Systems and methods for providing information for online to offline service

The present disclosure relates to a system, method and non-transitory computer readable medium. The system includes at least one computer-readable storage medium including a set of instructions and at least one processor in communication with the at least one computer-readable storage medium. When executing the set of instructions, the at least one processor is directed to: receive a triggering event in the absence of input from a user terminal associated with a user; obtain one or more candidate destinations based on the triggering event; obtain a trained ranking model; determine a ranking result of the one or more candidate destinations based on the trained ranking model; and transmit the ranking result to the user terminal in response to the triggering event.

TECHNICAL FIELD

The present disclosure generally relates to a system and method for providing information for an online to offline service, and in particular, to a system and method for providing a plurality of ranked destinations in the absence of input for an online to offline service request.

BACKGROUND

Online to offline services are becoming more and more popular. A user of the online to offline services may input a destination to initial a service order, for example, ordering a meal at a restaurant, taking a taxi to a place. In order to improve user experience, it may be desirable to generate a plurality of candidate destinations in the absence of the user input.

SUMMARY

According to an aspect of the present disclosure, a system may include at least one storage device including a set of instructions; and at least one processor in communication with the at least one storage device. When executing the set of instructions, the at least one processor is configured to cause the system to receive a triggering event in the absence of input from a user terminal associated with a user; obtain one or more candidate destinations based on the triggering event; obtain a trained ranking model; determine a ranking result of the one or more candidate destinations based on the trained ranking model; and transmit the ranking result to the user terminal in response to the triggering event.

In some embodiments, to obtain the one or more candidate destinations, the at least one processor may be further configured to cause the system to obtain a current location of the user terminal; obtain one or more historical records associated with the user, the one or more historical records including at least a historical order or a historical query; and obtain the one or more candidate destinations based on the one or more historical records and the current location of the user terminal.

In some embodiments, the trained ranking model may be generated based on a training process. The training process may include obtaining a plurality of primary historical records, the primary historical record including a primary historical order or a primary historical query; for each of the plurality of primary historical records, determining a plurality of secondary historical records, and determining a primary destination group corresponding to the each of the primary historical records; obtaining a preliminary ranking model; determining, based on the preliminary ranking model, a plurality of sample ranking results for the primary destination groups corresponding to the plurality of primary historical records; obtaining a plurality of primary actual destinations corresponding to the plurality of primary historical records; determining whether the plurality of sample ranking results satisfy a condition based on the plurality of primary actual destinations; and designating, based on a result of the determination that the plurality of ranking results satisfy the condition, the preliminary ranking model as the trained ranking model. The secondary historical record may include a secondary historical order or a secondary historical query. The primary destination group may include a plurality of primary candidate destinations based on the plurality of secondary historical records.

In some embodiments, determining the plurality of sample ranking results may include, for each of the plurality of primary candidate destinations of the primary destination group corresponding to the each of the plurality of primary historical records, extracting one or more features associated with the each of the plurality of primary candidate destinations; assigning one or more preliminary weighting coefficients to the extracted one or more features; and determining, based on the one or more features and the one or more preliminary weighting coefficients, a preliminary weighted value corresponding to the each of the plurality of the primary candidate destinations; and determining, based on the determined preliminary weighted values corresponding to the plurality of primary candidate destinations, a sample ranking result for the each of the primary historical records.

In some embodiments, the training process may further include updating, based on a result of the determination that the plurality of sample ranking results fail to satisfy the condition, the one or more preliminary weighting coefficients of the preliminary ranking model.

In some embodiments, each of the plurality of primary historical records may correspond to a primary start time point or a primary start location. The primary start time point may include a time point when the primary historical order is sent or a time point when the primary historical query is executed. The primary start location may include a location where the primary historical order is sent or a location where the primary historical query is executed. Each of the plurality of secondary historical records may correspond to a secondary start time point. The secondary start time point may include a time point when the secondary historical order is sent or a time point when the secondary historical query is executed. The one or more features associated with the each of the plurality of primary candidate destinations of the each of the plurality of the primary historical records include at least one of a distance between the primary start location of the each of the plurality of the primary historical records and the primary candidate destination of the each of the plurality of the primary historical records; a time interval between the primary start time point of the each of the plurality of the primary historical records and the secondary start time point corresponding to the primary candidate destination of the each of the plurality of the primary historical records; or an occurrence frequency of the primary candidate destination of the each of the plurality of the primary historical records in the plurality of secondary historical records in a time period.

In some embodiments, the preliminary ranking model may include a Lambdarank model.

According to an aspect of the present disclosure, a method implemented on a computing device having at least one processor, at least one computer-readable storage medium, and a communication platform connected to a network may include: receiving a triggering event in the absence of input from a user terminal associated with a user; obtaining one or more candidate destinations based on the triggering event; obtaining a trained ranking model; determining a ranking result of the one or more candidate destinations based on the trained ranking model; and transmitting the ranking result to the user terminal in response to the triggering event.

According to an aspect of the present disclosure, a non-transitory computer readable medium may include instructions configured to cause a computing system to: receive a triggering event in the absence of input from a user terminal associated with a user; obtain one or more candidate destinations based on the triggering event; obtain a trained ranking model; determine a ranking result of the one or more candidate destinations based on the trained ranking model; and transmit the ranking result to the user terminal in response to the triggering event.

DETAILED DESCRIPTION

The terms “passenger,” “requestor,” “service requestor,” and “user” in the present disclosure are used interchangeably to refer to an individual, an entity, or a tool that may request or order a service. Also, the term “driver,” “provider,” and “service provider” in the present disclosure are used interchangeably to refer to an individual, an entity, or a tool that may provide a service or facilitate the providing of the service.

The terms “service request,” “request for a service,” “requests,” “order,” and “service order” in the present disclosure are used interchangeably to refer to a request that may be initiated by a passenger, a service requestor, a user, a driver, a provider, a service provider, or the like, or any combination thereof. The service request may be accepted by any one of a passenger, a service requestor, a user, a driver, a provider, or a service provider. The service request may be chargeable or free.

