A new energy vehicle service station recommendation method and system, and storage medium

Abstract

The present invention belongs to the field of intelligent recommendation technology and discloses a method and system for recommending new energy vehicle service sites, as well as a storage medium. The method includes: obtaining a ratio A:B between a user's attention to the distance to a service site and the quality of service to form a user profile; obtaining the urgency of the service; allocating weights to recommendation indicators based on the user profile and the urgency of the service; obtaining related services of the service based on the service name; scoring service sites that provide the user's required service based on the recommendation indicators, and recommending the service sites to the user based on the scores; and modifying the user profile based on the user's rating of the service site after receiving the service and the user's acceptance of the recommended service site. The present invention not only meets the user's demand for a single service, but also creates a potential consumption environment, expands the scope of services, satisfies the user's needs to a greater extent, and embodies the advantages of a comprehensive service site.

Description

[0001] Divisional application

[0002] This application is a divisional application of the Chinese invention patent application [Application Number: 2024109786475] [Name: A method and system for recommending new energy vehicle service stations, and storage medium] filed on July 19, 2024. Technical Field

[0003] The present invention relates to the field of intelligent recommendation technology, and in particular to a new energy vehicle service site recommendation method and system, and a storage medium. Background Art

[0004] With the development of new energy and information technologies, new energy vehicles are characterized by "electrification, intelligence, and sharing." Electrification is the vehicle for future automotive industry development, primarily referring to new energy vehicle powertrains and transforming vehicle energy propulsion. Intelligence is the technological prerequisite for future automotive industry development, primarily focusing on autonomous driving and connected vehicle technologies. Sharing is the social model and value vehicle, primarily referring to car sharing and mobility. These three characteristics are driving increasing consumer demand for intelligent and convenient after-sales service for new energy vehicles.

[0005] Compared to traditional fuel vehicles, new energy vehicles require anywhere from tens of minutes to several hours to recharge due to the characteristics of their batteries. To effectively utilize the time waiting for charging, new energy vehicle owners engage in other activities such as leisure and shopping, thus creating new business models. For new energy vehicle owners, service stations that simply offer charging and battery swapping services are no longer sufficient; instead, they require comprehensive service centers that offer a wide range of services. Of course, due to various limitations, not every service station can offer all the necessary features, so choosing the right service station for your needs is a pressing issue.

[0006] Prior art Chinese patent application CN202311753205.2 discloses a charging station recommendation method, charging station recommendation device, and charging station recommendation system. The recommendation method includes obtaining information about charging stations within a preset distance range, where the preset distance range is the range of the vehicle's remaining battery life; generating an operation score for the charging station based on the charging data of the charging station; generating an equipment score for the charging station based on the charging pile information of the charging station; generating a service score for the charging station based on the service information; generating a user evaluation score for the charging station based on user evaluation information; and sorting the charging stations based on the operation score, equipment score, service score, and user evaluation score, generating a ranking result for the charging stations, and recommending the ranking result to the user.

[0007] For another example, the prior art Chinese patent application CN202111673428.9, "Optimization method and device for battery swap station recommendation method," includes the following steps: executing the battery swap station recommendation method and sending recommended battery swap station information to the user group; obtaining the feedback behavior of the user group regarding the recommended battery swap station information; dividing the user group into valid recommended users and invalid recommended users based on whether the feedback behavior meets a preset condition; and optimizing the battery swap station recommendation method based on the proportion of valid recommended users in the user group. The present invention optimizes the battery swap station recommendation method based on the proportion of valid recommended users in the user group, so that a closed loop can be formed between the recommended battery swap station and the user's feedback based on the recommended battery swap station, thereby enabling the recommended battery swap station to better meet the user's battery swap needs and improving the effectiveness of the recommendation. This also achieves the optimization of the battery swap station recommendation method and enhances the user experience of the battery swap process.

[0008] In the above-mentioned existing technologies, the recommendation process is mainly centered around charging or battery replacement, and the main evaluation indicators are also charging-related equipment, prices, services, evaluations, etc., which do not take into account the comprehensive needs of users and do not conform to the current positioning of comprehensive service stations. Summary of the Invention

[0009] The purpose of the present invention is to provide a new energy vehicle service station recommendation method and system, and storage medium, which partially solve or alleviate the above-mentioned deficiencies in the prior art and can recommend the most suitable service station based on the comprehensive needs of the user.

