Parking service recommendation method, parking service platform, equipment and readable storage medium

Abstract

The invention provides a parking service recommendation method, a parking service platform, equipment and a readable storage medium, and belongs to the field of commodity recommendation. The method comprises the following steps: matching a first parking service according to historical parking behavior data of a user, wherein the historical parking behavior data comprises at least one of historical parking frequency, historical parking duration and historical access flow of a parking lot; matching a second parking service according to current parking behavior data of the user, wherein the current parking behavior data comprises a current payment mode and a current parking position; matching a third parking service according to the historical parking service purchase data of the user; and combining the first parking service, the second parking service and the third parking service into a service package, and issuing the service package to the client of the user. By analyzing the historical parking behavior data, the current parking behavior data and the historical purchase parking service data, the parking service demand of the user is accurately matched, and the parking service recommendation effect is improved.

Description

Technical Field

[0001] The present application relates to the field of product recommendation, and in particular to a parking service recommendation method, a parking service platform, a device and a readable storage medium. Background Art

[0002] Currently, there are many types of services on parking service platforms. Different users require different types of parking services. Traditional methods do not take into account users' potential needs and interests, and the parking service recommendation effect is poor. Summary of the invention

[0003] In order to solve the technical problem that the traditional method has poor service product recommendation effect, the embodiments of the present application provide a parking service recommendation method, a parking service platform, a device and a readable storage medium.

[0004] In a first aspect, an embodiment of the present application provides a parking service recommendation method, the method comprising:

[0005] matching a first parking service according to historical parking behavior data of the user, wherein the historical parking behavior data includes at least one of historical parking frequency, historical parking duration, and historical parking lot in-and-out flow;

[0006] matching a second parking service according to the user's current parking behavior data, wherein the current parking behavior data includes a current payment method and a current parking location;

[0007] matching a third parking service according to the user's historical parking service purchase data;

[0008] The first parking service, the second parking service and the third parking service are combined into a service package, and the service package is sent to a client of the user.

[0009] In one embodiment, matching the first parking service according to the historical parking behavior data of the user includes:

[0010] Obtain the historical parking duration of the user at each parking lot;

[0011] Obtain the charging rule change point time of each parking lot, and set the charging rule change point time range according to the charging rule change point time;

[0012] Counting the number of times the user has paid within the time range of the charging rule change point based on the historical parking duration of each parking lot of the user;

[0013] If the number of times is greater than a preset number threshold, a fee skipping reminder service is matched as the first parking service.

[0014] In one embodiment, matching the first parking service according to the historical parking behavior data of the user includes:

[0015] Obtain the historical parking frequency of the user in each parking lot;

[0016] Preset multiple levels of parking frequency thresholds, and divide the historical parking frequencies into different parking demand levels according to the parking frequency thresholds;

[0017] A corresponding target parking card service is selected according to the parking demand level as the first parking service.

[0018] In one embodiment, matching the first parking service according to the historical parking behavior data of the user includes:

[0019] Obtaining the historical in-and-out traffic of the user at each parking lot;

[0020] A first-out-and-pay-later service is matched according to the historical in-and-out traffic of each parking lot as the first parking service.

[0021] In one embodiment, the historical parking behavior data further includes the browsing time of the unclicked service and the browsing time of the clicked service, and matching the first parking service according to the historical parking behavior data of the user further includes:

[0022] Calculate the non-clicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service according to the non-clicked service browsing time and the clicked service browsing time of the user, and set the corresponding non-clicked service browsing recommendation score weight and the clicked service browsing recommendation score weight respectively;

[0023] Obtaining a comprehensive recommendation score for each parking service according to the unclicked service browsing recommendation score and the unclicked service browsing recommendation score weight and the clicked service browsing recommendation score and the clicked service browsing recommendation score weight;

[0024] A recommendation score threshold is set, and the parking services whose comprehensive recommendation scores are greater than or equal to the recommendation score threshold are screened to obtain a first parking service.

[0025] In one embodiment, the step of calculating the non-clicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service according to the non-clicked service browsing time and the clicked service browsing time of the user includes:

[0026] The unclicked service browsing time and the clicked service browsing time under each service are obtained and normalized, and the normalized results are used as the unclicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service.

