022] Preferably, the step of dynamically adjusting the tourist travel companion plan according to changes in tourist information updates includes: after the tourist travel companion plan is formulated, adjusting it according to changes in tourist information updates before the departure of the trip; formulating the tourist travel companion plan in real time and updating the tourist travel companion plan according to changes in the number of tourists.

[0023] The beneficial effects of the present invention are as follows: the present invention collects consumption record information of historical tourists, classifies the consumption records into multiple levels, obtains records of tourist consumption types, obtains a consumption item-consumption heat curve according to the number of historical tourist consumption, and screens the items with consumption value in the tourist scenic spot according to the heat of the consumption items, thereby improving the consumption value of tourists and improving the tourist experience; according to the consumption budget of tourists and the consumption item-consumption heat curve, a list of consumption items is compiled for tourists, which is more ideal for the selection of tourist travel companions, enables tourists with similar consumption levels to complete travel companions, and improves the satisfaction of travel companions; based on the consumption item-consumption heat curve, tourist consumption items with lower consumption heat are removed, thereby allowing tourists to avoid pitfalls and improve the tourist travel value; dynamic adjustments are made according to the update changes of tourist information, thereby minimizing the impact of changes in tourists' travel plans on travel companions. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for the specific embodiments or the description of the prior art. In all the drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn according to the actual scale.

[0025] Figure 1 It is a flow chart of a travel companion method based on big data provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0026] In order to make the technical personnel in the technical field better understand the scheme of the present invention, the technical scheme in the embodiment of the present invention will be clearly and completely described below in combination with the drawings in the embodiment of the present invention. Obviously, the described embodiment is only a part of the embodiment of the present invention, not all the embodiments. Based on the embodiment of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0027] The terms "first", "second", etc. in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish different objects rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, device, product or end including a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units that are not listed, or may optionally include other steps or units inherent to these processes, methods, products or ends.

[0028] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present invention. The appearance of the phrase in various places in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0029] At present, more and more people are starting to travel together, but now many people want to travel but have no companions, and it is difficult to find travel companions with a suitable travel budget, travel time and duration. Now tourists who want to travel together can only do so by making an appointment with friends or joining a tour group, but the tour group experience is generally not good and not very free, so it is necessary to bring together tourists with the same travel intentions and travel budgets.

[0030] The present invention is intended to provide a travel companion method based on big data to solve the problems that it is difficult for tourists to find like-minded travel companions, the different consumption concepts and levels of travel companions lead to a bad travel experience, and group travel is not free.

[0031] The specific implementation of the present invention provides a travel companion method based on big data, the method is as follows Figure 1 As shown, the following steps are included:

[0032] S1: Collect and update historical tourists’ travel consumption information in real time.

[0033] In an embodiment of the present invention, the travel consumption information of historical tourists is all consumption records of the historical tourists related to the travel itinerary from the start of the travel itinerary to the end of the travel itinerary, specifically including: accommodation consumption records, food consumption records, ticket consumption records, transportation fee consumption records and other consumption records.

[0034] S2: Classify the consumption records according to the consumption types in the historical tourists' travel information to obtain the tourists' consumption type records.

[0035] In an embodiment of the present invention, the travel consumption information of historical tourists is divided into five categories of consumption information according to accommodation consumption records, food consumption records, ticket consumption records, transportation fee consumption records and other consumption records; the five categories of consumption information are refined and divided into subcategories according to the different levels of each type of consumption information and the different applicable consumer groups to obtain detailed type records of tourist consumption; the detailed type records of tourist consumption are counted according to the number of tourist consumption times, and the detailed type records of tourist consumption that are less than 10% of the number of tourist consumption times are removed to obtain tourist consumption type records.

[0036] S3: Record the tourists’ consumption types according to the historical tourists’ consumption times to obtain a consumption item-consumption heat curve.

[0037] In an embodiment of the present invention, a consumption item-consumption heat curve is established based on the records of tourist consumption types according to the historical tourist consumption times; if the consumption heat of a consumption item in the consumption item-consumption heat curve exceeds 80% of the historical tourist consumption times, the consumption item is listed as a necessary consumption item for tourists; if the consumption heat of a consumption item in the consumption item-consumption heat curve exceeds 50% of the historical tourist consumption times, the consumption item is listed as a recommended consumption item for tourists; if the consumption heat of a consumption item in the consumption item-consumption heat curve is lower than 30% of the historical tourist consumption times, the consumption item is listed as a consumption item not recommended for tourists.