[0010] In order to solve the above-mentioned technical problems, the present invention specifically adopts the following technical solutions:

[0011] A method for recommending new energy vehicle service stations, comprising:

[0012] Obtain the ratio A:B of users' attention to the distance to the service site and service quality to form a user profile;

[0013] Obtain the service name of the service required by the user based on the search keyword entered by the user, and collect the geographical location of the user when entering the search keyword;

[0014] Based on the urgency of obtaining services required by users;

[0015] Assign weights to recommendation indicators based on user profile and service urgency; the recommendation indicators include distance weight, service quality weight, and associated service weight;

[0016] Get the associated services of the service according to the service name;

[0017] Based on the geographical location of the user when entering the search keyword, the service site with the service required by the user is searched within the threshold range;

[0018] Scoring service sites that provide services required by users based on recommendation indicators, and recommending service sites to users based on the scores;

[0019] Modify the user profile based on the user's rating of the service site after receiving the service and the acceptance of the recommended service site;

[0020] The steps of obtaining services according to the urgency of the services required by the user include:

[0021] Classify services and categorize their urgency into levels one to three based on the type of service;

[0022] When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, and D1+S1=1;

[0023] When the urgency is at the second level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, and D2+S2=1;

[0024] When the urgency is at the third level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, and D3+S3=1;

[0025] The steps to assign weights to recommendation indicators based on user profile and service urgency include:

[0026] Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1;

[0027] When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0;

[0028] When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0;

[0029] When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; and the adjusted associated service weight C = C0.

[0030] As an improvement, the method for obtaining the ratio between the user's attention to the distance to the service site and the service quality includes:

[0031] When a user registers, a progress bar is displayed on the user registration page; one end of the progress bar is the distance, and the other end is the service quality; a slider that can slide along the progress bar is provided on the progress bar; the user changes the ratio between the distance end and the service quality end by dragging the slider, and the sum of the distance end ratio and the service quality end ratio is a constant value.

[0032] As an improvement, the method for obtaining the associated services of a service based on the service name includes:

[0033] If the service required by the user is a service that the user has historically received, other services that were performed simultaneously when the user historically received the service are considered as associated services;

[0034] In the case that the service required by the user is a service that the user has never received, a related service is selected according to the service related map.

[0035] As a further improvement, the service association graph uses services as nodes and relationships between services as edges;

[0036] The user's required services are selected in the service association graph, and services directly connected to the user's required services or / and services indirectly connected through edges less than a threshold number are taken as associated services.

[0037] As an improvement, the steps of scoring the service sites having the services required by the user according to the recommendation indicators include:

[0038] Obtain the distance between the service site and the user, and score the distance score based on the adjusted distance weight;

[0039] Obtain individual evaluations of services required by users at the service site and a comprehensive evaluation of the service site, and score them based on the adjusted service quality weights to obtain a service quality score;

[0040] Obtain the number of associated services included in the service site, and score the associated services according to the adjusted associated service weights to obtain associated service scores;

[0041] The sum of the distance score, service quality score, and associated service score is used as the score of the service site.

[0042] As an improvement, the rating ratio of the single evaluation of the service required by the user in the service site and the comprehensive evaluation of the service site is K1:K2, where K1>K2.

[0043] As an improvement, the steps of recommending service sites to users based on the ratings include:

[0044] Sort all service sites in descending order according to their scores, and recommend service sites with a ranking higher than the ranking threshold to users; or

[0045] The service sites with scores higher than the score threshold are recommended to the user.

[0046] As an improvement, the steps of modifying the user profile based on the user's rating of the service site after receiving the service and the user's acceptance of the recommended service site include:

[0047] When the number of times a user does not accept a recommended merchant exceeds a threshold, the user profile is adjusted; the adjustment method includes:

[0048] Compare the user's average score A1 for service quality with the average score A2 for service quality of all other users. When A1 is less than A2, increase the service quality weight by a first percentage; when A1 is greater than or equal to A2 and A1 is not a full score, increase the service quality weight by a second percentage; when A1 is a full score, reduce the service quality weight by a third percentage; wherein the first percentage is greater than the second percentage.

