Data processing method, device, related equipment and computer program product

Abstract

The present disclosure provides a data processing method, device, electronic device, computer-readable storage medium and computer program product, which relate to the field of computer internet technology. The data processing method includes: collecting car rental search result information of multiple car rental users, wherein each car rental search result information includes a search location and a vehicle to be rented, wherein the distance of the vehicle to be rented to the search location is less than a first threshold; based on the vehicles to be rented in the car rental search result information of multiple car rental users, determining a first candidate location with fewer car models to be rented than a second threshold among multiple search locations; determining a first target location with a number of occurrences greater than a third threshold among the first candidate locations; and sending the first target location to an operation and maintenance object so that the operation and maintenance object can allocate vehicles to be rented based on the first target location. The embodiment of the present disclosure can determine a place with fewer car models to be rented but with a high frequency of car rental searches based on the car rental search result information, so as to allocate vehicles to be rented.

Description

Technical Field

[0001] The present disclosure relates to the field of computer and Internet technology, and in particular to a data processing method, device, electronic device, computer-readable storage medium, and computer program product. Background Art

[0002] With the development of the car rental company's business, the number of users on the platform has gradually increased, and the number of models in stock on the platform has also been increasing; however, the platform operators lack guidance in choosing store addresses or model configurations, which has caused the model inventory to be too concentrated near popular areas such as airports, railway stations, bus stations, and large shopping malls. This will cause users in some places to search for cars on the platform or there are few models, and the utilization rate of the platform's model inventory is not high.

[0003] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure. Summary of the Invention

[0004] The present disclosure aims to provide a data processing method, apparatus, electronic device, computer-readable storage medium, and computer program product, which can determine, based on car rental search result information, locations with fewer available car models but high frequency of car rental searches, so as to allocate available car models.

[0005] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by practice of the present disclosure.

[0006] An embodiment of the present disclosure provides a data processing method, comprising: collecting car rental search result information of multiple car rental users, wherein each car rental search result information includes a search location and a vehicle to be rented, wherein the distance between the vehicle to be rented and the search location is less than a first threshold; determining a first candidate location in which the number of vehicles to be rented is less than a second threshold from multiple search locations based on the vehicles to be rented in the car rental search result information of the multiple car rental users; determining a first target location in which the number of occurrences is greater than a third threshold from the first candidate locations; and sending the first target location to an operation and maintenance object so that the operation and maintenance object can allocate vehicles to be rented based on the first target location.

[0007] In some embodiments, the method further includes: determining a second candidate location in which the number of vehicles to be rented is less than a fourth threshold value among multiple search locations based on the vehicles to be rented in the car rental search result information of the multiple car rental users; determining a second target location in which the number of occurrences is greater than a fifth threshold value among the second candidate locations; and sending the second target location to the operation and maintenance object so that the operation and maintenance object can allocate the vehicles to be rented according to the first target location.

[0008] In some embodiments, each car rental search result information includes a user identifier; wherein, before determining a first candidate location in multiple search locations where the number of cars for rent is less than a second threshold based on the cars for rent in the car rental search result information of the multiple car rental users, it includes: deduplicating the car rental search result information of the same user identifier at the same search location based on the search location and the user identifier.

[0009] In some embodiments, the search location includes geographic coordinates, and the car rental search result information of the multiple car rental users includes first car rental search result information and second car rental search result information, the first car rental search result information includes a first user identifier and a first geographic coordinate, and the second car rental search result information includes the first user identifier and the second geographic coordinate; wherein, based on the search location and the user identifier, deduplication processing is performed on the car rental search result information with the same user identifier at the same search location, including: determining that the user identifier in the first car rental search result information is the same as the user identifier in the second car rental search result information; determining that the distance between the first geographic coordinate in the first car rental search result information and the second geographic coordinate in the second car rental search result information is less than a sixth threshold, then determining that the first car rental search result information and the second car rental search result information are car rental search result information with the same user identifier at the same search location; deduplication processing is performed on the first car rental search result information and the second car rental search result information.

[0010] In some embodiments, the search location includes a search address name, and the car rental search result information of the multiple car rental users includes third car rental search result information and fourth car rental search result information, the third car rental search result information includes a second user identifier and a third search address name, and the fourth car rental search result information includes the second user identifier and a fourth search address name; wherein, according to the search location and the user identifier, deduplication processing is performed on the car rental search result information with the same user identifier in the same search location, including: determining that the user identifier in the third car rental search result information is the same as the user identifier in the fourth car rental search result information; determining that the third search address name in the third car rental search result information is the same as the fourth search address name in the fourth car rental search result information, then determining that the third car rental search result information and the fourth car rental search result information are car rental search result information with the same user identifier in the same search location; deduplication processing is performed on the third car rental search result information and the fourth car rental search result information.