[0038] S4: Collect tourists’ travel plans in real time, and match consumption items-consumption heat curves according to tourists’ travel plans to obtain tourists’ exclusive planned consumption curves.

[0039] In an embodiment of the present invention, the travel plans of tourists are collected in real time, specifically, the travel budgets, intended consumption items, travel departure places, travel time and duration, number of people traveling, target number of companions, and target requirements for companions are collected; according to the travel budgets and intended consumption items of tourists, matching consumption item-consumption heat curves that meet the requirements are performed; if there are completely overlapping consumption item-consumption heat curves, the consumption item-consumption heat curves are marked as the tourist-exclusive planned consumption curve; if there are no completely overlapping consumption item-consumption heat curves, the nearest consumption item point in the non-overlapping consumption item column is selected and connected with other overlapping consumption item-consumption heat curves to obtain the tourist-exclusive planned consumption curve.

[0040] S5: Match the exclusive planned consumption curves of different tourists and the travel plans of tourists to obtain a highly matched tourist group.

[0041] In an embodiment of the present invention, tourist-exclusive planned consumption curves of different tourists are matched, and the matching is performed from high to low according to the overlap of the tourist-exclusive planned consumption curves to obtain a tourist-exclusive companion matching ranking table; according to the tourist's travel plan, the travel departure place, travel time and duration, number of tourists, target number of companions, and companion target requirements, the tourists with high companion matching and the number of tourists are screened in the tourist-exclusive companion matching ranking table to obtain a high-matching tourist group; the tourist-exclusive companion matching ranking table includes: basic personal information of tourists, tourist-exclusive planned consumption curves, overlap of tourist-exclusive planned consumption curves of matching tourists and matched tourists, tourist's travel departure place, travel time and duration, number of tourists, target number of companions, and companion target requirements.

[0042] S6: According to the different travel companion needs of different tourists, the tourist groups with high matching degree are paired up to obtain the tourist travel companion plan.

[0043] In an embodiment of the present invention, two-way travel pairing is performed among a group of tourists with a high matching degree, and two-way travel pairing is performed according to the tourists' travel plans; if after the two-way travel pairing, the number of travel companions does not reach the target number of travel companions, the needs of the matching tourists are collected to determine whether the matching tourists need to continue to pair up; if the matching tourists need to continue to pair up, the degree of overlap between the consumption items of the matched tourists and the necessary consumption items of the tourists, the recommended consumption items of the tourists, and the consumption items that the tourists do not recommend in the consumption heat curve diagram and the corresponding consumption items of the matching tourists is determined, and if the overlap is greater than 80%, the pairing requirements are met, and travel pairing is performed to obtain a travel pairing plan for the tourists; if the matching tourists need to continue to pair up, and the degree of overlap between the necessary consumption items of the tourists, the recommended consumption items of the tourists, and the consumption items that the tourists do not recommend in the consumption heat curve diagram of the matched tourists and the corresponding consumption items of the matching tourists is less than 80%, then secondary pairing is performed to obtain a travel pairing plan for the tourists. If the matched tourists do not need to continue to travel together, the travel companion process is completed and the tourist travel companion plan is obtained; the second-level companion matching step includes: judging the overlap between the tourist's essential consumption items and the tourist's recommended consumption items in the consumption heat curve of the matched tourists and the corresponding consumption items of the matched tourists, and whether the overlap is greater than 80%; if the overlap between the tourist's essential consumption items and the tourist's recommended consumption items and the corresponding consumption items of the matched tourists is greater than 80%, the companionship requirement is met, and the travel companionship is carried out to obtain the tourist travel companion plan; if the overlap between the tourist's essential consumption items and the tourist's recommended consumption items and the corresponding consumption items of the matched tourists is not greater than 80%, the overlap requirement is reduced to 70%, and the overlap between the tourist's essential consumption items and the tourist's recommended consumption items and the corresponding consumption items of the matched tourists is judged again, until the companionship requirement is met, the travel companionship is carried out, and the tourist travel companion plan is obtained, and the second-level companion matching step is ended.

[0044] S7: Dynamically adjust the tourist travel companion plan according to the updated changes in tourist information.