[0049] The present invention also provides a new energy vehicle service station recommendation system, comprising:

[0050] User portrait construction module: the ratio A:B between the user's attention to the distance to the service site and the service quality is obtained to form a user portrait;

[0051] The urgency acquisition module is used to obtain the service name of the service required by the user based on the search keyword entered by the user, and collect the geographical location of the user when entering the search keyword; and obtain the urgency of the service based on the service required by the user;

[0052] A weight allocation module is used to allocate weights to recommendation indicators based on user profiles and service urgency; the recommendation indicators include distance weight, service quality weight, and associated service weight;

[0053] The recommendation module is used to obtain related services of a service based on the service name; query service sites within a threshold range that provide the user's required service based on the user's geographical location when the user enters the keyword; score the service sites that provide the user's required service based on the recommendation index, and recommend service sites to the user based on the score;

[0054] A user portrait correction module is used to correct the user portrait based on the user's rating of the service site after receiving the service and the user's acceptance of the recommended service site;

[0055] The urgency acquisition module specifically includes:

[0056] Classify services and categorize their urgency into levels one to three based on the type of service;

[0057] When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, and D1+S1=1;

[0058] When the urgency is at the second level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, and D2+S2=1;

[0059] When the urgency is at the third level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, and D3+S3=1;

[0060] The weight allocation module allocates the weights of the recommendation indicators according to the user profile and the urgency of the service, specifically including:

[0061] Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1;

[0062] When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0;

[0063] When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0;

[0064] When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; and the adjusted associated service weight C = C0.

[0065] The present invention also provides a storage medium, in which a computer program is stored; when the computer program is executed, the above-mentioned new energy vehicle service station recommendation method can be implemented.

[0066] The present invention is beneficial in that:

[0067] As mentioned above, the existing technologies are more targeted at sites that provide single charging services or battery swapping services, and users usually recommend sites based solely on the charging or battery swapping rating of a battery swapping site or charging site, without considering service sites that can provide comprehensive services (for example, other services in addition to charging or battery swapping services). With the improvement of living standards, people are paying more and more attention to comprehensive services. Although service sites can be scored and even recommended on various platforms, these are all comprehensive ratings of sites. If the ranking and recommendation are simply based on the comprehensive rating of a certain site in the existing technology, users will have no choice, or the user experience will be poor after blindly choosing. For example, you choose a service site with the highest comprehensive rating, but in fact the service quality of the service required by the user may be poor, or it may not be able to provide the related services that the user expects.

[0068] The present invention first constructs a user profile to express the user's preference for distance and service quality. It then uses the user's search keywords to determine the user's desired services and their urgency. Using the user profile as a starting point, the system then assigns weights to recommendation indicators in the scoring system, using urgency as an adjustment factor. Each service site is then scored based on the recommendation indicators to recommend suitable service sites to the user. The system recommends a suitable service site based on the urgency of the user's desired service (i.e., the type of service specified by the user), along with a comprehensive consideration of distance, service quality, and related services (derived from user history data). This eliminates the problem of users being overwhelmed by the vast number of service sites. Furthermore, compared to existing methods that unilaterally consider charging services, this approach ignores the fact that people often consider one or more other services simultaneously when receiving a single service at a service site. For example, while charging, they may also consider post-charging maintenance or car washing, while waiting to charge, and other services such as coffee or beverages. Therefore, to provide comprehensive service, related services to the user's desired service are also considered as a recommendation indicator.

[0069] The present invention also uses the user's input of a desired service to obtain services related to that service, and then comprehensively scores all service sites within the range based on distance and service quality. This not only satisfies the user's needs for a single service, but also creates a potential consumption environment, expands the scope of services, and satisfies user needs to a greater extent, demonstrating the advantages of comprehensive service sites.

[0070] This invention does not rely on artificial intelligence models, nor on chips or significant computing power. Against the backdrop of increasingly tense international situations, it better meets the needs of the times. Despite lacking AI support, the invention can still accurately predict user needs and recommend the most suitable service sites. It can also self-correct based on user feedback (for example, whether the user accepts the recommended service site), gradually improving itself to better reflect the user's needs.

[0071] In addition, the present invention uses the progress bar and slider modes to obtain users' attention to logistics speed and quality, which is more easily accepted by users. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] In order to more clearly illustrate the 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 embodiments or the description of the prior art. In all drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the various elements or parts are not necessarily drawn according to the actual scale. Obviously, the drawings described below are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can also be obtained based on these drawings without inventive work.