[0011] An embodiment of the present disclosure provides a data processing device, including: a data collection module, a candidate position determination module, a target position determination module, and a data sending module.

[0012] Among them, the data collection module is used to collect car rental search result information of multiple car rental users, wherein each car rental search result information includes a search location and a vehicle to be rented, and the distance between the vehicle to be rented and the search location is less than a first threshold; the candidate location determination module can be used to determine a first candidate location whose vehicle type to be rented is less than a second threshold among multiple search locations based on the vehicles to be rented in the car rental search result information of the multiple car rental users; the target location determination module can be used to determine a first target location whose number of occurrences is greater than a third threshold among the first candidate locations; the data sending module can be used to send the first target location to the operation and maintenance object, so that the operation and maintenance object can allocate vehicles to be rented according to the first target location.

[0013] An embodiment of the present disclosure provides an electronic device, comprising: a memory and a processor; the memory is used to store program instructions; the processor calls the program instructions stored in the memory to implement any of the above-mentioned data processing methods.

[0014] An embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, the data processing method as described above is implemented.

[0015] The present disclosure provides a computer program product or computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the above-described data processing method.

[0016] The data processing method, apparatus, electronic device, computer-readable storage medium, and computer program product provided by the embodiments of the present disclosure first determine, based on the car rental search results of multiple car rental users, a first candidate location in multiple search locations where the number of available rental models is less than a second threshold, so as to determine those places where there are search records but fewer available rental models are found; then, a first target location with an appearance frequency greater than a third threshold is determined at the first candidate location, so as to determine those places where there are fewer available rental models nearby but where high-frequency searches occur, so that operation and maintenance personnel can allocate available rental vehicles to the first target location to achieve optimal allocation of resources.

[0017] It should be understood that the foregoing general description and the following detailed description are exemplary only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0019] Figure 1 A schematic diagram showing an exemplary system architecture that can be applied to a data processing method or a data processing device according to an embodiment of the present disclosure.

[0020] Figure 2 The figure is a flow chart showing a data processing method according to an exemplary embodiment.

[0021] Figure 3 The figure is a flow chart showing a data processing method according to an exemplary embodiment.

[0022] Figure 4 The figure is a flow chart showing a data processing method according to an exemplary embodiment.

[0023] Figure 5 The figure is a flow chart showing a data processing method according to an exemplary embodiment.

[0024] Figure 6 It is a block diagram of a data processing device according to an exemplary embodiment.

[0025] Figure 7 A schematic structural diagram of an electronic device suitable for implementing the embodiments of the present disclosure is shown. DETAILED DESCRIPTION

[0026] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the drawings represent like or similar parts, and thus repetitive description thereof will be omitted.

[0027] The features, structures or characteristics described in the present disclosure may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure may be practiced while omitting one or more of the specific details, or other methods, components, devices, steps, etc. may be adopted. In other cases, known methods, devices, implementations or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0028] The accompanying drawings are merely schematic illustrations of the present disclosure. Identical reference numerals in the drawings denote identical or similar components, and thus their repeated descriptions will be omitted. Some of the block diagrams shown in the accompanying drawings do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0029] The flowcharts shown in the accompanying drawings are for illustrative purposes only and do not necessarily include all content and steps, nor must they be executed in the order described. For example, some steps may be decomposed, while others may be combined or partially combined. Therefore, the actual execution order may vary depending on the actual situation.

[0030] In the description of this application, unless otherwise specified, " / " means "or", for example, A / B can mean A or B. "And / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, "at least one" means one or more, and "a plurality" means two or more. The words "first", "second", etc. do not limit the quantity and execution order, and the words "first", "second", etc. do not limit them to be different; the terms "comprising", "including" and "having" are used to express open-ended inclusion and mean that in addition to the listed elements / components / etc., there may be other elements / components / etc.

[0031] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below with reference to the accompanying drawings and specific implementation methods. It should be noted that the embodiments of the present application and the features in the embodiments can be combined with each other unless there is a conflict.

[0032] The following first explains some of the terms involved in the embodiments of the present application to facilitate understanding by those skilled in the art.