[0045] In the embodiment of the present invention, after the tourist travel companion plan is formulated, it is adjusted according to the information update changes of the tourists before the travel; according to the increase or decrease in the number of tourists, the tourist travel companion plan is formulated and updated in real time.

[0046] The beneficial effects of the present invention are as follows: the present invention collects consumption record information of historical tourists, classifies the consumption records into multiple levels, obtains records of tourist consumption types, obtains a consumption item-consumption heat curve according to the number of historical tourist consumption, and screens the items with consumption value in the tourist scenic spot according to the heat of the consumption items, thereby improving the consumption value of tourists and improving the tourist experience; according to the consumption budget of tourists and the consumption item-consumption heat curve, a list of consumption items is compiled for tourists, which is more ideal for the selection of tourist travel companions, enables tourists with similar consumption levels to complete travel companions, and improves the satisfaction of travel companions; based on the consumption item-consumption heat curve, tourist consumption items with lower consumption heat are removed, thereby allowing tourists to avoid pitfalls and improve the tourist travel value; dynamic adjustments are made according to the update changes of tourist information, thereby minimizing the impact of changes in tourists' travel plans on travel companions.

[0047] The above is only an embodiment of the present invention, and the common knowledge such as the known specific technical solutions or characteristics in the solution is not described in detail here. It should be pointed out that for those skilled in the art, without departing from the solution of the present invention, several modifications and improvements can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the present invention and the practicality of the patent. The scope of protection required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. A travel companion method based on big data, characterized in that: The method comprises: S1: collect and update historical tourists’ travel consumption information in real time; S2: Classifying the consumption records according to the types of consumption in the historical tourist's travel information to obtain tourist consumption type records; S3: obtaining a consumption item-consumption heat curve chart based on the consumption type records of the tourists according to the historical consumption times of the tourists; S4: collecting tourists' travel plans in real time, and matching the consumption items-consumption heat curve according to the tourists' travel plans to obtain tourists' exclusive planned consumption curve; S5: Matching the tourist-specific planned consumption curves of different tourists and the tourist travel plans to obtain a high-matching tourist group; S6: Pairing the high-matching tourist groups according to the different travel companion needs of different tourists to obtain a travel companion plan for tourists; S7: Dynamically adjust the tourist travel companion plan according to the updated changes in the tourist information.

2. A travel companion method based on big data according to claim 1, characterized in that: The travel consumption information of historical tourists refers to all consumption records of historical tourists related to the travel itinerary from the start to the end of the travel itinerary, specifically including: accommodation consumption records, food consumption records, ticket consumption records, transportation fee consumption records and other consumption records.

3. A travel companion method based on big data according to claim 2, characterized in that: The step of classifying the consumption records according to the types of consumption in the historical tourist's travel information to obtain the tourist's consumption type records includes: Dividing the historical tourists' travel consumption information into five categories of consumption information according to the accommodation consumption records, food consumption records, ticket consumption records, transportation expense consumption records and other consumption records; The five types of consumption information are divided into subcategories according to the different levels of each type of consumption information and the different applicable consumer groups, so as to obtain detailed records of tourist consumption types; The detailed type records of tourist consumption are counted according to the number of times of tourist consumption, and the detailed type records of tourist consumption that are less than 10% of the number of times of tourist consumption are removed to obtain the tourist consumption type records.

4. A travel companion method based on big data according to claim 2, characterized in that: The step of obtaining a consumption item-consumption heat curve chart based on the consumption type records of the tourists according to the historical consumption times of the tourists includes: The consumption item-consumption heat curve is established based on the consumption type records of the tourists according to the historical consumption times of the tourists; If the consumption heat of the consumption item in the consumption item-consumption heat curve exceeds 80% of the historical consumption times of tourists, the consumption item will be listed as a must-have consumption item for tourists; If the consumption heat of the consumption item in the consumption item-consumption heat curve exceeds 50% of the historical consumption times of tourists, the consumption item is listed as a consumption item recommended by tourists; If the consumption heat of the consumption item in the consumption item-consumption heat curve is lower than 30% of the historical consumption times of tourists, the consumption item will be listed as a consumption item not recommended for tourists.