The term “service provider terminal” in the present disclosure is used to refer to a mobile terminal that is used by a service provider to provide a service or facilitate the providing of the service. The term “user terminal” in the present disclosure is used to refer to a mobile terminal that is used by a service requestor to request or order a service.

It will be understood that, while the system and method in the present disclosure are described primarily in regard to determining a ranking of one or more candidate destinations of a transportation service, it should also be understood that the present disclosure is not intended to be limiting. The system or method of the present disclosure may be applied to any other kind of service. For example, the system or method of the present disclosure may be applied to search engines, digital map applications, navigation systems, etc. The search engines, digital map applications, or navigation systems may use the system and the method provided herein to rank the search results, locations, or destinations, etc. As another example, the system or method of the present disclosure may be applied to transportation systems of different environments including land, ocean, aerospace, or the like, or any combination thereof. The vehicle of the transportation systems may include a taxi, a private car, a hitch, a bus, a train, a bullet train, a high speed rail, a subway, a vessel, an aircraft, a spaceship, a hot-air balloon, a driverless vehicle, or the like, or any combination thereof. The transportation system may also include any transportation system for management, for example, a system for sending and/or receiving an express. The application of the system or method of the present disclosure may be implemented on a user device and include a webpage, a plug-in of a browser, a client terminal, a custom system, an internal analysis system, an artificial intelligence robot, or the like, or any combination thereof.

Moreover, a system and method for providing at least one ranked candidate destination in the absence of a user input are provided. To be specific, the system may receive a triggering event in the absence of input from a user. Then, the system may determine one or more candidate destinations based on the triggering event. Further, the system may determine a ranking result of the one or more candidate destinations based on a trained ranking model, and transmit the ranking result to the user. Thus, the efficiency of the transportation service is enhanced, and the user experience is also improved.

It should be noted that online to offline transportation service, such as online to offline taxi-hailing service, is a new form of service rooted only in post-Internet era. It provides technical solutions to users and service providers that could raise only in post-Internet era. In pre-Internet era, a user may receive a special offer such as a discount related to a service from newspapers, television advertisements, telephone calls, or leaflets. It is difficult to inform users of the special offer related to the service in time. In addition, the coverage area of users of the traditional methods of special offer recommendation in pre-Internet era is limited. Online to offline service system, however, recommends special offers to larger numbers of users via Internet and ensure that users will not miss the special offers. Therefore, through Internet, the online to offline service systems may provide a much more efficient and accurate recommendation platform for users that may never met in pre-Internet era.

FIG.1illustrates an exemplary network environment of providing an online to offline service according to some embodiments. An online to offline service system100may be an online to offline transportation service platform implemented in a network environment for providing transportation services. The online to offline service system100may include a server110, a network120, a user terminal130, a service provider terminal140, and a storage150.

The online to offline service system100may provide a plurality of services. Exemplary online to offline service may include a taxi hailing service, a chauffeur service, an express car service, a carpool service, a bus service, a driver hire service, and a shuttle service. In some embodiments, an online to offline service may be provided with supplementary information recommended to perform the online to offline service. The order types may include a taxi order, a luxury car order, an express car order, a bus order, a shuttle order, etc. In some embodiments, the service may be any on-line service, such as booking a meal, shopping, or the like, or a combination thereof.

The server110may be a computer server. The server110may communicate with the user terminal130and/or the service provider terminal140to provide various functions of an online to offline service. In some embodiments, the server110may be a single server or a server group. The server group may be a centralized server group connected to the network120via an access point or a distributed server group connected to the network120via one or more access points, respectively. In some embodiments, the server110may be locally connected to the network120or in remote connection with the network120. For example, the server110may access information and/or data stored in the user terminal130, the service provider terminal140, and/or the storage150via the network120. As another example, the storage150may serve as backend data storage of the server110. In some embodiments, the server110may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof. In some embodiments, the server110may be implemented on a computing device200having one or more components illustrated inFIG.2in the present disclosure.

In some embodiments, the server110may include a processing engine112. The processing engine112may process information and/or data related to performing one or more functions described in the present disclosure. For example, the processing engine112may determine one or more candidate destinations associated with a user. As another example, the processing engine112may train a ranking model for the one or more candidate destinations. As still another example, the processing engine112may determine a ranking result of the one or more candidate destinations based on the ranking model. In some embodiments, the processing engine112may include one or more processing units (e.g., single-core processing engine(s) or multi-core processing engine(s)). Merely by way of example, the processing engine112may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), an application-specific instruction-set processor (ASIP), a graphics processing unit (GPU), a physics processing unit (PPU), a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a controller, a microcontroller unit, a reduced instruction-set computer (RISC), a microprocessor, or the like, or any combination thereof.

The network120may facilitate exchange of information and/or data. In some embodiments, one or more components in the online to offline service system100(e.g., the server110, the user terminal130, the service provider terminal140, the storage150) may send information and/or data to another component (s) in the online to offline service system100via the network120. For example, the server110may access and/or obtain a plurality of historical records from the storage150via the network120. The historical records may include historical orders and/or historical queries. As another example, the server110may transmit a ranking result of the one or more candidate destinations to the user terminal130. In some embodiments, the network120may be any type of wired or wireless network, or combination thereof. Merely by way of example, the network120may include a cable network, a wireline network, an optical fiber network, a tele communications network, an intranet, an Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a wide area network (WAN), a public telephone switched network (PSTN), a Bluetooth network, a ZigBee network, a near field communication (NFC) network, or the like, or any combination thereof. In some embodiments, the network120may include one or more network access points. For example, the network120may include wired or wireless network access points such as base stations and/or internet exchange points120-1,120-2, . . . , through which one or more components of the online to offline service system100may be connected to the network120to exchange data and/or information.