[0073] Figure 1 This is a flow chart of a method for recommending new energy vehicle service stations according to an embodiment of the present invention;

[0074] Figure 2 This is a structural diagram of a new energy vehicle service station recommendation system according to an embodiment of the present invention. DETAILED DESCRIPTION

[0075] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0076] Herein, suffixes such as "module," "component," or "unit" used to represent elements are only used to facilitate description of the present invention and have no specific meaning. Therefore, "module," "component," or "unit" may be used interchangeably.

[0077] As used herein, terms such as "upper," "lower," "inner," "outer," "front," "back," "one end," and "the other end" indicate positions or locations based on those shown in the accompanying drawings. These terms are intended solely to facilitate and simplify the description of the present invention and are not intended to indicate or imply that the devices or components referred to must have, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0078] As used herein, unless otherwise expressly specified or limited, the terms "installed," "provided with," and "connected" should be understood broadly. For example, "connected" may refer to a fixed connection, a detachable connection, or an integral connection; it may refer to a mechanical connection, a direct connection, an indirect connection via an intermediate medium, or internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention on a case-by-case basis.

[0079] As used herein, "and / or" includes any and all combinations of one or more of the associated listed items.

[0080] Herein, "plurality" means two or more than two, ie, it includes two, three, four, five, etc.

[0081] Example 1

[0082] like Figure 1 As shown, the present invention provides a method for recommending new energy vehicle service sites. The method is triggered based on the search keywords input by the user and recommends comprehensive service sites that include the services the user needs, thereby improving the user experience while inducing user consumption to form a new business model. The specific steps include:

[0083] S101 obtains the ratio A:B between the user's attention to the distance to the service site and the service quality, and forms a user profile.

[0084] A comprehensive service station should include core services related to new energy vehicles as well as peripheral services relevant to vehicle owners. Core services include charging, battery replacement, repair, and maintenance, while peripheral services include dining, entertainment, shopping, and leisure. Therefore, when recommending service stations to vehicle owners, it's also necessary to explore their other needs.

[0085] For new energy vehicle owners, of course, the focus is on the core services they need. Only when these core services are met will they consider surrounding services. Regarding core services, the proximity to service stations and service quality are the primary considerations for new energy vehicle owners.

[0086] Based on this, in order to more accurately recommend service sites to users, this embodiment first needs to obtain the user's attention to the distance to the service site and the service quality. In order to better express the difference between the attention to distance and service quality, this embodiment uses a ratio to quantify the attention to the two.

[0087] In practical applications, there are various ways to obtain the ratio of users' attention to the distance to a service station and the service quality. However, existing methods either require filling in data or multiple clicks, which are both cumbersome. In today's fast-paced life, many users cannot patiently input the required information.

[0088] In order to solve this problem, in this implementation, when a user registers, a progress bar is displayed on the user registration page; one end of the progress bar is the distance, and the other end is the service quality; a slider that can slide along the progress bar is provided on the progress bar; the user changes the ratio between the distance end and the service quality end by dragging the slider, and the sum of the distance end ratio and the service quality end ratio is a constant value, that is, the sum of the distance end ratio and the service quality end ratio is fixed.

[0089] As the user drags the slider, the scale changes simultaneously at both ends. For example, initially, when the slider is in the middle, the scale at both the distance and quality of service ends is 50%. As the user drags the slider toward the distance, the distance ends become shorter, and the scale decreases; while the quality of service ends become longer, and the scale increases.

[0090] The above method is very convenient and intuitive when inputting different ratios, which is easy for users to use and also makes it easier to obtain data in the background.

[0091] Of course, it is possible that some users are still unwilling to provide the ratio between their concerns about distance and service quality. In this case, it is only necessary to directly match a default template for such users.

[0092] S102 obtains the service name of the service required by the user according to the search keyword input by the user, and collects the geographical location of the user when the search keyword is input.

[0093] When users need a certain service, they will enter keywords in the system to obtain it, such as charging, tire changing, maintenance, etc. When the system obtains the keywords entered by the user, it also obtains the user's geographic location.

[0094] S103 obtains the service according to the urgency of the service required by the user.