[0027] In one embodiment, matching the second parking service according to the current parking behavior data of the user includes:

[0028] Obtain the user's current payment method;

[0029] If the user's current payment method is paid by someone else, a privacy protection service is matched as the second parking service, and the privacy protection service will hide the current parking information when someone else pays on behalf of the user.

[0030] In a second aspect, an embodiment of the present application provides a parking service platform, the parking service platform comprising:

[0031] A first matching module, configured to match a first parking service according to historical parking behavior data of a user, wherein the historical parking behavior data includes at least one of historical parking frequency, historical parking duration, and historical parking lot in-and-out flow;

[0032] A second matching module, configured to match a second parking service according to the user's current parking behavior data, wherein the current parking behavior data includes a current payment method and a current parking location;

[0033] A third matching module, configured to match a third parking service according to the user's historical parking service purchase data;

[0034] The sending module is used to combine the first parking service, the second parking service and the third parking service into a service package, and send the service package to the user's client.

[0035] In a third aspect, an embodiment of the present application provides an electronic device including a memory and a processor, wherein the memory is used to store a computer program, and when the computer program is run by the processor, the parking service recommendation method provided in the first aspect is executed.

[0036] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium storing a computer program, which executes the parking service recommendation method provided in the first aspect when the computer program is executed on a processor.

[0037] The parking service recommendation method provided by the present application matches the first parking service according to the user's historical parking behavior data, which includes at least one of the historical parking frequency, historical parking duration, and historical parking lot in-and-out flow; matches the second parking service according to the user's current parking behavior data, which includes the current payment method and the current parking location; matches the third parking service according to the user's historical parking service purchase data; combines the first parking service, the second parking service, and the third parking service into a service package, and sends the service package to the user's client. By analyzing the historical parking behavior data, the current parking behavior data, and the historical parking service purchase data, the user's parking service needs can be accurately matched, and the parking service recommendation effect can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the technical solution of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present application and should not be regarded as limiting the scope of protection of the present application. In each of the drawings, similar components are numbered similarly.

[0039] Figure 1 A schematic diagram showing a process of a parking service recommendation method provided in an embodiment of the present application is shown;

[0040] Figure 2 Another schematic diagram of the process of the parking service recommendation method provided by the embodiment of the present application is shown;

[0041] Figure 3 Another schematic diagram of a parking service recommendation method provided in an embodiment of the present application is shown;

[0042] Figure 4 Another flowchart of the parking service recommendation method provided in the embodiment of the present application is shown;

[0043] Figure 5 A structural schematic diagram of a parking service platform provided in an embodiment of the present application is shown.

[0044] Icons: 500-parking service platform, 501-first matching module, 502-second matching module, 503-third matching module, 504-issuing module. DETAILED DESCRIPTION

[0045] The technical solutions in the embodiments of the present application will be described clearly and completely below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0046] The components of the embodiments of the present application generally described and shown in the drawings herein may be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0047] Hereinafter, the terms "including", "having" and their cognates, which may be used in various embodiments of the present application, are intended only to indicate specific features, numbers, steps, operations, elements, components, or combinations of the foregoing items, and should not be understood as first excluding the existence of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing items or adding the possibility of one or more features, numbers, steps, operations, elements, components, or combinations of the foregoing items.

[0048] Furthermore, the terms “first”, “second”, “third”, etc. are merely used for distinguishing descriptions and are not to be understood as indicating or implying relative importance.

[0049] Unless otherwise defined, all terms (including technical terms and scientific terms) used herein have the same meanings as those generally understood by those skilled in the art to which the various embodiments of the present application belong. Terms (such as those defined in generally used dictionaries) will be interpreted as having the same meanings as the contextual meanings in the relevant technical field and will not be interpreted as having idealized meanings or overly formal meanings unless clearly defined in the various embodiments of the present application.

[0050] Example 1

[0051] Currently, there are many services on the parking service platform. The traditional parking service provision model usually adopts a fixed service package. This model fails to fully consider the differences in user needs and often leads to users purchasing service rights that they do not really need, thus affecting users' purchasing intention and satisfaction.

[0052] Based on the above problems, this application mines users' parking behavior data to accurately match users' actual needs for parking services.

[0053] An embodiment of the present application provides a parking service recommendation method.

[0054] See also Figure 1 The parking service recommendation method includes steps S101 to S104:

[0055] S101: Matching a first parking service according to historical parking behavior data of a user, where the historical parking behavior data includes at least one of historical parking frequency, historical parking duration, and historical parking lot in-and-out flow.