The user terminal130may include a mobile device130-1, a tablet computer130-2, a laptop computer130-3, a built-in device in a vehicle130-4, or the like, or any combination thereof. In some embodiments, the mobile device130-1may include a smart home device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home device may include a smart lighting device, a control device of an intelligent electrical apparatus, a smart monitoring device, a smart television, a smart video camera, an interphone, or the like, or any combination thereof. In some embodiments, the wearable device may include a smart bracelet, a smart footgear, smart glass, a smart helmet, a smart watch, smart clothing, a smart backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the smart mobile device may include a smartphone, a personal digital assistant (PDA), a gaming device, a navigation device, a point of sale (POS) device, or the like, or any combination thereof. In some embodiments, the virtual reality device and/or the augmented reality device may include a virtual reality helmet, a virtual reality glass, a virtual reality patch, an augmented reality helmet, an augmented reality glass, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device and/or the augmented reality device may include a Google Glass™, an Oculus Rift™, a Hololens™, a Gear VR™, etc. In some embodiments, a built-in device in the vehicle130-4may include a built-in computer, an onboard built-in television, a built-in tablet, etc. In some embodiments, the user terminal130may include a signal transmitter and a signal receiver configured to communicate with a positioning system for locating the position of the passenger and/or the user terminal130. In some embodiments, the positioning system may be a global positioning system (GPS), a global navigation satellite system (GLONASS), a compass navigation system (COMPASS), a BeiDou navigation satellite system, a Galileo positioning system, a quasi-zenith satellite system (QZSS), etc.

In some embodiments, the user terminal130may be owned by a passenger. In some embodiments, the user terminal130may be owned by someone other than the passenger. For example, an owner A of the user terminal130may use the user terminal130to send a service request for a passenger B, and/or receive a service confirmation and/or information or instructions from the server110. It should be understood that, in some embodiments, “passenger” and “user terminal” may be used interchangeably, and “driver” and “service provider terminal” may be used interchangeably.

In some embodiments, the service provider terminal140may include a plurality of service provider terminals140-1,140-2, . . . ,140-n. In some embodiments, the service provider terminal140may be similar to, or the same device as the user terminal130. In some embodiments, the service provider terminal140may be customized to implement the online to offline transportation service. In some embodiments, the service provider terminal140and the user terminal130may be configured with a signal transmitter and a signal receiver to receive position information of the service provider terminal140and the user terminal130from a positioning system.

In some embodiments, the service provider terminal140may be used by a driver. In some embodiments, the service provider terminal140may be used by someone other than the driver. For example, a user C of the service provider terminal140may use the service provider terminal140to receive a service request for a driver D, and/or information or instructions from the server110. In some embodiments, a driver may be assigned to use one of the service provider terminal140for at least a certain period of time, for example, a day, a week, a month, or a year, etc. In some other embodiments, a driver may be assigned to use one of the service provider terminal140on a random basis. For example, when a driver is available to provide an online to offline service, he/she may be assigned to use a driver terminal that receives the earliest request and a vehicle that is recommended to perform the type of online to offline service. In some embodiments, the service provider terminal140may be associated with one or more drivers (e.g., a night-shift driver, a day-shift driver, or a driver pool by a random shifting).

The storage150may store data and/or instructions. The data may include data related to a plurality of historical orders, data related to a plurality of destinations, data related to a plurality of users, data related to a plurality of drivers, data related to the external environment, etc. The data related to the historical orders may include historical start locations, historical start time points, historical destinations, etc. The data related to the plurality of destinations may include names of the destinations, descriptions of the destinations, locations of the destinations, comments of the destinations, etc. The data related to the users may include user profiles. The data related to the drivers may include driver profiles. The data related to the external environment may include weather conditions, road conditions, etc. In some embodiments, the storage150may store data obtained from the user terminal130and/or the service provider terminal140. For example, the storage150may store log information associated with the user terminal130. In some embodiments, the storage150may store data and/or instructions that the server110may execute to provide the online to offline services described in the present disclosure. In some embodiments, storage150may include a mass storage, removable storage, a volatile read-and-write memory, a read-only memory (ROM), or the like, or any combination thereof. Exemplary mass storage may include a magnetic disk, an optical disk, a solid-state drive, etc. Exemplary removable storage may include a flash drive, a floppy disk, an optical disk, a memory card, a zip disk, a magnetic tape, etc. Exemplary volatile read-and-write memory may include a random access memory (RAM). Exemplary RAM may include a dynamic RAM (DRAM), a double date rate synchronous dynamic RAM (DDR SDRAM), a static RAM (SRAM), a thyristor RAM (T-RAM), and a zero-capacitor RAM (Z-RAM), etc. Exemplary ROM may include a mask ROM (MROM), a programmable ROM (PROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a compact disk ROM (CD-ROM), and a digital versatile disk ROM, etc. In some embodiments, the storage150may be implemented on a cloud platform. Merely by way of example, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an inter-cloud, a multi-cloud, or the like, or any combination thereof.

In some embodiments, one or more components in the online to offline service system100may access the data or instructions stored in the storage150via the network120. In some embodiments, the storage150may be directly connected to the server110as a backend storage.

In some embodiments, one or more components in the online to offline service system100(e.g., the server110, the user terminal130, the service provider terminal140) may have permissions to access the storage150. In some embodiments, one or more components in the online to offline service system100may read and/or modify the information related to the passenger, the driver, and/or the vehicle when one or more conditions are met. For example, the server110may read and/or modify one or more passengers' user profile after an online to offline service order is completed.

In some embodiments, information exchanging between one or more components of the online to offline service system100may be initiated by a triggering event, for example, by way of launching the mobile application of the online to offline services on the user terminal130, requesting a service order, initiating a query, or other operation of the mobile application on the user terminal (e.g., clicking an input box). The object of the service request may be any product. In some embodiments, the product may include food, medicine, commodity, chemical product, electrical appliance, clothing, car, housing, luxury, or the like, or any combination thereof. In some other embodiments, the product may include a service product, a financial product, a knowledge product, an internet product, or the like, or any combination thereof. The internet product may include an individual host product, a web product, a mobile internet product, a commercial host product, an embedded product, or the like, or any combination thereof. The mobile internet product may be used in a software of a mobile terminal, a program, a system, or the like, or any combination thereof. The mobile terminal may include a tablet computer, a laptop computer, a mobile phone, a personal digital assistant (PDA), a smartwatch, a point of sale (POS) device, an onboard computer, an onboard television, a wearable device, or the like, or any combination thereof. For example, the product may be any software and/or application used on the computer or mobile phone. The software and/or application may relate to socializing, shopping, transporting, entertainment, learning, investment, or the like, or any combination thereof. In some embodiments, the software and/or application related to transporting may include a traveling software and/or application, a vehicle scheduling software and/or application, a mapping software and/or application, etc. In the vehicle scheduling software and/or application, the vehicle may include a horse, a carriage, a rickshaw (e.g., a wheelbarrow, a bike, a tricycle, etc.), a car (e.g., a taxi, a bus, a private car, etc.), a train, a subway, a vessel, an aircraft (e.g., an airplane, a helicopter, a space shuttle, a rocket, a hot-air balloon, etc.), or the like, or any combination thereof.