[0033] The foregoing text introduces some of the terms and concepts involved in the embodiments of this application. The following text introduces the technical features involved in the embodiments of this application.

[0034] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings.

[0035] Figure 1 A schematic diagram showing an exemplary system architecture that can be applied to a data processing method or a data processing device according to an embodiment of the present disclosure.

[0036] like Figure 1As shown, system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. Network 104 is a medium for providing communication links between terminal devices 101, 102, 103 and server 105. Network 104 may include various connection types, such as wired or wireless communication links or fiber optic cables.

[0037] Users can use terminal devices 101, 102, and 103 to interact with server 105 via network 104 to receive or send messages, etc. Terminal devices 101, 102, and 103 can be various electronic devices with display screens and support web browsing, including but not limited to smartphones, tablet computers, laptop computers, desktop computers, wearable devices, virtual reality devices, smart homes, etc.

[0038] The server 105 may be a server that provides various services, such as a background management server that provides support for devices operated by users using the terminal devices 101, 102, and 103. The background management server may analyze and process received requests and other data, and feed back the processing results to the terminal device.

[0039] The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN (Content Delivery Network), as well as basic cloud computing services such as big data and artificial intelligence platforms, etc. This disclosure does not impose any restrictions on this.

[0040] The server 105 may, for example, collect car rental search result information of multiple car rental users, wherein each car rental search result information includes a search location and a vehicle to be rented, wherein the distance between the vehicle to be rented and the search location is less than a first threshold; the server 105 may, for example, determine a first candidate location in which the number of vehicles to be rented is less than a second threshold among multiple search locations based on the vehicles to be rented in the car rental search result information of multiple car rental users; the server 105 may, for example, determine a first target location in which the number of occurrences is greater than a third threshold among the first candidate locations; the server 105 may, for example, send the first target location to the operation and maintenance object so that the operation and maintenance object can allocate the vehicles to be rented according to the first target location.

[0041] It should be understood that Figure 1 The number of terminal devices, networks and servers is merely illustrative. The server 105 may be a single entity server or may be composed of multiple servers. It may have any number of terminal devices, networks and servers according to actual needs.

[0042] Under the above system architecture, an embodiment of the present disclosure provides a data processing method, which can be executed by any electronic device with computing and processing capabilities.

[0043] Figure 2 The method provided by the embodiment of the present disclosure can be executed by any electronic device with computing and processing capabilities. For example, the method can be executed by the above-mentioned Figure 1 The server or terminal device in the embodiment may be executed, or the server and the terminal device may be executed together. In the following embodiments, the server is used as the execution subject for example, but the present disclosure is not limited to this.

[0044] Reference Figure 2 The data processing method provided by the embodiment of the present disclosure may include the following steps.

[0045] Step S202 : collecting car rental search result information of a plurality of car rental users, wherein each car rental search result information includes a search location and a car for rent, wherein the distance between the car for rent and the search location is less than a first threshold.

[0046] In some embodiments, car rental search result information of car rental users in a certain application may be collected, wherein each car rental search result information may include a search location and a car for rent.

[0047] It should be noted that before collecting car rental search result information of car rental users in the application, it may be necessary to obtain the user's prior permission.

[0048] The search location may be an address name (such as XX Building or XX University, etc.) or a geographical coordinate (such as XX degrees east longitude and XX degrees north latitude).

[0049] In some embodiments, in order to better distinguish each search address, the search location may further include a city name.

[0050] In some embodiments, when a user searches for a rental vehicle in an application, the user will generally be pushed vehicles for rent in stores that are less than a first threshold distance from the user (or the user will be pushed vehicles for rent that are less than a first threshold distance from the user), and the first threshold may be 5 km, for example.

[0051] It can be understood that the above-mentioned store may refer to an address, which may correspond to a shop, a square, or a road. This application does not limit the specific form of the store.

[0052] In some embodiments, the above-mentioned vehicle for rent may include vehicle model information, etc.

[0053] Step S204: determining a first candidate location where the number of available rental vehicles is less than a second threshold value from among the multiple search locations based on the available rental vehicles in the rental search result information of the multiple rental users.

[0054] In some embodiments, the number of car models pushed to the user in the car rental search results may be counted, and a first candidate location where the number of car models for rent is less than a second threshold may be determined based on the car rental search results.

[0055] Step S206 : determining a first target position in the first candidate positions, the first target position having an appearance number greater than a third threshold.

[0056] Step S208: sending the first target location to the operation and maintenance object so that the operation and maintenance object can allocate the vehicles for rent according to the first target location.