[0056] In this embodiment, the parking service that the user may need is matched according to the user's historical parking frequency, historical parking duration and historical parking lot in and out traffic, so as to help the user better understand his or her parking behavior, optimize parking strategy and explore potential opportunities to save parking fees. For example, based on the historical parking duration and the change points of the billing rules of each parking lot, the number of times users park and the amount they pay near the billing change point are counted, and users are reminded when the billing change point is about to be reached to avoid unnecessary cost increases; for example, based on the historical parking frequency, the user's parking demand type (such as daily commuting, weekend travel, etc.) is analyzed to provide users with more economical and flexible parking service options, including parking card services such as daily cards / weekly cards / monthly cards / annual cards; for example, it is determined whether the traffic volume in and out of the parking lot is greater than the preset threshold. If it is greater than the preset threshold, the first-out-and-pay-later service is recommended, and the user can leave the parking lot first and then pay the parking fee; for high-frequency users with a high parking frequency or users with specific payment methods (such as using specific payment channels), a discount service is provided to each parking fee; for example, based on the user's historical parking frequency and historical payment amount, a coupon service is provided to high-frequency users or high-value users to enhance user stickiness and encourage users to continue using the service.

[0057] See also Figure 2 In one embodiment, matching the first parking service according to the historical parking behavior data of the user includes steps S201 to S204:

[0058] S201: Obtain the historical parking duration of each parking lot of the user.

[0059] In this embodiment, detailed records of users' parking in different parking lots are obtained, including the start and end time of each parking. The obtained data is used as an important basis for subsequent analysis of the user's parking behavior and judgment on whether the user has paid unnecessary extra fees.

[0060] S202: Obtain the charging rule change point time of each parking lot, and set the charging rule change point time range according to the charging rule change point time.

[0061] In this embodiment, in order to accurately assess the impact that the user may be affected by the change in charging rules, the change time of each parking lot's charging rules is obtained. The change time is the occurrence of fee jumps in different time periods, such as the first half hour of the parking lot is free, and after half an hour, parking will be charged according to time, or after two hours, it will be charged according to other standards. Based on these change times, a time range is set, which can be within 5 minutes before and after the change time or other time ranges, which are not limited in this embodiment, and whether the user has made a payment within the time range is obtained, so that the user can avoid fee jumps as much as possible.

[0062] S203: Counting the number of times the user paid within the time range of the charging rule change point based on the historical parking duration of each parking lot of the user.

[0063] In this embodiment, the previously collected historical parking data and the time range of charging rule changes are used to count the number of parking fee payments made by users within the time range of each change point. Based on the statistical results, it is determined whether the user is frequently affected by the charging rule changes, thereby evaluating whether the user needs the fee skipping reminder service.

[0064] S204: If the number of times is greater than the preset number threshold, matching the fee skipping reminder service as the first parking service.

[0065] In this embodiment, the statistical number of payments is compared with a preset number threshold. If the number of payments made by the user within the time range of the billing rule change point exceeds the preset threshold, it means that the user is often affected by the change in billing rules because he or she does not pay attention to the payment time or the parking billing rules of the parking lot. Therefore, the parking service platform determines that the user needs a fee skipping reminder service. At this time, the parking service platform can match the user with the corresponding service to notify him or her of the upcoming fee changes in advance, thereby helping the user to better plan the parking budget and avoid unnecessary cost increases.

[0066] See also Figure 3 In one embodiment, matching the first parking service according to the historical parking behavior data of the user includes steps S301-S303:

[0067] S301: Obtain the user's historical parking frequency in each parking lot.

[0068] In this embodiment, the number of times a user parks in each parking lot within a specified time period is counted, and the historical parking frequency corresponding to each parking lot is calculated.

[0069] S302: Preset multiple levels of parking frequency thresholds, and divide the historical parking frequencies into different parking demand levels according to the parking frequency thresholds.

[0070] In one embodiment, applicable parking frequency thresholds for different parking card services are set based on business rules or market research. If the user's historical parking frequency is higher than the preset daily card frequency threshold, the daily card service is recommended. If the historical parking frequency is higher and meets the threshold conditions for the monthly card service, the monthly card service is recommended. For users who occasionally park, the occasional card service can be recommended.