One of ordinary skill in the art would understand that when an element of the online to offline service system100performs, the element may perform through electrical signals and/or electromagnetic signals. For example, when a user terminal130processes a task, such as making a determination, ranking a plurality of candidate destinations, the user terminal130may operate logic circuits in its processor to process such task. When the user terminal130sends out a triggering event to the server110, a processor of the user terminal130may generate electrical signals encoding the triggering event. The processor of the user terminal130may then send the electrical signals to an output port. If the user terminal130communicates with the server110via a wired network, the output port may be physically connected to a cable, which may further transmit the electrical signal to an input port of the server110. If the user terminal130communicates with the server110via a wireless network, the output port of the user terminal130may be one or more antennas, which convert the electrical signals to electromagnetic signals. Similarly, a service provider terminal140may process a task through operation of logic circuits in its processor, and receive an instruction and/or service order from the server110via electrical signals or electromagnet signals. Within an electronic device, such as the user terminal130, the service provider terminal140, and/or the server110, when a processor thereof processes an instruction, sends out an instruction, and/or performs an action, the instruction and/or action is conducted via electrical signals. For example, when the processor retrieves a plurality of historical records associated with a user from a storage medium (e.g., the storage150), it may send out electrical signals to a reading device of the storage medium, which may read structured data in the storage medium. The structured data may be transmitted to the processor in the form of electrical signals via a bus of the electronic device. Here, an electrical signal refers to one electrical signal, a series of electrical signals, and/or a plurality of discrete electrical signals.

FIG.2illustrates an exemplary computing device200on which the online to offline service system100can be implemented, according to some embodiments of the present disclosure.

The computing device200may be a general purpose computer or a special purpose computer. Both may be used to implement an on-demand system of the present disclosure. The computing device200may be used to implement any component of the service as described herein. For example, the processing engine112of the server may be implemented on the computing device200, via its hardware, software program, firmware, or a combination thereof. Although only one such computer is shown for convenience, the computer functions related to the service as described herein may be implemented in a distributed manner on a number of similar platforms to distribute the processing load.

The computing device200, for example, may include COM ports250connected to and from a network (e.g., the network120) connected thereto to facilitate data communications. The computing device200may also include a processor220, in the form of one or more processors, for executing program instructions. The exemplary computer platform may include an internal communication bus210, program storage and data storage of different forms, for example, a disk270, and a read-only memory (ROM)230, or a random access memory (RAM)240, for various data files to be processed and/or transmitted by the computer. The exemplary computer platform may also include program instructions stored in the ROM230, the RAM240, and/or another type of non-transitory storage medium to be executed by the processor220. The methods and/or processes of the present disclosure may be implemented as the program instructions. The computing device200also includes an I/O component260, supporting input/output between the computer, the user, and other components therein. The computing device200may also receive programming and data via network communications.

Merely for illustration, only one CPU and/or processor is described in the computing device200. However, it should be noted that the computing device200in the present disclosure may also include multiple CPUs and/or processors, thus operations and/or method steps that are performed by one CPU and/or processor as described in the present disclosure may also be jointly or separately performed by the multiple CPUs and/or processors. For example, the CPU and/or processor of the computing device200may execute both step A and step B. As in another example, step A and step B may also be performed by two different CPUs and/or processors jointly or separately in the computing device200(e.g., the first processor executes step A and the second processor executes step B, or the first and second processors jointly execute steps A and B).

FIG.3illustrates an exemplary mobile device on which the online to offline service can be implemented, according to some embodiments of the present disclosure.

FIG.4illustrates an exemplary processing engine112according to some embodiments of the present disclosure. The processing engine112of the server110may include an acquisition module410, a training module420, a determination module430, and a communication module440. One or more modules in the processing engine112may be implemented by at least one processor, such as the processor220.

The acquisition module410may obtain a triggering event associated with the user terminal130. The triggering event may correspond to a current time point and a current location. The current time point refers to a time point when the triggering event occurs by the user via the user terminal130. The current location refers to a location where the triggering event occurs, e.g., the current location of the user terminal130. In some embodiments, the triggering event may occur in the absence of input. The input may include any input by the user via the user terminal130, for example, a character string, an image, audio. In some embodiments, the triggering event may include a user login of a mobile application of the on-demand devices on the user terminal130, the open or initiation of the mobile application on the user terminal130, a click by the user on the interface (e.g., an input box, a map) of the mobile application, or other suitable operation on the mobile application.

The acquisition module410may obtain one or more historical records. The one or more historical records may include at least a historical order or a historical query (e.g., the latest historical query from the current time point). As used herein, an order (a current order or historical order) refers to a service order initiated by a user, which may be transmitted to and/or accepted by the server120and/or a driver to perform the service associated with the service order. A query (a current query or historical query) refers to a service query initiated by a user to request information regarding a service (e.g., fees, estimated waiting time, estimated time of arrival), which may become an order if the user takes further action via his or her user terminal130(e.g., placing an order based on the query). The historical order may be sent by the user, and the historical query may be executed by the user. In some embodiments, the acquisition module410may obtain the one or more records based on a user of the user terminal130. For example, the acquisition module410may obtain the one or more historical records initialized (e.g., sent, executed) by a specified user of the user terminal130. In some embodiments, the acquisition module410may obtain the one or more historical records based on the triggering event. More particularly, the acquisition module410may obtain the one or more historical records based on the current time point of the triggering event, the current location of the triggering event, or a combination thereof. For example, the acquisition module410may obtain the one or more historical records occurring within a predetermined time range from the current time point of the triggering event. The predetermined time range may include one week, one month, two months, three months, or other time periods. Alternatively or additionally, the acquisition module410may obtain the one or more historical records whose destinations exceed a predetermined geographical range from the current location of the triggering event. The predetermined geographical range may include 100 meters, 500 meters, 1000 meters, or other geographical ranges. Alternatively or additionally, the acquisition module410may obtain the one or more historical records occurring within a predetermined time range (e.g., 30 days) from the current time point of the triggering event and having a destination exceeding a predetermined geographical range (e.g., 1000 meters) from the current location of the triggering event.