[0095] Based on the service keywords entered by the user, we can roughly determine the urgency of the service they need. For example, a tire change is often an emergency (i.e., the first level), requiring immediate repair. Therefore, a distant service station is unlikely to be chosen. In other words, users prioritize distance. For services like car washing (the second level), since they don't impact driving safety and don't require immediate completion, and the wait time isn't long, users are more likely to choose a more distant service station with better service quality (i.e., a better user experience). In other words, users prioritize service quality, and the distance weight can be appropriately lowered. For maintenance and film coating (the third level), since they don't impact driving safety and don't require immediate completion, and the wait time is long, users are more likely to choose a more distant service station with better service quality and a wider range of supporting services, such as leisure and entertainment. In other words, comprehensive services are preferred over nearby service stations. In other words, users prioritize service quality, and the distance weight can be appropriately lowered accordingly.

[0096] Based on this, in this embodiment, services (mainly core services) are classified, and the urgency of services is divided into levels one to three according to the service type;

[0097] When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, D1+S1=1; preferably, D1>S1

[0098] When the urgency is at the second level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, D2+S2=1; preferably, D1>D2;

[0099] When the urgency is at the third level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, D3+S3=1, preferably, D2>D3.

[0100] For example, in some embodiments, the urgency of the "charging" service may be ranked first. In this case, the distance weight adjustment coefficient may be set to 0.8, and the service quality weight adjustment coefficient may be adjusted to 0.2.

[0101] S104 allocates weights to recommendation indicators based on user portraits and service urgency.

[0102] In some embodiments, the recommendation index includes a distance weight, a service quality weight, and an associated service weight.

[0103] In this embodiment, the step of allocating weights to the recommendation indicators specifically includes:

[0104] S1401 initializes the weights of the recommendation indicators and assigns an initial weight to each recommendation indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1.

[0105] In order to avoid the user not providing the ratio between the degree of concern for distance and service quality, this embodiment directly matches a default template for this type of user. This step can also use this template when initializing the user.

[0106] For example, initially, the distance weight is 40%, the service quality weight is 40%, and the associated service weight is 20%.

[0107] In step S1402 , when the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; and the adjusted associated service weight C = C0.

[0108] S1403: When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; and the adjusted associated service weight C = C0.

[0109] In step S1404 , when the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; and the adjusted associated service weight C = C0.

[0110] If the ratio of users' concerns about distance and service quality obtained based on user portraits is 60%:40%, and the distance weight adjustment coefficient of the first tier is D1=0.8, and the service quality weight adjustment coefficient is S1=0.2, then according to the above formula, the adjusted weights are 68.6% for distance, 11.4% for service quality, and 20% for related services.

[0111] S105 obtains the associated services of the service according to the service name.

[0112] The steps for obtaining associated services in this step include:

[0113] S1051: If the service required by the user is a service that the user has received in the past, other services that were performed simultaneously when the user received the same service in the past are considered as related services.

[0114] For example, if the user had a cup of coffee at the service station cafe and bought a pack of cigarettes at the service station's mini-mart during their last charging session, the coffee and cigarette sales services would be considered associated services when selecting the charging service this time.

[0115] S1052: When the service required by the user is a service that the user has never received, a related service is selected according to the service related map.

[0116] Another situation is that the service required by the user this time is a service that the user has never received before. For example, the service required by the user this time is film pasting, but the user has no consumption record of film pasting at the service site before. In this case, the only option is to select the associated service based on the service association map.

[0117] In this embodiment, the service association graph is pre-built. It uses services as nodes and relationships between services as edges. A strong association is defined as a direct edge connection between one service and another. A weak association is defined as an indirect connection between one service and another, requiring an indirect connection through other services.

[0118] The service relationship graph is constructed based on the connections between services and consumer habits. For example, the connection between tire replacement and wheel repair is a service, while the connection between charging and cigarette sales is a consumer habit.

[0119] In this implementation, services required by the user are selected from the service association graph, and services that are directly connected (strongly associated) to the user's required services or / and services that are indirectly connected (weakly associated) through less than a threshold number of edges to the user's required services are used as associated services.

[0120] S106 searches for service sites within a threshold range that provide the service required by the user based on the geographical location of the user when the keyword is input.

[0121] When searching for service sites, the search is performed with a preset distance radius, centered on the user's geographic location when the keyword is entered. Of course, the preset distance can also be adjusted based on the user's focus on distance. The higher the user's focus on distance, the shorter the preset distance. Conversely, the lower the user's focus on distance, the longer the preset distance.

[0122] S107 scores the service sites that provide the services required by the user according to the recommendation index, and recommends the service sites to the user according to the scores.