[0071] S303: Selecting a corresponding target parking card service as a first parking service according to the parking demand level.

[0072] In this embodiment, users are divided into different parking demand levels according to their historical parking frequencies and preset thresholds, and the most suitable parking card service is selected according to the parking demand levels of the users.

[0073] Optionally, for low-frequency users, single payment or daily card services are more suitable because their parking needs are not frequent; for medium-frequency users, weekly or monthly card discount packages are recommended to attract them to use for a long time. For high-frequency users, monthly cards or longer-term parking service packages are recommended to provide the greatest discount and convenience. If the user has already pre-purchased a parking service (such as an existing monthly card), but based on the new parking frequency assessment, it is found that it is more suitable for another service (such as switching from a monthly card to a weekly card or a daily card), you can proactively communicate with the user and provide replacement suggestions. If the user has not pre-purchased any parking service, the most suitable parking card service is recommended directly based on the evaluation results.

[0074] In one embodiment, matching the first parking service according to the user's historical parking behavior data includes: obtaining the user's historical parking lot entry and exit traffic in each parking lot; matching the first-out-and-then-pay service as the first parking service according to the parking lot's historical parking lot entry and exit traffic in each parking lot.

[0075] In this embodiment, the traffic data of the parking lot frequently visited by the user is analyzed to determine whether the traffic data will cause congestion before paying for leaving the parking lot. If the parking lot frequently visited by the user has a large historical in-and-out traffic flow and the user is accustomed to parking during peak hours, then the pay-later service is recommended to reduce the time wasted by the user when leaving the parking lot.

[0076] See also Figure 4 In one embodiment, the historical parking behavior data further includes the browsing time of the unclicked service and the browsing time of the clicked service, and matching the first parking service according to the historical parking behavior data of the user also includes steps S401-S403:

[0077] S401: Calculate the non-clicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service according to the non-clicked service browsing time and the clicked service browsing time of the user, and set the corresponding non-clicked service browsing recommendation score weight and the clicked service browsing recommendation score weight respectively.

[0078] In this embodiment, by embedding a log recording function in the front-end page of the parking service platform, the user's historical browsing and click data are collected, including recording the browsing time after the user clicks on the parking service, the number of service clicks, and the browsing time of the parking service that is not clicked. Further, the non-clicked service browsing recommendation score corresponding to each service is calculated according to the non-clicked service browsing time, and a value between 0 and 1 is set to indicate the relative importance of the non-clicked service browsing recommendation score in the comprehensive recommendation score.

[0079] Exemplarily, the browsing time and click count data of the parking services clicked by the user are collected. Combined with the browsing time after clicking the service and the number of clicks on the service, the click service browsing recommendation score is calculated, and the click service browsing recommendation score weight is set. Since the click behavior can more directly reflect the user's interest than the non-click behavior, the weight of the click service browsing will be set higher, where the sum of the non-click service browsing recommendation score weight and the click service browsing recommendation score weight is 1.

[0080] In one embodiment, the unclicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service are calculated based on the user's unclicked service browsing time and clicked service browsing time, including: obtaining the unclicked service browsing time and the clicked service browsing time under each service and normalizing them, and using the normalized results as the unclicked service browsing recommendation score and the clicked browsing recommendation score.

[0081] In this embodiment, for each unclicked parking service number i, the unclicked service browsing time T under each service is counted. i , the unclicked browsing time of each parking service is normalized. First, the sum of the browsing time of all unclicked services is calculated. Where WDT Total is the sum of the unclicked browsing time of all parking services. Finally, the formula The unclicked browsing time is normalized to obtain the unclicked service browsing recommendation score for each unclicked parking service. It should be noted that the unclicked service browsing time refers to the time spent by the user when browsing a parking service, but the user did not perform any click operation during this period, such as clicking any link, button or performing any interaction. This "passive" browsing behavior reflects the user's interest and participation in the parking service content.

