WO2020133548A1

WO2020133548A1 - Systems and methods for point of interest retrieving

Info

Publication number: WO2020133548A1
Application number: PCT/CN2018/125992
Authority: WO
Inventors: Wanji ZHENG; Huan CHEN; Qi Song; Li Ma
Original assignee: Beijing Didi Infinity Technology And Development Co., Ltd.
Priority date: 2018-12-29
Filing date: 2018-12-31
Publication date: 2020-07-02
Also published as: CN111382218B; CN111382218A

Abstract

A system and a method for points of interest（POI）retrieving are disclosed. The method includes, obtaining a query initiated in a local region via communicating with a terminal device of a user over a network (710), determining a first number of POIs in the local region based on the query (720), determining a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number (730), merging the first number of POIs and the second number of POIs (740), ranking the merged POIs according to the query (750), and displaying at least a portion of the merged POIs on the terminal device of the user according to the ranking (760).

Description

SYSTEMS AND METHODS FOR POINT OF INTEREST RETRIEVING

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims priority to Chinese Patent Application No. 201811639983.8, filed on December 29, 2018, the contents of which are incorporated herein by reference.

TECHNICAL FIELD

The present disclosure generally relates to map-based services and platforms, and in particular, relates to systems and methods for retrieving point of interests (POIs) for the on-line services and platforms.

BACKGROUND

With the development of Internet, on-line services, such as a taxi-hailing service, start to play a significant role in daily lives. When a user inputs a query relating to a destination of a trip in a taxi hailing service, the server may retrieve and recommend a plurality of POIs in response to the query to the user. The retrieved and recommended POIs are determined based on the current location of the user. In some scenarios, the user currently located in a local region may have a cross-regional travel demand. For example, the user may search for a destination out of the local region. However, the server may still retrieve and recommend a plurality of POIs in the local region based on the current location of the user. Thus, it is desirable to provide systems and methods for retrieving and recommending POIs in both local region and one or more target regions out of the local region to the user to improve user experience for an on-line service platform.

SUMMARY

According to an aspect of the present disclosure, a system for POI retrieving may include at least one computer-readable storage medium, a data exchange port communicatively connected to a network, and at least one processor configured to communicate with the at least one computer-readable storage medium. When executing the set of instructions, the at least one processor may be configured to cause the system to obtain a query initiated in a local region via communicating with a terminal device of a user over a network. The at least one processor may also cause the system to determine a first number of points of interest (POIs) in the local region based on the query. The at least one processor may also cause the system to determine a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number. The at least one processor may also cause the system to merge the first number of POIs and the second number of POIs. The at least one processor may further cause the system to rank the merged POIs according to the query. The at least one processor may still further cause the system to display at least a portion of the merged POIs on the terminal device of the user according to the ranking.

In some embodiments, the at least one processor may also cause the system to determine whether the first number of POIs is smaller than a threshold. In response to the determination that the first number of POIs is smaller than the threshold, the at least one processor may further cause the system to determine the second number of POIs out of the local region based on the query and the cross-regional list associated with the local region.

In some embodiments, the cross-regional list associated with the local region may include at least one region out of the local region.

In some embodiments, the at least one processor may also cause the system to obtain the at least one region out of the local region from the cross-regional list associated with the local region. The at least one processor may further cause the system to determine the second number of POIs out of the local region by determining POIs in each of the at least one region out of the local region based on the query.

In some embodiments, the at least one processor may also cause the system to obtain a plurality of cross-regional orders of the user in a historical time period. The at least one processor may further cause the system to determine the number of orders directed, from the local region, to each of multiple regions based on the plurality of cross-regional orders. The at least one processor may further cause the system to determine a cross-regional rate of each of the multiple regions. The at least one processor may further cause the system to determine the at least one region out of the local region based on the cross-regional rate of each of the multiple regions.

In some embodiments, the at least one processor may also cause the system to determine whether the cross-regional rate of each of the multiple regions is larger than a preset rate. In response to the determination that the cross-regional rate of a region is larger than the preset rate, the at least one processor may further cause the system to determine the region as one of the at least one region out of the local region.

In some embodiments, the at least one processor may also cause the system to obtain a learning to rank (LTR) model. The at least one processor may further cause the system to rank, using the LTR model, the merged POIs according to the query.

In some embodiments, LTR model may be trained according to at least one of a distance between the user and a POI, hot degree of a POI, a historical click rate of a POI, or a textual relevance.