[0123] Specifically, in this embodiment, the method for scoring service sites that provide services required by users according to recommendation indicators includes:

[0124] S1071 obtains the distance between the service site and the user, and scores the distance based on the adjusted distance weight to obtain a distance score.

[0125] For example, a distance of 0 between a service station and a user is defined as 100 points, and a maximum distance of 50 km is defined as 0 points. The distance score is then weighted using the distance weight. For example, if a service station is 5 km away and has a score of 90, the distance score after weighting by 60% is 54.

[0126] S1072 obtains the individual evaluations of the services required by the user in the service site and the comprehensive evaluation of the service site, and scores them according to the adjusted service quality weights to obtain the service quality score.

[0127] In this embodiment, the rating ratio of the single evaluation of the service required by the user in the service site and the comprehensive evaluation of the service site is K1:K2, where K1>K2.

[0128] For example, if a user's service score is 90 for a single item on a site, and the site's overall score is 80, then after adjusting the K1 / K2 ratio to 2:1, the score is 87. The service quality score, weighted by a service quality weight of 20%, is 17.4.

[0129] S1073 obtains the number of associated services included in the service site, and scores the associated services according to the adjusted associated service weights to obtain associated service scores.

[0130] If a service site contains all the related services required by the user, the score is 100, and none of them is 0. Then, when a service site contains all the related services, its score of 100 is weighted by the related service weight of 20%, and the related service score is 20.

[0131] S1074 uses the sum of the distance score, service quality score, and associated service score as the score of the service site.

[0132] The final score of the service site is obtained by adding up the above three scores, that is, 54+17.4+20=91.4.

[0133] This implementation provides two methods for recommending service sites to users based on ratings.

[0134] First, the service sites are sorted in descending order according to their scores, and service sites with a ranking higher than a threshold are recommended to users. For example, the top three service sites are recommended to users.

[0135] The second is to recommend service sites with scores higher than the score threshold to users, for example, recommending service sites with scores higher than 90 to users.

[0136] S108 modifies the user portrait based on the user's rating of the service site after receiving the service and the user's acceptance of the recommended service site.

[0137] In this implementation, after recommending service sites to users, the user profile can be modified based on user feedback, thereby achieving closed-loop management, specifically including:

[0138] When the number of times that the user does not accept the recommended service site exceeds a threshold, the method for adjusting the user profile includes:

[0139] Compare the user's average score A1 for service quality with the average score A2 for service quality of all other users. When A1 is less than A2, increase the service quality weight by a first percentage; when A1 is greater than or equal to A2 and A1 is not a full score, increase the service quality weight by a second percentage; when A1 is a full score, reduce the service quality weight by a third percentage; wherein the first percentage is greater than the second percentage.

[0140] For example, when a user does not select a service site recommended by the system three times in a row, it indicates that there is a problem in the weight setting of the recommendation parameters, so adjustments are made.

[0141] In this embodiment, the basis for adjustment is the user's evaluation. This evaluation is not just the evaluation of a single service, but a comprehensive evaluation of all users.

[0142] For example, when the average user rating of service quality is 80, while the average rating of other users is 90, it means that the user has very high requirements for service quality and the weight of service quality needs to be significantly increased, for example, by 30% on the original basis. Correspondingly, the distance weight should be reduced accordingly.

[0143] For example, another user's average score for service quality evaluation is 95, which is higher than the average score of 90 for other users. This means that the user still cares about the service quality, but is more easily satisfied. Therefore, the weight of is slightly increased, for example, by 5% on the original basis. Similarly, the distance weight should be reduced accordingly.

[0144] For example, another user's service evaluation is full marks, which means that the user does not care much about the service quality and just habitually gives good reviews. Therefore, the weight of service quality can be appropriately reduced, for example, by 10% on the original basis, and the distance weight can be increased accordingly.

[0145] It can be foreseen that after the user portrait is corrected, the next recommendation activity will be based on the corrected user portrait.