[0082] For example, for each clicked parking service number j, the user clicked the service browsing time DT j and click service times (DC j), in order to comprehensively consider the click duration and click count, the two are multiplied to obtain the click service browsing value CV of each service j =DT j ×DC j The click-through service view value reflects the user's interest in the service through the click duration, and reflects the user's attention to the service through the number of clicks. Since the click-through service view values ​​of different parking services have different dimensions and ranges from the unclicked service view recommendation scores, in order to calculate the comprehensive recommendation score, the click-through service view values ​​of each service are also normalized. Calculate the sum of the click-through service view values ​​of all services According to CB Total Normalize the click and service browsing values ​​of each service. CScore j Indicates the click-to-browse service recommendation score of the sequence number j of the click-to-browse service.

[0083] S402: Obtain a comprehensive recommendation score for each parking service according to the unclicked service browsing recommendation score and the unclicked service browsing recommendation score weight and the clicked service browsing recommendation score and the clicked service browsing recommendation score weight.

[0084] In this embodiment, the value Score after normalization of the unclicked service browsing recommendation score i Multiply the clicked service browsing recommendation score weight by the unclicked service browsing recommendation score weight W to get the weighted score of the unclicked part. Similarly, the normalized value of the clicked service browsing recommendation score CScore j Multiply it by the click service browsing recommendation score weight WC to get the weighted score of the clicked part. The weighted score of the unclicked part is WScore i =Score i ×W, the weighted score of the click part is WCScore j =CScore j ×WC.

[0085] S403: Setting a recommendation score threshold, screening parking services whose comprehensive recommendation scores are greater than or equal to the recommendation score threshold, and obtaining a first parking service.

[0086] In this embodiment, by analyzing the business needs and parking service data of the user's historical purchases, a recommendation score threshold is set, and the comprehensive recommendation score WScore of each parking service is calculated. i or WScore j The service is compared with the recommendation score threshold. If the comprehensive recommendation score is greater than or equal to the threshold, the service is taken as the first parking service. These parking services will be recommended to users as the first purchase options they may be interested in.

[0087] S102: Matching a second parking service according to the user's current parking behavior data, where the current parking behavior data includes a current payment method and a current parking location.

[0088] In this embodiment, if the user's payment method is paid by someone else, it is inferred that the user may need to hide the parking lot name, parking location, parking duration, etc., and provide privacy protection services to ensure the security and privacy of user data and enhance user trust.

[0089] For example, if the parking service platform obtains the current parking location reported by the vehicle, it will match the user's current parking location with the parking lot discount information based on the current parking lot location of the user's vehicle, and provide an automatic coupon collection service. The automatic coupon collection service can query the parking lot's discount activity information in real time, including but not limited to free parking coupons, discounts, points redemption, etc.

[0090] In one embodiment, matching the first parking service based on the user's historical parking behavior data includes: obtaining the user's current payment method; if the user's current payment method is paid by someone else, matching the privacy protection service as the second parking service, and the privacy protection service will hide the current parking information when someone else pays on behalf of the user.

[0091] In this embodiment, the user's current payment method is obtained. If the user currently uses someone else to pay, the user may need confidentiality for personal privacy or financial status. The parking service platform matches the user with a privacy protection service, which allows the parking lot name, parking location and parking duration of the vehicle to be hidden.

[0092] S103: Matching with a third parking service based on the user's historical parking service purchase data.

[0093] In this embodiment, the user's historical purchase data is collected, and a purchased parking service is selected from the historically purchased parking services as the third parking service. The third parking service is the parking service that the user has purchased in the past. The parking service that the user has purchased in the past is sent to the customer's client.

[0094] S104: Combining the first parking service, the second parking service, and the third parking service into a service package, and sending the service package to the user's client.

[0095] In this embodiment, the parking service platform will combine the selected parking services to provide users with multiple service packages, including single service packages and combined service packages. Users can choose to purchase any one of the first parking service, the second parking service or the third parking service separately, that is, a single service package, to meet specific needs. Users can also choose to purchase a combined service package formed by combining multiple services of the first parking service, the second parking service and the third parking service according to different needs. To meet the diverse parking needs of users, corresponding pricing strategies are formulated for different service packages.

[0096] Optionally, after the service package combination is completed, the parking service platform will generate a corresponding data package for each service package, including detailed information of the service package (such as service type, price, validity period, etc.) and instructions for use, and send the data package corresponding to each service package to the user's client. The user can view the service package content through the client and choose to purchase the service package that suits him or her.