[0057] In the above embodiment, first, based on the car rental search results of multiple car rental users, a first candidate location is determined among multiple search locations, where the number of cars for rent is less than a second threshold, so as to determine those places where there are search records but fewer cars for rent are found; then, a first target location with an appearance frequency greater than a third threshold is determined at the first candidate location, so as to determine those places where there are fewer cars for rent but high-frequency searches occur, so that operation and maintenance personnel can allocate cars for rent to the first target location to achieve optimal allocation of resources.

[0058] In some embodiments, the above steps S202 to S208 may be executed according to a target period, and after each execution is completed, the car rental search result information of multiple car rental users may be deleted.

[0059] Through the above periodic execution and deletion operations, it is possible to periodically send locations with fewer car models but more search records to operation and maintenance personnel to optimize car rental resources in a timely manner; and to delete used data in a timely manner to reduce memory usage.

[0060] The purpose of this embodiment is to provide an optimization solution for the case where the model inventory is low when the user searches for the model on the platform, so as to solve the problem that the model inventory is low or no model is displayed when the user searches for the model on the platform.

[0061] Figure 3 The figure is a flow chart showing a data processing method according to an exemplary embodiment.

[0062] refer to Figure 3 , the above data processing method may include the following steps.

[0063] Step S302 : collecting car rental search result information of a plurality of car rental users, wherein each car rental search result information includes a search location and a vehicle for rent, wherein the distance between the vehicle for rent and the search location is less than a first threshold.

[0064] Step S304: determining a first candidate location where the number of available rental vehicles is less than a second threshold value from among the multiple search locations based on the vehicles for rent in the rental search result information of the multiple car rental users.

[0065] Step S306 : determining a first target position in the first candidate positions, the first target position having an appearance number greater than a third threshold.

[0066] Step S308: sending the first target location to the operation and maintenance object so that the operation and maintenance object can allocate the vehicles for rent according to the first target location.

[0067] Step S310 , based on the vehicles for rent in the car rental search result information of the plurality of car rental users, determine a second candidate location where the number of vehicles for rent is less than a fourth threshold value from the plurality of search locations.

[0068] In some embodiments, the number of available rental vehicles pushed to the user in the car rental search results may be counted, and a second candidate location where the number of available rental vehicles is less than a fourth threshold is determined from the multiple search locations based on the car rental search results. It is understood that the first candidate location and the second candidate location may be the same or different.

[0069] Step S312: determining a second target position whose number of appearances is greater than a fifth threshold value in the second candidate positions.

[0070] Step S314: Send the second target location to the operation and maintenance object so that the operation and maintenance object can allocate the vehicle for rent according to the second target location.

[0071] In the above embodiment, first, based on the car rental search results of multiple car rental users, a first candidate location is determined in multiple search locations where the number of cars to be rented is less than a second threshold, or a second candidate location is determined where the number of cars to be rented is less than a fourth threshold, so as to determine those places where there are search records but fewer cars to be rented or fewer cars to be rented are found; then a first target location whose appearance frequency is greater than a third threshold is determined at the first candidate location, or a second target location whose appearance frequency is greater than a fifth threshold is determined at the second candidate location, so as to determine those places where there are fewer cars to be rented but high-frequency searches occur, so that operation and maintenance personnel can allocate cars to be rented to the first target location or the second target location to achieve optimal allocation of resources.

[0072] In some embodiments, the above steps S302 to S314 may be executed according to a target period, and after each execution is completed, the car rental search result information of multiple car rental users may be deleted.

[0073] Through the above periodic execution and deletion operations, it is possible to periodically send locations with fewer car models but more search records to operation and maintenance personnel to optimize car rental resources in a timely manner; and to delete used data in a timely manner to reduce memory usage.

[0074] The purpose of this embodiment is to provide an optimization solution for the case where the model inventory is small when the user queries the model on the platform, so as to solve the problem that the model inventory is small or no model is displayed when the user searches for the model on the platform.

[0075] Figure 4 The figure is a flow chart showing a data processing method according to an exemplary embodiment.

[0076] In some embodiments, each car rental search result information may include a user identifier.

[0077] refer to Figure 4 , the above data processing method may include the following steps.

[0078] Step S402 : collecting car rental search result information of a plurality of car rental users, wherein each car rental search result information includes a search location and a vehicle for rent, wherein the distance between the vehicle for rent and the search location is less than a first threshold.

[0079] Step S404: Deduplication of car rental search results for the same user ID at the same search location is performed based on the search location and the user ID.