For an obtained triggering event, the acquisition module410may also obtain one or more candidate destinations. A candidate destination refers to a destination in which the user of an online to offline service is probably interested at the current time point of the triggering event. In some embodiments, the acquisition module410may obtain the one or more candidate destinations based on one or more obtained historical records. For example, the acquisition module410may extract an actual destination of an obtained historical record as a candidate destination.

The training module420may obtain a trained ranking model. The trained ranking model may rank the one or more obtained candidate destinations. The trained ranking model may include a learning-to-rank (LTR) model, for example, a Lambdarank model. In some embodiments, the trained ranking model may be determined by training a preliminary ranking model using a vast of training data (e.g., a plurality of historical records).

In some embodiments, the training module420may obtain a plurality of historical records. For illustration, the plurality of historical records used herein may be referred to as a plurality of primary historical records. A primary historical record may include a primary historical order, a primary historical query, or a combination thereof. In some embodiments, the primary historical record may include a primary start time point, a primary start location, a primary actual destination, etc. For a primary historical order, the primary start time point refers to a time point when the primary historical order is sent by the user via the user terminal130to the server110and/or the service provider140. The primary start location refers to a location where the primary historical order is sent by the user via the user terminal130to the server110and/or the service provider140(e.g., the pickup location of the primary historical order). The primary actual destination refers to the destination of the primary historical order. For a primary historical query, the primary start time point refers to a time point when the primary historical query is executed (e.g., when the user requests information relating to a potential service order). The primary start location refers to a location where the primary historical query is executed. The primary actual destination refers to a destination that a user inputted to execute the primary historical query or a destination that the user selected from a plurality of candidate destinations. In some embodiments, the primary historical record may include a primary destination group. The primary destination group may include a plurality of primary candidate destinations. The plurality of primary candidate destinations may include the destinations that had appeared on the list of the candidate destinations shown in the user interface of the user terminal130when the user initiated the primary historical record. A primary candidate destination refers to a destination in which the user of an online to offline service was probably interested at the primary start time point.

In some embodiments, for each of the plurality of primary historical record, the training module420may determine a plurality of secondary historical records. As used in the present application, the secondary historical records of a primary historical record refer to historical records that occurred before the primary historical record. Similar to a primary historical record, a secondary historical record may include a primary historical order, a primary historical query, or a combination thereof. The secondary historical record may include a secondary start time point, a secondary start location, a secondary actual destination, etc. For a secondary historical order, the secondary start time point refers to a time point when the secondary historical order is sent by the user via the user terminal130to the server110and/or the service provider140. The secondary start location refers to a location where the secondary historical order is sent or the service is initiated (e.g., the pickup location) by the user via the user terminal130to the server110and/or the service provider140. The secondary actual destination refers to the destination of the historical order. For a secondary historical query, the secondary start time point refers to a time point when the secondary historical query is executed. The secondary start location refers to a location where the secondary historical query is executed. The secondary actual destination refers to a destination that a user inputted to execute the secondary historical query or a destination that the user selected from a plurality of candidate destinations. The acquisition module410may obtain the secondary historical records of a primary historical record based on the primary start time point of the primary historical record, the primary start location of the primary historical record, or a combination thereof. For example, the acquisition module410may obtain the secondary historical records occurring within a predetermined time range from the primary start time point of the primary historical record. The predetermined time range may include one week, one month, two months, three months, or other time periods. Alternatively or additionally, the acquisition module410may obtain the secondary historical records whose secondary actual destinations exceed a predetermined geographical range from the primary start location of the primary historical record. The predetermined geographical range may include 100 meters, 500 meters, 1000 meters, or other geographical ranges. Alternatively or additionally, the acquisition module410may obtain the secondary historical records occurring within a predetermined time range (e.g., 30 days) from primary start time point of the primary historical record and having a secondary actual destination exceeding a predetermined geographical range (e.g., 1000 meters) from the primary start location of the primary historical record.

In some embodiments, the training module420may determine a plurality of primary candidate destinations based on the plurality of secondary historical records. For example, the training module420may extract a secondary actual destination of a secondary historical record as a primary candidate destination.

In some embodiments, the training module420may train the preliminary ranking model using the plurality of primary historical records and the plurality of secondary historical records corresponding to each of the plurality of primary historical records. Details regarding the trained ranking model may be found elsewhere in the present disclosure. See, e.g.,FIG.6, and the description thereof.

The determination module430may determine a ranking result of the one or more candidate destinations. In some embodiments, for each of the one or more candidate destinations, the determination module430may extract one or more features, and determine a weighted value corresponding to the candidate destination based on the one or more features and the trained ranking model. Details regarding the ranking result of the one or more candidate destinations may be found elsewhere in the present disclosure. See, e.g.,FIG.5, and the description thereof.

The communication module440may transmit the ranking result of the one or more candidate destinations to the user terminal130in response to the triggering event. In some embodiments, the communication module440may transmit all or part of the one or more ranked candidate destinations. For example, the communication module440may transmit the top six candidate destinations out of ten candidate destinations in the ranking to the user terminal130.

The acquisition module410, the training module420, the determination module430, and the communication module440in the processing engine112may be connected to or communicate with each other via a wired connection, a wireless connection, or any combination thereof. The wired connection may include a metal cable, an optical cable, a hybrid cable, or the like, or any combination thereof. The wireless connection may include a Local Area Network (LAN), a Wide Area Network (WAN), a Bluetooth, a ZigBee, a Near Field Communication (NFC), or the like, or any combination thereof. Two or more of the acquisition module410, the training module420, the determination module430, and the communication module440may be combined as a single module. For example, the training module420may be integrated with the determination module430as a single module. The single module may determine a trained ranking model and determine a ranking result of one or more candidate destinations based on the trained ranking model.