[0097] The parking service recommendation method provided in this embodiment matches the first parking service according to the user's historical parking behavior data, the historical parking behavior data includes at least one of the historical parking frequency, the historical parking duration, and the historical parking lot in-and-out flow; matches the second parking service according to the user's current parking behavior data, the current parking behavior data includes the current payment method and the current parking location; matches the third parking service according to the user's historical parking service purchase data; combines the first parking service, the second parking service, and the third parking service into a service package, and sends the service package to the user's client. By analyzing the historical parking behavior data, the current parking behavior data, and the historical parking service purchase data, the user's parking service needs are accurately matched, and the parking service recommendation effect is improved.

[0098] Example 2

[0099] In addition, an embodiment of the present application provides a parking service platform, which is applied to electronic devices.

[0100] like Figure 5 As shown, the parking service platform 500 includes:

[0101] The first matching module 501 is used to match the first parking service according to the user's historical parking behavior data, wherein the historical parking behavior data includes at least one of historical parking frequency, historical parking duration, and historical parking lot in-and-out flow.

[0102] The second matching module 502 is used to match a second parking service according to the current parking behavior data of the user, wherein the current parking behavior data includes a current payment method and a current parking location.

[0103] The third matching module 503 is used to match a third parking service according to the historical parking service purchase data of the user.

[0104] The sending module 504 is used to combine the first parking service, the second parking service and the third parking service into a service package, and send the service package to the user's client.

[0105] Optionally, the first matching module 501 shown is also used to obtain the historical parking duration of each parking lot by the user; obtain the billing rule change point time of each parking lot, and set the billing rule change point time range according to the billing rule change point time; count the number of times the user pays within the billing rule change point time range according to the historical parking duration of each parking lot by the user; if the number is greater than a preset number threshold, match the fee skipping reminder service as the first parking service.

[0106] Optionally, the first matching module 501 shown is also used to obtain the historical parking frequency of the user in each parking lot; preset multiple levels of parking frequency thresholds, and divide the historical parking frequencies into different parking demand levels according to the parking frequency thresholds; and select the corresponding target parking card service as the first parking service according to the parking demand level.

[0107] Optionally, the first matching module 501 is further used to obtain the historical parking lot entry and exit traffic of the user in each parking lot; and match the first-out-and-then-pay service as the first parking service according to the historical parking lot entry and exit traffic of each parking lot.

[0108] Optionally, the first matching module 501 shown is also used to calculate the unclicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service based on the user's unclicked service browsing time and the clicked service browsing time, and set the corresponding unclicked service browsing recommendation score weight and the clicked service browsing recommendation score weight respectively; obtain the comprehensive recommendation score of each parking service based on the unclicked service browsing recommendation score and the unclicked service browsing recommendation score weight and the clicked service browsing recommendation score and the clicked service browsing recommendation score weight; set the recommendation score threshold, filter the parking services whose comprehensive recommendation scores are greater than or equal to the recommendation score threshold, and obtain the first parking service.

[0109] Optionally, the first matching module 501 is further used to obtain the unclicked service browsing time and the clicked service browsing time under each service and perform normalization processing, and use the normalized results as the unclicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service.

[0110] Optionally, the second matching module 502 is also used to obtain the current payment method of the user; if the current payment method of the user is paid by someone else, the privacy protection service is matched as the second parking service, and the privacy protection service will hide the current parking information when someone else pays on behalf of the user.

[0111] The parking service platform 500 provided in this embodiment can implement the parking service recommendation method provided in Embodiment 1, and will not be described again here to avoid repetition.

[0112] The parking service platform provided in this embodiment matches the first parking service according to the user's historical parking behavior data, which includes at least one of the historical parking frequency, historical parking duration, and historical parking lot in-and-out flow; matches the second parking service according to the user's current parking behavior data, which includes the current payment method and the current parking location; matches the third parking service according to the user's historical parking service purchase data; combines the first parking service, the second parking service, and the third parking service into a service package, and sends the service package to the user's client. By analyzing the historical parking behavior data, the current parking behavior data, and the historical parking service purchase data, the user's parking service needs are accurately matched, and the parking service recommendation effect is improved.

[0113] Example 3

[0114] In addition, an embodiment of the present application provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and when the computer program runs on the processor, the parking service recommendation method provided in Embodiment 1 is executed.

[0115] The electronic device provided in the embodiment of the present invention can execute the steps of the parking service recommendation method provided in the above method embodiment 1, which will not be described again here to avoid repetition.