[0080] In some embodiments, the above-mentioned search location may include geographic coordinates, and the car rental search result information of multiple car rental users may include first car rental search result information and second car rental search result information. The first car rental search result information may include the first user identifier and the first geographic coordinates, and the second car rental search result information may include the first user identifier and the second geographic coordinates.

[0081] Then, based on the search location and user ID, deduplication processing of the car rental search result information with the same user ID at the same search location may include: determining that the user ID in the first car rental search result information is the same as the user ID in the second car rental search result information; determining that the distance between the first geographic coordinates in the first car rental search result information and the second geographic coordinates in the second car rental search result information is less than a sixth threshold (for example, 10 meters, 20 meters, etc.), then determining that the first car rental search result information and the second car rental search result information are car rental search result information with the same user ID at the same search location; and deduplication processing of the first car rental search result information and the second car rental search result information.

[0082] In some other embodiments, the search location may include a search address name, and the car rental search result information of multiple car rental users includes third car rental search result information and fourth car rental search result information, the third car rental search result information includes the second user identifier and the third search address name, and the fourth car rental search result information includes the second user identifier and the fourth search address name; then, based on the search location and user identifier, deduplication processing of the car rental search result information with the same user identifier in the same search location may include: determining that the user identifier in the third car rental search result information is the same as the user identifier in the fourth car rental search result information; determining that the third search address name in the third car rental search result information is the same as the fourth search address name in the fourth car rental search result information, then determining that the third car rental search result information and the fourth car rental search result information are car rental search result information with the same user identifier in the same search location; and deduplication processing of the third car rental search result information and the fourth car rental search result information.

[0083] The above method can be used to delete the car rental search results of the same user at the same location (or a nearby location) to avoid the same user constantly searching at the same location, thereby avoiding deploying vehicles to places with few vehicles but also few users.

[0084] Step S406: determining a first candidate location where the number of available rental vehicles is less than a second threshold value from among the multiple search locations based on the available rental vehicles in the rental search result information of the multiple rental users.

[0085] Step S408: Determine a first target position in the first candidate positions whose number of appearances is greater than a third threshold.

[0086] Step S410: sending the first target location to the operation and maintenance object so that the operation and maintenance object can allocate the vehicles for rent according to the first target location.

[0087] Through the above embodiment, the search records of the same user at the same or similar locations can be deduplicated, so that the operation and maintenance personnel only consider the search records of the same user at the same location (or similar location) once when optimizing the allocation of vehicles for rent, thereby improving the optimization effect.

[0088] Figure 5 The figure is a flow chart showing a data processing method according to an exemplary embodiment.

[0089] refer to Figure 5 , the above data processing method may include the following steps.

[0090] Step S502: The user uses the application to search for rental car model information.

[0091] Step S504: Data collection and reporting to the database.

[0092] First, it is necessary to collect the vehicle model data at the user's filtered address.

[0093] After the user selects the city, address, and pick-up and return time to search, the front end of the application will add a data information collection log and store the collected log in the database table. The data collected in the log includes the user's unique identifier, city name, address name, address geographic location coordinates, and number of car models.

[0094] Step S506, data processing interval.

[0095] The previously collected and uploaded data will be sorted every 7 days. After sorting, all data before 0:00:00 on the sorting day will be deleted. When new statistical data is sorted, the previous analysis results will be cleared.

[0096] Step S508: data organization and analysis.

[0097] For the data collected within 7 days, at 0:00 on the 8th day, data screening is performed based on the condition that the number of vehicle models is less than 10 (or the number of vehicles is less than 10). The sorted data is then summarized and organized based on the address and geographic location. Addresses with the same geographic location coordinates are deduplicated by user unique identifier (the same user unique identifier is only counted once) and the number of occurrences is added up. The sorted data includes the following content: city name, address name, address geographic location coordinates, number of vehicle models, and number of occurrences. These data are stored in a database table in descending order of occurrence.

[0098] Step S510: Send a notification to the platform operator.

[0099] Based on the sorted data results, the top 30 city addresses with the highest frequency of occurrence will be notified to the platform operators via email.

[0100] Step S512: adjust store addresses, add new stores, and increase store service areas.

[0101] In this embodiment, the number of car models and stores that appear after the user queries the platform is collected and uploaded, and then the collected data is analyzed and sorted every 7 days. The address information with no car models or few car models is extracted, and the number of times the same address appears is calculated. The addresses with more appearances are sent to the platform operators in the form of emails, providing data support for the platform operators to adjust the car model inventory and select store addresses.