[0146] Example 2

[0147] like Figure 2 As shown, the present invention also provides a new energy vehicle service station recommendation system, comprising:

[0148] User portrait construction module: the ratio A:B between the user's attention to the distance to the service site and the service quality is obtained to form a user portrait;

[0149] The urgency acquisition module is used to obtain the service name of the service required by the user based on the search keyword entered by the user, and collect the geographical location of the user when entering the search keyword; and obtain the urgency of the service based on the service required by the user;

[0150] A weight allocation module is used to allocate weights to recommendation indicators based on user profiles and service urgency; the recommendation indicators include distance weight, service quality weight, and associated service weight;

[0151] The recommendation module is used to obtain related services of a service based on the service name; query service sites within a threshold range that provide the user's required service based on the user's geographical location when the user enters the keyword; score the service sites that provide the user's required service based on the recommendation index, and recommend service sites to the user based on the score;

[0152] A user portrait correction module is used to correct the user portrait based on the user's rating of the service site after receiving the service and the user's acceptance of the recommended service site;

[0153] The method in which the urgency acquisition module acquires the urgency of the service according to the service required by the user includes:

[0154] Classify services and categorize their urgency into levels one to three based on the type of service;

[0155] When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, and D1+S1=1;

[0156] When the urgency is at the first level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, and D1+S1=1;

[0157] When the urgency is at the first level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, and D1+S1=1;

[0158] The method for the weight allocation module to allocate the weights of the recommendation indicators according to the user portrait and the urgency of the service includes:

[0159] Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1;

[0160] When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0;

[0161] When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0;

[0162] When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; and the adjusted associated service weight C = C0.

[0163] Example 3

[0164] The present invention also provides a storage medium, in which a computer program is stored; when the computer program is executed, the above-mentioned new energy vehicle service station recommendation method can be implemented.

[0165] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus comprising the element.

[0166] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), including a number of instructions for enabling a computer terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0167] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are protected by the present invention.

Claims

1. A new energy vehicle service station recommendation method, characterized in that include: When a user registers, a progress bar is displayed on the user registration page; one end of the progress bar represents the distance, and the other end represents the service quality. A slider is provided on the progress bar that can slide along the progress bar. The user drags the slider to change the ratio A:B between the distance end and the service quality end to form a user profile, and the sum of the distance end ratio and the service quality end ratio is a constant value. Obtain the service name of the service required by the user based on the search keyword entered by the user, and collect the geographical location of the user when entering the search keyword; the services include core services and peripheral services related to car owners; the core services include charging, tire changing, maintenance, and car washing; the peripheral services include catering, entertainment, shopping, and leisure; The urgency of obtaining the core service according to the service required by the user; Assigning weights to recommendation indicators based on the user profile and the urgency of the core service; the recommendation indicators include distance weight, service quality weight, and associated service weight; Obtain the associated services of the core service according to the service name; querying service sites within a threshold range that have the service required by the user based on the geographical location of the user when the search keyword is entered; Scoring service sites that provide services required by users based on recommendation indicators, and recommending service sites to users based on the scores; Modifying the user profile based on the user's rating of the service site after receiving the service and the user's acceptance of the recommended service site; The step of obtaining the urgency of the core service according to the service required by the user includes: The core services are classified into three levels of urgency, one to three levels, based on the service type; charging and tire changing are ranked first in urgency; car washing is ranked second in urgency; and maintenance is ranked third in urgency; When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, and D1+S1=1; When the urgency is at the second level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, and D2+S2=1; When the urgency is at the third level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, and D3+S3=1; The step of allocating weights of recommendation indicators based on the user profile and the urgency of the core service includes: Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1; where D0=40%, S0=40%, and C0=20%. When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0; When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0; When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; and the adjusted associated service weight C = C0.

2. A new energy vehicle service station recommendation method according to claim 1, characterized in that The steps for obtaining the associated services of a service based on the service name include: In the case where the service required by the user is a service that the user has historically received, other services that were performed simultaneously when the user historically received the service are considered as associated services; In the case that the service required by the user is a service that the user has never received, a related service is selected according to the service related graph.

3. The method for recommending new energy vehicle service stations according to claim 2, characterized in that: The service association graph uses services as nodes and relationships between services as edges; A service required by the user is selected from the service association graph, and services directly connected to the service required by the user or / and services indirectly connected via edges less than a threshold number are used as associated services.

4. A new energy vehicle service station recommendation method according to claim 1, characterized in that The steps of scoring the service sites that have the services required by the user according to the recommendation indicators include: Obtaining the distance between the service site and the user, and scoring according to the adjusted distance weight to obtain a distance score; Obtaining individual evaluations of services required by users at the service site and a comprehensive evaluation of the service site, and scoring them according to the adjusted service quality weights to obtain a service quality score; Obtain the number of associated services included in the service site, and score the associated services according to the adjusted associated service weights to obtain associated service scores; The sum of the distance score, the service quality score and the associated service score is used as the score of the service site.