5. A travel companion method based on big data according to claim 4, characterized in that: The step of collecting tourists' travel plans in real time and matching the consumption item-consumption heat curve according to the tourists' travel plans to obtain a tourists' exclusive planned consumption curve includes: Collect tourists' travel plans in real time, specifically collecting tourists' travel budget, intended consumption items, travel departure place, travel time and duration, number of tourists, number of companions, and companion target requirements; Matching the consumption items-consumption heat curve that meet the requirements according to the tourist's travel budget and intended consumption items; If there is a completely overlapping consumption item-consumption heat curve, the consumption item-consumption heat curve is marked as a tourist-exclusive planned consumption curve; If there is no completely overlapping consumption item-consumption heat curve, the nearest consumption item point in the non-overlapping consumption item column is selected and connected with other overlapping consumption item-consumption heat curves to obtain a tourist-specific planned consumption curve.

6. A travel companion method based on big data according to claim 5, characterized in that: The step of matching the tourist-specific planned consumption curves of different tourists with the tourist travel plans to obtain a high-matching tourist group includes: Matching the tourist-exclusive planned consumption curves of different tourists, matching them from high to low according to the overlap of the tourist-exclusive planned consumption curves, and obtaining a tourist-exclusive companion matching ranking table; According to the tourist's travel plan, the travel departure place, travel time and duration, number of tourists, target number of companions, and companion target requirements, the tourists with high companion matching and the number of tourists are screened in the tourist-exclusive companion matching ranking table to obtain a high-matching tourist group.

7. A travel companion method based on big data according to claim 6, characterized in that: The tourist-exclusive companion matching ranking table includes: basic personal information of tourists, the tourist-exclusive planned consumption curve, the overlap of the tourist-exclusive planned consumption curves of matching tourists and matched tourists, the tourist's travel departure place, travel time and duration, the number of tourists traveling, the target number of companions, and the companion target requirements.

8. A travel companion method based on big data according to claim 5, characterized in that: The step of pairing the high-matching tourist groups according to the different companion needs of different tourists to obtain a tourist travel companion plan includes: Performing two-way travel pairing among the high-matching tourist group, and performing two-way travel pairing according to the tourist's travel plan; If after two-way travel pairing, the number of travel companions does not reach the target number of travel companions, then collect the needs of matching tourists and whether the matching tourists need to continue to pair up; If the matched tourist needs to continue traveling together, the necessary consumption items of the tourist, the recommended consumption items of the tourist and the non-recommended consumption items of the tourist in the consumption item-consumption heat curve of the matched tourist are judged to be coincident with the corresponding consumption items of the matched tourist. If the coincidence is greater than 80%, the travel companion requirement is met, and the travel companion is carried out to obtain the travel companion plan of the tourist; If the matched tourists need to continue traveling together, and the overlap between the necessary consumption items of the tourists, the recommended consumption items of the tourists and the consumption items not recommended by the tourists in the consumption items-consumption heat curve of the matched tourists and the corresponding consumption items of the matched tourists is less than 80%, then secondary pairing is performed to obtain the tourist travel companion plan; If the matched tourists do not need to continue traveling together, the travel companion process is completed and the travel companion plan for the tourists is obtained.

9. A travel companion method based on big data according to claim 8, characterized in that: The step of secondary pairing includes: Determine the overlap between the must-have consumption items of the tourists in the consumption item-consumption heat curve of the matched tourists, the consumption items recommended by the tourists and the corresponding consumption items of the matched tourists, and whether the overlap is greater than 80%; If the overlap between the essential consumption items of the tourists, the consumption items recommended by the tourists and the corresponding consumption items of the matching tourists is greater than 80%, the companionship requirement is met, and a travel companionship plan for the tourists is obtained; If the overlap of the essential consumption items for tourists, the recommended consumption items for tourists and the corresponding consumption items of the matched tourists is not greater than 80%, the overlap requirement will be reduced to 70%, and the overlap of the essential consumption items for tourists, the recommended consumption items for tourists and the corresponding consumption items of the matched tourists will be judged again until the companionship requirements are met, and travel companionship is carried out to obtain the travel companionship plan for the tourists, and the secondary companionship pairing step is ended.

10. A travel companion method based on big data according to claim 1, characterized in that: The step of dynamically adjusting the tourist travel companion plan according to the updated changes of tourist information includes: After the tourist travel companion plan is formulated, it is adjusted according to the tourist's information update before the travel; According to the increase or decrease in the number of tourists, the tourist travel companion plan is formulated and updated in real time.

Images