[0102] Based on the same inventive concept, the present disclosure also provides a data processing device, such as the following embodiment. Since the principle of solving the problem in the device embodiment is similar to that in the above method embodiment, the implementation of the device embodiment can refer to the implementation of the above method embodiment, and the repeated parts will not be repeated.

[0103] Figure 6 FIG. 1 is a block diagram of a data processing device according to an exemplary embodiment. Figure 6 The data processing device 600 provided in the embodiment of the present disclosure may include: a data collection module 601, a candidate position determination module 602, a target position determination module 603 and a data sending module 604.

[0104] Among them, the data collection module 601 can be used to collect car rental search result information of multiple car rental users, wherein each car rental search result information includes a search location and a vehicle to be rented, wherein the distance between the vehicle to be rented and the search location is less than a first threshold; the candidate location determination module 602 can be used to determine a first candidate location whose number of vehicles to be rented is less than a second threshold among multiple search locations based on the vehicles to be rented in the car rental search result information of multiple car rental users; the target location determination module 603 can be used to determine a first target location whose number of occurrences is greater than a third threshold among the first candidate locations; the data sending module 604 can be used to send the first target location to the operation and maintenance object, so that the operation and maintenance object can allocate vehicles to be rented according to the first target location.

[0105] It should be noted that the data collection module 601, candidate location determination module 602, target location determination module 603, and data transmission module 604 described above correspond to S202 to S208 in the method embodiment. The examples and application scenarios implemented by these modules and corresponding steps are the same, but are not limited to the contents disclosed in the method embodiment described above. It should be noted that the above modules, as part of the apparatus, can be executed in a computer system, such as a set of computer-executable instructions.

[0106] In some embodiments, the method further includes: a second candidate position determination module, a second target position determination module, and a second push module.

[0107] Among them, the second candidate location determination module can be used to determine a second candidate location with fewer than a fourth threshold number of vehicles to be rented among multiple search locations based on the vehicles to be rented in the rental search result information of multiple car rental users; the second target location determination module can be used to determine a second target location with a number of appearances greater than a fifth threshold among the second candidate locations; the second push module can be used to send the second target location to the operation and maintenance object so that the operation and maintenance object can allocate vehicles to be rented according to the first target location.

[0108] In some embodiments, each car rental search result information includes a user identifier; the data processing device may further include a deduplication module. The deduplication module may be configured to, before determining a first candidate location in a plurality of search locations where the number of available rental vehicles in the car rental search result information of multiple car rental users is less than a second threshold, perform deduplication processing on the car rental search result information for the same user identifier at the same search location based on the search location and the user identifier.

[0109] In some embodiments, the search location includes geographic coordinates, and the car rental search result information of multiple car rental users includes first car rental search result information and second car rental search result information, the first car rental search result information includes a first user identifier and a first geographic coordinate, and the second car rental search result information includes a first user identifier and a second geographic coordinate; wherein the deduplication module may include: a first user identifier matching unit, a distance determination unit, and a first deduplication unit.

[0110] Among them, the first user identification matching unit can be used to determine that the user identification in the first car rental search result information is the same as the user identification in the second car rental search result information; the distance determination unit can be used to determine that the distance between the first geographic coordinates in the first car rental search result information and the second geographic coordinates in the second car rental search result information is less than a sixth threshold, and then determine that the first car rental search result information and the second car rental search result information are car rental search result information with the same user identification at the same search location; the first deduplication unit can be used to deduplicate the first car rental search result information and the second car rental search result information.

[0111] In some embodiments, the search location includes a search address name, and the car rental search result information of multiple car rental users includes third car rental search result information and fourth car rental search result information, the third car rental search result information includes the second user identifier and the third search address name, and the fourth car rental search result information includes the second user identifier and the fourth search address name; wherein, the deduplication module may include: a second user identifier matching unit, an address name matching unit and a second deduplication unit.

[0112] Among them, the second user identification matching unit can be used to determine that the user identification in the third car rental search result information is the same as the user identification in the fourth car rental search result information; the address name matching unit can be used to determine that the third search address name in the third car rental search result information is the same as the fourth search address name in the fourth car rental search result information, and then determine that the third car rental search result information and the fourth car rental search result information are car rental search result information with the same user identification at the same search location; the second deduplication unit can be used to deduplicate the third car rental search result information and the fourth car rental search result information.