[0116] Example 4

[0117] The present application also provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the parking service recommendation method provided in Example 1 is implemented.

[0118] In this embodiment, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0119] The computer-readable storage medium provided in this embodiment can implement the parking service recommendation method provided in Example 1, and will not be described again here to avoid repetition.

[0120] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or terminal including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or terminal. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or terminal including the element.

[0121] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, 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, a disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods of each embodiment of the present application.

[0122] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application 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 application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

Claims

1. A parking service recommendation method, characterized in that: The method comprises: matching a first parking service according to historical parking behavior data of the user, wherein the historical parking behavior data includes at least one of historical parking frequency, historical parking duration, and historical parking lot in-and-out flow; matching a second parking service according to the user's current parking behavior data, wherein the current parking behavior data includes a current payment method and a current parking location; matching a third parking service according to the user's historical parking service purchase data; The first parking service, the second parking service and the third parking service are combined into a service package, and the service package is sent to a client of the user.

2. The method according to claim 1, characterized in that The matching of the first parking service according to the historical parking behavior data of the user includes: Obtain the historical parking duration of the user at each parking lot; Obtain the charging rule change point time of each parking lot, and set the charging rule change point time range according to the charging rule change point time; Counting the number of times the user has paid within the time range of the charging rule change point based on the historical parking duration of each parking lot of the user; If the number of times is greater than a preset number threshold, a fee skipping reminder service is matched as the first parking service.

3. The method according to claim 1, characterized in that The matching of the first parking service according to the historical parking behavior data of the user includes: Obtain the historical parking frequency of the user in each parking lot; Preset multiple levels of parking frequency thresholds, and divide the historical parking frequencies into different parking demand levels according to the parking frequency thresholds; A corresponding target parking card service is selected according to the parking demand level as the first parking service.

4. The method according to claim 1, characterized in that: The matching of the first parking service according to the historical parking behavior data of the user includes: Obtaining the historical in-and-out traffic of the user at each parking lot; A first-out-and-pay-later service is matched according to the historical in-and-out traffic of each parking lot as the first parking service.

5. The method according to claim 1, characterized in that The historical parking behavior data also includes browsing time of services that were not clicked and browsing time of services that were clicked. Matching the first parking service according to the historical parking behavior data of the user also includes: Calculate the non-clicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service according to the non-clicked service browsing time and the clicked service browsing time of the user, and set the corresponding non-clicked service browsing recommendation score weight and the clicked service browsing recommendation score weight respectively; Obtaining a comprehensive recommendation score for each parking service according to the unclicked service browsing recommendation score and the unclicked service browsing recommendation score weight and the clicked service browsing recommendation score and the clicked service browsing recommendation score weight; A recommendation score threshold is set, and the parking services whose comprehensive recommendation scores are greater than or equal to the recommendation score threshold are screened to obtain a first parking service.

6. The method according to claim 5, characterized in that The step of calculating the unclicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service according to the unclicked service browsing time and the clicked service browsing time of the user includes: The unclicked service browsing time and the clicked service browsing time under each service are obtained and normalized, and the normalized results are used as the unclicked service browsing recommendation score and the clicked service browsing recommendation score corresponding to each service.

7. The method according to claim 1, characterized in that The matching the second parking service according to the current parking behavior data of the user includes: Obtain the user's current payment method; If the user's current payment method is paid by someone else, a privacy protection service is matched as the second parking service, and the privacy protection service will hide the current parking information when someone else pays on behalf of the user.

8. A parking service platform, characterized in that: The parking service platform includes: A first matching module, configured to match a first parking service according to historical parking behavior data of a user, wherein the historical parking behavior data includes at least one of historical parking frequency, historical parking duration, and historical parking lot in-and-out flow; A second matching module, configured to match a second parking service according to the user's current parking behavior data, wherein the current parking behavior data includes a current payment method and a current parking location; A third matching module, configured to match a third parking service according to the user's historical parking service purchase data; The sending module is used to combine the first parking service, the second parking service and the third parking service into a service package, and send the service package to the user's client.

9. An electronic device, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the parking service recommendation method according to any one of claims 1 to 7 is executed.

10. A computer-readable storage medium, characterized in that: The computer program stores a computer program, which executes the parking service recommendation method according to any one of claims 1 to 7 when running on a processor.

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