5. The method for recommending new energy vehicle service stations according to claim 4, characterized in that: The rating ratio of the single evaluation of the service required by the user in the service site and the comprehensive evaluation of the service site is K1:K2, where K1>K2.

6. A new energy vehicle service station recommendation method according to claim 1, characterized in that The steps for recommending service sites to users based on ratings include: Sort all service sites in descending order according to their scores, and recommend the service sites with a ranking higher than a ranking threshold to the user; or The service sites whose scores are higher than a score threshold are recommended to the user.

7. A new energy vehicle service station recommendation method according to claim 1, characterized in that The steps for modifying the user profile based on the user's rating of the service site after receiving the service and the acceptance of the recommended service site include: When the number of times that the user does not accept the recommended service site exceeds a preset threshold, the user profile is adjusted; the adjustment step specifically includes: Compare the user's average score A1 for service quality with the average score A2 for service quality of all other users. When A1 is less than A2, increase the service quality weight by a first percentage; when A1 is greater than or equal to A2 and A1 is not a full score, increase the service quality weight by a second percentage; when A1 is a full score, reduce the service quality weight by a third percentage; wherein the first percentage is greater than the second percentage.

8. A new energy vehicle service station recommendation system, characterized by include: A user profile building module is used to display a progress bar on the user registration page during user registration; one end of the progress bar represents distance, and the other end represents service quality; a slider is provided on the progress bar that can slide along the progress bar; the user drags the slider to change the ratio A:B between the distance end and the service quality end to form a user profile, and the sum of the distance end ratio and the service quality end ratio is a constant value; The urgency acquisition module is used to obtain the service name of the service required by the user based on the search keyword entered by the user, and collect the user's geographical location when the search keyword is entered; obtain the urgency of the core service based on the service required by the user; the services include core services and peripheral services related to the car owner; the core services include charging, tire changing, maintenance, and car washing; the peripheral services include catering, entertainment, shopping, and leisure; A weight allocation module, configured to allocate weights of recommendation indicators based on the user profile and the urgency of the core service; the recommendation indicators include distance weight, service quality weight, and associated service weight; A recommendation module, used to obtain related services of the core service according to the service name; and querying service sites that have the service required by the user within a threshold range based on the geographical location when the user inputs the search keyword; scoring the service sites that have the service required by the user according to the recommendation index, and recommending the service sites to the user based on the scoring; A user portrait correction module is used to correct the user portrait according to the user's rating of the service site after receiving the corresponding service and the user's acceptance of the recommended service site; The urgency acquisition module specifically includes: Categorize core services and categorize their urgency into levels one to three based on the type of service; When the urgency is at the first level, the distance weight adjustment coefficient is D1, the service quality weight adjustment coefficient is S1, and D1+S1=1; When the urgency is at the second level, the distance weight adjustment coefficient is D2, the service quality weight adjustment coefficient is S2, and D2+S2=1; When the urgency is at the third level, the distance weight adjustment coefficient is D3, the service quality weight adjustment coefficient is S3, and D3+S3=1; The weight allocation module allocates the weights of the recommendation indicators according to the user profile and the urgency of the core service, specifically including: Initialize the weights of the recommended indicators and assign an initial weight to each recommended indicator. The initial distance weight is D0, the initial service quality weight is S0, and the initial associated service weight is C0. D0+S0+C0=1; where D0=40%, S0=40%, and C0=20%. When the urgency is at the first level, the adjusted distance weight D = D0*(A*D1) / [(A*D1)+(B*S1)]; the adjusted service quality weight S = S0*(B*S1) / [(A*D1)+(B*S1)]; the adjusted associated service weight C = C0; When the urgency is at the second level, the adjusted distance weight D = D0*(A*D2) / [(A*D2)+(B*S2)]; the adjusted service quality weight S = S0*(B*S2) / [(A*D2)+(B*S2)]; the adjusted associated service weight C = C0; When the urgency is at the third level, the adjusted distance weight D = D0*(A*D3) / [(A*D3)+(B*S3)]; the adjusted service quality weight S = S0*(B*S3) / [(A*D3)+(B*S3)]; and the adjusted associated service weight C = C0.

9. A computer-readable storage medium, characterized in that: The storage medium stores a computer program; when the computer program is executed, it can implement the new energy vehicle service station recommendation method described in any one of claims 1 to 7.

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