[0113] In some embodiments, the data processing apparatus may further include: a periodic execution module and a deletion module.

[0114] Among them, the periodic execution module is used to control the periodic operation of modules other than the periodic execution module in the above-mentioned data processing device; the deletion module is used to delete the car rental search result information of multiple car rental users after each cycle is completed.

[0115] Since the functions of the apparatus 600 have been described in detail in the corresponding method embodiments, they will not be described in detail herein.

[0116] The modules and / or units described in the embodiments of the present application may be implemented in software or hardware. The modules and / or units described may also be provided in a processor. The names of these modules and / or units do not, in certain circumstances, limit the modules and / or units themselves.

[0117] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, program segment, or a part of code, and the above-mentioned module, program segment, or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of the boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs the specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0118] Furthermore, the figures above are merely illustrative of the processes included in the methods according to exemplary embodiments of the present disclosure and are not intended to be limiting. It is readily understood that the processes illustrated in the figures above do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0119] Figure 7 Schematic diagram of the structure of an electronic device suitable for implementing the embodiment of the present disclosure is shown. Figure 7 The electronic device 700 shown is only an example and should not limit the functions and scope of use of the embodiments of the present disclosure.

[0120] like Figure 7As shown, electronic device 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes according to programs stored in a read-only memory (ROM) 702 or programs loaded from a storage unit 708 into a random access memory (RAM) 703. Various programs and data required for the operation of electronic device 700 are also stored in RAM 703. CPU 701, ROM 702, and RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to bus 704.

[0121] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, mouse, and the like; an output section 707 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and speakers; a storage section 708 including devices such as a hard disk; and a communication section 709 including a network interface card such as a LAN card or a modem. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. Removable media 711, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 710 as needed, so that computer programs read from the media can be installed in the storage section 708 as needed.

[0122] In particular, according to embodiments of the present disclosure, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer-readable storage medium, the computer program containing program code for executing the methods illustrated in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via the communication section 709 and / or installed from removable media 711. When executed by the central processing unit (CPU) 701, the computer program performs the aforementioned functions defined in the system of the present application.

[0123] It should be noted that the computer-readable storage medium described in this disclosure may be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. This propagated data signal may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable storage medium other than a computer-readable storage medium that can transmit, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code contained on a computer-readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wireline, optical cable, RF, or any suitable combination thereof.

[0124] As another aspect, the present application also provides a computer-readable storage medium, which may be included in the device described in the above embodiment; or it may exist independently and not be assembled into the device. The above computer-readable storage medium carries one or more programs. When the above one or more programs are executed by a device, the device can implement functions including: collecting car rental search result information of multiple car rental users, wherein each car rental search result information includes a search location and a vehicle for rent, wherein the distance between the vehicle for rent and the search location is less than a first threshold; based on the vehicles for rent in the car rental search result information of the multiple car rental users, determining a first candidate location with a number of vehicles for rent less than a second threshold from multiple search locations; determining a first target location with a number of occurrences greater than a third threshold from the first candidate location; and sending the first target location to an operation and maintenance object so that the operation and maintenance object can allocate the vehicle for rent based on the first target location.

[0125] According to one aspect of the present application, a computer program product or computer program is provided, the computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods provided in various optional implementations of the above-described embodiments.

[0126] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution of the embodiment of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.), including a number of instructions for enabling a computing device (which can be a personal computer, a server, a mobile terminal, or a smart device, etc.) to execute the method according to the embodiment of the present disclosure, for example Figures 2 to 5 in one or more of the steps shown.

[0127] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the disclosure herein. This disclosure is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not claimed herein. The specification and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the claims.

[0128] It should be understood that the present disclosure is not limited to the detailed structures, drawings or implementations shown herein, but rather is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A data processing method, characterized in that: include: Collecting car rental search result information of a plurality of car rental users, wherein each car rental search result information includes the user's search location and a vehicle for rent, wherein the vehicle for rent is a vehicle whose distance from the user's search location is less than a first threshold or a vehicle in a store whose distance from the user's search location is less than the first threshold; The vehicle to be rented includes model information; Counting the number of car models pushed to the user in each car rental search result information, to determine a first candidate location where the number of car models for rent is less than a second threshold value among the multiple search locations corresponding to the multiple car rental search result information; Determining a first target position in the first candidate positions, the first target position having a search frequency greater than a third threshold; Sending the first target location to an operation and maintenance object so that the operation and maintenance object can allocate the vehicle for rent according to the first target location; Counting the number of vehicles for rent pushed to the user in each of the vehicle rental search result information, to determine a second candidate location where the number of vehicles for rent is less than a fourth threshold value among the multiple search locations corresponding to the multiple vehicle rental search result information; Determine, among the second candidate positions, a second target position whose search frequency is greater than a fifth threshold; The second target location is sent to an operation and maintenance object so that the operation and maintenance object can allocate vehicles for rent according to the first target location.