FIG.5illustrates an exemplary process for determining a ranking result, according to some embodiments of the present disclosure. The process500may be implemented as a set of instructions in a non-transitory storage medium of the server110of the online to offline service system100. The processor220of the server110may execute the set of instructions and may accordingly perform the steps in the process500.

The operations of the illustrated process500presented below are intended to be illustrative and not limiting. In some embodiments, the process500may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of the process500as illustrated inFIG.5and described below is not intended to be limiting.

In510, the acquisition module410may receive a triggering event in the absence of input from the user terminal130associated with a user. The triggering event may be an event that triggers a request of a ranked destination group. For example, a trigger event may include a user login of a mobile application of the on-demand devices on the user terminal130, the open or initiation of the mobile application on the user terminal130, a click by the user on the interface (e.g., an input box, a map) of the mobile application, or other suitable operation on the mobile application.

As illustrated somewhere else, the triggering event may correspond to a current time point and a current location. The current time point refers to a time point when the triggering event occurs. The current location refers to a location where the triggering event occurs (e.g., the current location of the user terminal130).

In520, the acquisition module410may obtain one or more candidate destinations based on the triggering event. In some embodiments, the acquisition module410may select the one or more candidate destinations from a destination collection (e.g., from the storage150) based on the triggering event. The destination collection may include a plurality of destinations generated beforehand. In some embodiments, the acquisition module410may obtain one or more historical records (e.g., one or more historical orders, one or more historical queries) based on the triggering event. The acquisition module410may also obtain the one or more candidate destinations based on the one or more historical records. For example, the determination module430may obtain the one or more actual destinations of the one or more historical records as the one or more candidate destinations. The acquisition module410may obtain the actual destinations of one or more historical orders and/or the latest historical query as the one or more candidate destinations. Each of the one or more candidate destinations may correspond to a historical start time point and a historical start location. The historical start time point corresponding to the candidate destination may include a time point when the historical order is sent or a time point when the historical query is executed. The historical start location may include a location where the historical order is sent or a location where the historical query is executed.

In some embodiments, the acquisition module410may obtain the one or more historical records based on the current time point of the triggering event, the current location of the triggering event, or a combination thereof. For example, the acquisition module410may obtain one or more historical records within three months from the current time point of the triggering event. Alternatively or additionally, the acquisition module410may obtain the one or more historical records whose destination exceeds 1000 meters from the current location of the triggering event. Alternatively, the acquisition module410may obtain one or more historical records within three months from the current time point of the triggering event and having a destination exceeding 1000 meters from the current location of the triggering event.

In530, the training module420may obtain a trained ranking model. The trained ranking model may include a machine learning model, for example, a learning-to-rank model. The learning-to-rank model may include a Ranknet model, a LambdaMart model, a Lambdarank model, and the like. In some embodiments, the trained ranking model may be a general ranking model trained using the training data collected from a group of users (e.g., a group of 10000 random users, a group of frequent users). In some embodiments, the ranking model may be a specific ranking model trained using designated training data associated with a user (for example, the user of the user terminal130). In some embodiments, the ranking model may be trained in accordance with operations of process600described in connection withFIG.6.

In540, the determination module430may determine a ranking result of the obtained one or more candidate destinations in520according to the trained ranking model. For each of the one or more candidate destinations, the determination module430may extract one or more features, and determine a weighted value corresponding to the candidate destination based on the one or more features and the trained ranking model. The determination module430may determine the ranking result of the one or more candidate destinations based on the one or more weighted values.

In some embodiments, the one or more features of a candidate destination may relate to the distance between the current location of the triggering event and the candidate destination.

Alternatively or additionally, the one or more features may relate to the time interval between the current time point of the triggering event and the historical start time point corresponding to the candidate destination. In some embodiments, the time interval between the current time point and the historical start time point may be the time difference between the current time point and the historical start time point in their respective dates. For example, if the current time point is 3:00 p.m. on Jun. 7, 2017 and the historical start time point is 4:00 p.m. on Jul. 7, 2017, the time interval may be an hour. Alternatively, the time interval may be the actual time difference between the current time point and the historical start time point. For example, if the current time point is 3:00 p.m. on Jun. 7, 2017 and the historical start time point is 4:00 p.m. on Jul. 7, 2017, the time interval may be 30 days.

Alternatively or additionally, the one or more features may relate to the occurrence frequency of the candidate destination as the actual destination in historical records. In some embodiments, the occurrence frequency of the candidate destination may be the ratio of the number of historical records whose actual destinations are the candidate destination to the total number of the one or more historical records. For example, if the total number of the historical records is one hundred and the number of the historical records whose actual destinations are the candidate destination is 20, the occurrence frequency of the candidate destination may be 0.20.

In some embodiments, the occurrence(s) of the candidate destination as the actual destination in historical record(s) within a time range from the current time point of the triggering event may be used to determine the occurrence frequency. The time range may be in terms of hours or dates. For example, the time range may be one hour (plus and minus) from the current time point of the triggering event regardless of which date (or regardless which date if the date of a historical record is within certain days, e.g., 30 days). Merely by way of example, if the current time point is 3:00 p.m. on Jun. 7, 2017 and the time range may be 2 to 4 p.m. (i.e., plus and minus one hour from 3:00 p.m.), the occurrence(s) of a candidate destination as the actual destination in historical record(s) whose time point is within the time range of 2 to 4 p.m. will be used (regardless the date of a historical record or regardless the date of the historical record if the date is within, for example, 30 days from the current time point) to determine the occurrence frequency of the candidate destination. Alternatively, the time range may be certain days before the current time point (e.g., 30 days). For example, if the current time point is 3:00 p.m. on Jun. 7, 2017 and the time range may be 30 days, the occurrence(s) of a candidate destination as the actual destination in historical record(s) whose date is within 30 days before the current time point will be used (regardless the time point) to determine the occurrence frequency of the candidate destination. In some embodiments, the occurrence frequency of the candidate destination may be determined on special dates (e.g., holidays, weekend, working days).

In550, the communication module440may transmit the ranking result to the user terminal130in response to the triggering event. In some embodiments, the communication module440may transmit all or part of the ranking result to the user terminal130. For example, the communication module440may transmit the top six candidate destinations out of ten candidate destinations in the ranking to the user terminal130. Alternatively, the communication module440may transmit ten candidate destinations to the user terminal130. In some embodiments, the user terminal130may display all or part of the candidate destinations to the user via the user interface.

In some embodiments, the process500may further include additional steps. The acquisition module410may receive a selection by the user of the one or more candidate destinations from the user terminal130. The acquisition module410may also receive a service order based on the selection by the user of the one or more candidate destinations. The above description is merely for illustrative purposes. It should be noted that those skilled in the art may contemplate additional or alternative steps beside the steps described inFIG.5.

FIG.6illustrates an exemplary process600for determining a trained ranking model using the online to offline service system, according to some embodiments of the present disclosure. The process600may be implemented as a set of instructions in a non-transitory storage medium of the server110of the online to offline service system100. The processor220of the server110may execute the set of instructions and may accordingly perform the steps in the process600.

The operations of the illustrated process600presented below are intended to be illustrative. In some embodiments, the process600may be accomplished with one or more additional operations not described, and/or without one or more of the operations discussed. Additionally, the order in which the operations of the process600as illustrated inFIG.6and described below is not intended to be limiting.

In610, the training module420may obtain a plurality of primary historical records. Each of the plurality of primary historical records may include a historical record, which may be a historical order, a historical query, or a combination thereof. As used herein, a historical order refers to a service order initiated by a user and completed by a service provider, and a historical query refers to a service query initiated by a user to request information regarding a service (e.g., fees, estimated waiting time, estimated time of arrival).

In some embodiments, the plurality of primary historical records may associate with a plurality of users of an online to offline service. A primary historical record may include a primary start time point, a primary start location, a primary actual destination, etc. For a primary historical order, the primary start time point refers to a time point when the primary historical order is sent by the user via the user terminal130to the server110and/or the service provider140. The primary start location refers to a location where the primary historical order is sent by the user via the user terminal130to the server110and/or the service provider140(e.g., the pickup location of the primary historical order). The primary actual destination refers to the destination of the primary historical order. For a primary historical query, the primary start time point refers to a time point when the primary historical query is executed (e.g., when the user requests information relating to a potential service order). The primary start location refers to a location where the primary historical query is executed. The primary actual destination refers to a destination that a user inputted to execute the primary historical query or a destination that the user selected from a plurality of candidate destinations.

In620, for each of the plurality of primary historical records, the training module420may determine a plurality of secondary historical records. As used in the present application, the secondary historical records of a primary historical record refer to historical records (e.g., historical orders, historical queries) that occurs before the primary historical record. For example, for a primary historical record, the training module420may obtain a plurality of secondary historical records that occur within a time range (e.g., 3 months) from the date of the primary historical record.

In some embodiments, each of plurality of secondary historical records may include a secondary start time point, a secondary start location, a secondary actual destination, etc. For a secondary historical order, the secondary start time point refers to a time point when the secondary historical order is sent by the user via the user terminal130to the server110and/or the service provider140. The secondary start location refers to a location where the secondary historical order is sent or the service is initiated (e.g., the pickup location) by the user via the user terminal130to the server110and/or the service provider140. The secondary actual destination refers to the destination of the historical order. For a secondary historical query, the secondary start time point refers to a time point when the secondary historical query is executed. The secondary start location refers to a location where the secondary historical query is executed. The secondary actual destination refers to a destination that a user inputted to execute the secondary historical query or a destination that the user selected from a plurality of candidate destinations.

In some embodiments, the training module420may determine the plurality of secondary historical records based on the primary start time point of the primary historical record, the primary start location of the primary historical record, or a combination thereof. For example, the training module420may obtain the secondary historical record(s) within a time range from the primary start time point of the primary historical record (e.g., three months from the primary start time point of the primary historical record). Alternatively or additionally, the training module420may obtain the secondary historical record(s) whose destination exceeds a distance (e.g., 1000 meters) from the primary start location of the primary historical record. Alternatively or additionally, the training module420may obtain the secondary historical record(s) having a start time point within a time range (e.g., three months) from the primary start time point of the primary historical record and having a destination exceeding a distance (e.g., 1000 meters) from the primary start location of the primary historical record.

Alternatively or additionally, the training module420may determine the secondary historical records according to the primary destination group of the primary historical record. In some embodiments, the primary destination group may include a plurality of primary candidate destinations. The plurality of primary candidate destinations may include the destinations that had appeared on the list of the candidate destinations shown in the user interface of the user terminal130when the user initiated the primary historical record. The training module420may determine one or more secondary historical records that have one of these primary candidate destinations as the primary actual destination.

In some embodiments, for each of the plurality of primary historical records, the training module420may determine a plurality of primary candidate destinations according to the determined secondary historical records. For example, the training module420may designate the actual destinations of the secondary historical records as the primary candidate destinations, which may be included in the primary destination group of the primary historical record.

An example is given below to help better understanding, which is for illustration purposes only and not intended to be limiting. For a primary historical record generated at 3:00 p.m. on Jul. 7, 2017, the training module420may obtain a plurality of secondary historical records that are generated before 3:00 p.m. on Jul. 7, 2017. For example, the training module420may obtain the plurality of secondary historical records within 30 days from 3:00 p.m. on Jul. 7, 2017 (i.e., the primary start time). For illustration, the secondary historical records may be referred to as SHR 1, SHR 2, . . . , SHR n. The secondary actual destinations of the secondary historical records may be marked as SAD 1, SAD 2, . . . , SAD m. n and m may be positive integers. In some embodiments, m may be the same as n, and each of the secondary actual destinations of the plurality of secondary historical records may be different. Alternatively, m may be less than n, and at least two of the secondary actual destinations of the secondary historical records may be the same. Then, the training module420may determine a group including SAD 1, SAD 2, . . . , and SAD m as the primary destination group.