2. The method according to claim 1, characterized in that Each car rental search result information includes a user identifier; and before counting the number of car models pushed to the user in each car rental search result information to determine a first candidate location having a number of car models for rent less than a second threshold among multiple search locations corresponding to the multiple car rental search result information, the method includes: According to the search location and the user identifier, duplicate car rental search result information for the same user identifier at the same search location is deduplicated.

3. The method according to claim 2, characterized in that The search location includes geographic coordinates, the car rental search result information of the multiple car rental users includes first car rental search result information and second car rental search result information, the first car rental search result information includes a first user identifier and a first geographic coordinate, and the second car rental search result information includes the first user identifier and the second geographic coordinates; wherein, based on the search location and the user identifier, deduplication processing is performed on the car rental search result information for the same user identifier at the same search location, including: Determining that the user identifier in the first car rental search result information is the same as the user identifier in the second car rental search result information; Determining that a distance between the first geographic coordinates in the first car rental search result information and the second geographic coordinates in the second car rental search result information is less than a sixth threshold, then determining that the first car rental search result information and the second car rental search result information are car rental search result information for the same user identifier and the same search location; Deduplication processing is performed on the first car rental search result information and the second car rental search result information.

4. The method according to claim 2, characterized in that The search location includes a search address name, the car rental search result information of the multiple car rental users includes third car rental search result information and fourth car rental search result information, the third car rental search result information includes a second user identifier and a third search address name, and the fourth car rental search result information includes the second user identifier and a fourth search address name; wherein, based on the search location and the user identifier, deduplication processing is performed on the car rental search result information of the same user identifier at the same search location, including: Determining that the user identifier in the third car rental search result information is the same as the user identifier in the fourth car rental search result information; If it is determined that the third search address name in the third car rental search result information is the same as the fourth search address name in the fourth car rental search result information, then it is determined that the third car rental search result information and the fourth car rental search result information are car rental search result information for the same user identifier and the same search location; Deduplication processing is performed on the third car rental search result information and the fourth car rental search result information.

5. The method according to claim 1, characterized in that: The method further comprises: Execute the method of claim 1 according to the target period; After each execution of the method of claim 1, the car rental search result information of the multiple car rental users is deleted.

6. A data processing device, characterized in that: include: a data collection module configured to collect car rental search result information from a plurality of car rental users, wherein each car rental search result information includes a user's search location and a vehicle for rent, wherein the vehicle for rent is a vehicle whose distance from the user's search location is less than a first threshold or a vehicle in a store whose distance from the user's search location is less than the first threshold; The vehicle to be rented includes model information; a candidate location determination module, configured to count the number of car models pushed to the user in each car rental search result information, so as to determine a first candidate location where the number of car models for rent is less than a second threshold value among the multiple search locations corresponding to the multiple car rental search result information; a target position determining module, configured to determine a first target position having a search frequency greater than a third threshold value among the first candidate positions; a data sending module, configured to send the first target location to an operation and maintenance entity, so that the operation and maintenance entity can allocate vehicles for rent according to the first target location; a second candidate location determination module configured to count the number of vehicles for rent pushed to the user in each vehicle rental search result information, so as to determine a second candidate location where the number of vehicles for rent is less than a fourth threshold value from among the multiple search locations corresponding to the multiple vehicle rental search result information; A second target position determining module, configured to determine a second target position having a search frequency greater than a fifth threshold value in the second candidate positions; The second push module is used to send the second target location to the operation and maintenance object so that the operation and maintenance object can allocate the rental vehicle according to the first target location.

7. An electronic device, characterized in that: include: Memory; as well as A processor coupled to the memory, wherein the processor is configured to execute the data processing method according to any one of claims 1 to 5 based on instructions stored in the memory.

8. A computer-readable storage medium having program instructions stored thereon, wherein the program instructions, when executed by a processor, implement the data processing method according to any one of claims 1 to 5.

9. A computer program product comprising computer instructions stored in a computer-readable storage medium, wherein: When the computer instructions are executed by a processor, the method according to any one of claims 1 to 5 is implemented.

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