In630, the training module420may obtain a preliminary ranking model. The preliminary ranking model may include one or more features corresponding to a destination. The preliminary ranking model may also include a preliminary weighting coefficient of each of the one or more features. In some embodiments, the preliminary ranking model may include a learning-to-rank model. The learning-to-rank model may include a Ranknet model, a LambdaMart model, a Lambdarank model, and the like.

In640, the training module420may determine, based on the preliminary ranking model, a plurality of sample ranking results for the plurality of primary destination groups corresponding to the plurality of primary historical records.

A primary historical record may have a primary start time point, a primary start location, a primary actual destination, and a primary destination group including a plurality of primary candidate destinations. A primary candidate destination may be the secondary actual destination of a secondary historical order that has a secondary start time point and a secondary start location. For a primary historical record, the training module420may determine, based on the preliminary ranking model, a sample ranking result of the primary candidate destinations of the primary historical record.

In some embodiments, for each of the plurality of primary candidate destinations, the training module420may determine one or more features of the primary candidate destination. The one or more features may relate to a distance between the primary candidate destination (i.e., the secondary actual destination) and the primary start location, a time interval between the secondary start time point and the primary start time point, the occurrence frequency of the primary candidate destination in the plurality of secondary historical records in a time period. The occurrence frequency of a primary candidate destination may be the ratio of the number of secondary historical records whose historical actual destinations are the primary candidate destination to the total number of the plurality of secondary historical records in the time range. The time period may be in terms of hours or dates. For example, the time range may be one hour (plus and minus) from the primary start time point of the primary historical record regardless of which date (or regardless which date if the date of a historical record is within certain days, e.g., 30 days). Alternatively, the time range may be certain days before the primary start time point (e.g., 30 days) regardless the time point. In some embodiments, the occurrence frequency of the primary candidate destination may be determined on special dates (e.g., holidays, weekend, working days).

Merely by way of example, if the primary start time point of a primary historical record is 3:00 p.m. on Jul. 7, 2017, the primary start location is the east gate of Peking University, the primary actual destination is the east gate of Renmin University of China, and the primary destination group includes three primary candidate destinations, namely, D1, D2, and D3. D1 is the actual destination of a secondary historical record that has the secondary start time point of 1 p.m. on Jul. 7, 2017 and the secondary start location as the west gate of Tsinghua University. For D1, the distance between the primary candidate destination and the primary start location is the distance between D1 and the east gate of Peking University. The time interval between the secondary start time point and the primary start time point may be the time difference between 3:00 p.m. on Jul. 7, 2017 and 1 p.m. on Jul. 7, 2017 (i.e., two hours). The occurrence frequency of D1 may be the ratio of the number of secondary historical records whose historical actual destinations are D1 to the total number of the plurality of secondary historical records in a time range (e.g., within 30 days before the primary start time point).

For each of the plurality of primary candidate destinations, the training module420may assign one or more preliminary weighting coefficients of the preliminary ranking model to the one or more features of the primary candidate destination. The training module420may also determine a preliminary weighted value corresponding to the primary candidate destination based on the one or more features and the one or more preliminary weighting coefficients.

For each of the primary historical records, the training module420may determine a ranking result of the primary candidate destinations of the primary destination group based on the plurality of preliminary weighted values.

In650, the training module420may obtain a plurality of primary actual destinations corresponding to the plurality of primary historical records. A primary historical records may include a primary actual destination. The training module420may extract the plurality of primary actual destinations based on the plurality of primary historical records.

In660, the training module420may determine whether the plurality of sample ranking results satisfy a condition based on the plurality of actual destinations. In some embodiments, the training module420may determine a loss function of the preliminary model based on the plurality of sample ranking results. The training module420may also determine whether the loss function of the preliminary model is less than a predetermined threshold.

In some embodiments, the loss function may be determined based on Normalized Discounted Cumulative Gain (NDCG). The NDCG may indicate a measure of the quality of a sample ranking result. When the NDCG is greater, the loss function may be smaller. Specifically, for each of the plurality of primary destination groups, the training module420may determine an NDCG. The NDCG may be determined based on the ranking of the primary actual destination in the primary destination group. For example, if the primary actual destination is No. 1 in a sample ranking result of the primary candidate destinations of a primary historical record, the NDCG is greater.

For the plurality of primary historical records, the training module420may determine an average NDCG of the plurality of primary destination groups corresponding to the plurality of primary historical records. The obtaining module410may determine the loss function based on the average NDCG of the plurality of primary destination groups.

Upon a determination that the plurality of sample ranking results fail to satisfy a condition based on the plurality of primary actual destinations, for example, the loss function is not less than the predetermined threshold, the process600may proceed to630and may update the preliminary ranking model. In some embodiments, the training module420may update the preliminary ranking model by adjusting the preliminary weighting coefficients. The training module420may also perform steps640through660. In other words, the training module420may adjust the one or more preliminary weighting coefficients of the preliminary model until the plurality of sample ranking results satisfy the condition.

Upon a determination that the plurality of sample ranking results satisfy the condition based on the plurality of actual destinations, for example, the loss function is less than the predetermined threshold, the process600may proceed to670. In670, the training module420may designate the (updated) preliminary ranking model as the trained ranking model. The trained ranking model may include one or more final weighting coefficients which may output a ranking result of candidate destinations.

The above description is merely for illustrative purposes. It should be noted that those skilled in the art may contemplate additional or alternate steps beside the steps described inFIG.6. For example, the process600may further include transmitting the ranking model to the storage150or any other components in the online to offline service system100by the communication module440.

FIG.7illustrates an exemplary interface700of a mobile application on the user terminal130, according to some embodiments of the present disclosure. As illustrated inFIG.7, the interface700may include an input box710, an enter button720, and a destination group730. The destination group730may include a candidate destination730-1, a candidate destination730-2, . . . , a candidate destination730-n. The candidate destination730-1, the candidate destination730-2, . . . , the candidate destination730-nmay be ranked, one of which may be the actual destination (e.g., the candidate destination730-2) that is selected by the user via the user interface.

When the user of the mobile application (for example, a mobile application of an online to offline service) triggers an triggering event, for example, clicking the input box710, the user terminal130may obtain the triggering event and present all or part of the destination group (e.g., the candidate destinations in the ranking) to the user.