In some embodiments, the local region may be determined based on location information of the terminal device of the user.

In some embodiments, the location information may include at least one of Global Positioning System (GPS) information, base station information, and wireless fidelity (WIFI) Internet protocol (IP) address information.

According to still another aspect of the present disclosure, a computer-implemented method may include one or more of the following operations performed by at least one processor. The method may include obtaining a query initiated in a local region via communicating with a terminal device of a user over a network. The method may also include determining a first number of points of interest (POIs) in the local region based on the query. The method may also include determining a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number. The method may also include merging the first number of POIs and the second number of POIs. The method may also include ranking the merged POIs according to the query. The method may further include displaying at least a portion of the merged POIs on the terminal device of the user according to the ranking.

According to yet another aspect of the present disclosure, a non-transitory computer readable medium may include at least one set of instructions for POI retrieving, wherein when executed by at least one processor of a computing device, the at least one set of instructions may cause the at least one processor to perform a method. The method may include obtaining a query initiated in a local region via communicating with a terminal device of a user over a network. The method may also include determining a first number of points of interest (POIs) in the local region based on the query. The method may also include determining a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number. The method may also include merging the first number of POIs and the second number of POIs. The method may also include ranking the merged POIs according to the query. The method may further include displaying at least a portion of the merged POIs on the terminal device of the user according to the ranking.

Additional features will be set forth in part in the description which follows, and in part will become apparent to those skilled in the art upon examination of the following and the accompanying drawings or may be learned by production or operation of the examples. The features of the present disclosure may be realized and attained by practice or use of various aspects of the methodologies, instrumentalities and combinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplary embodiments. These exemplary embodiments are described in detail with reference to the drawings. The drawings are not to scale. These embodiments are non-limiting exemplary embodiments, in which like reference numerals represent similar structures throughout the several views of the drawings, and wherein:

FIG. 1 is a schematic diagram illustrating an exemplary on-line service system according to some embodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating exemplary components of a computing device according to some embodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary terminal device according to some embodiments of the present disclosure;

FIG. 4 is a block diagram illustrating an exemplary processing engine according to some embodiments of the present disclosure;

FIG. 5 is a flowchart illustrating an exemplary process for displaying one or more merged POIs on a terminal device of a user according to some embodiments of the present disclosure;

FIG. 6 is a block diagram illustrating an exemplary processing module according to some embodiments of the present disclosure;

FIG. 7 is a flowchart illustrating an exemplary process for displaying one or more merged POIs on a terminal device of a user according to some embodiments of the present disclosure;

FIG. 8 is a flowchart illustrating an exemplary process for determining at least one region out of a local region according to some embodiments of the present disclosure;

FIG. 9 is a schematic diagram illustrating an exemplary user interface of a terminal device displaying a query and POIs according to some embodiments of the present disclosure; and

FIG. 10 is a schematic diagram illustrating an exemplary process for retrieving one or more POIs based on a query according to some embodiments of the present disclosure.

DETAILED DESCRIPTION

In order to illustrate the technical solutions related to the embodiments of the present disclosure, brief introduction of the drawings referred to in the description of the embodiments is provided below. Obviously, drawings described below are only some examples or embodiments of the present disclosure. Those having ordinary skills in the art, without further creative efforts, may apply the present disclosure to other similar scenarios according to these drawings. Unless stated otherwise or obvious from the context, the same reference numeral in the drawings refers to the same structure and operation.

As used in the disclosure and the appended claims, the singular forms “a, ” “an, ” and “the” include plural referents unless the content clearly dictates otherwise. It will be further understood that the terms “comprises, ” “comprising, ” “includes, ” and/or “including” when used in the disclosure, specify the presence of stated steps and elements, but do not preclude the presence or addition of one or more other steps and elements.

Some modules of the system may be referred to in various ways according to some embodiments of the present disclosure, however, any number of different modules may be used and operated in a client terminal and/or a server. These modules are intended to be illustrative, not intended to limit the scope of the present disclosure. Different modules may be used in different aspects of the system and method.

According to some embodiments of the present disclosure, flowcharts are used to illustrate the operations performed by the system. It is to be expressly understood, the operations above or below may or may not be implemented in order. Conversely, the operations may be performed in inverted order, or simultaneously. Besides, one or more other operations may be added to the flowcharts, or one or more operations may be omitted from the flowchart.

Technical solutions of the embodiments of the present disclosure be described with reference to the drawings as described below. It is obvious that the described embodiments are not exhaustive and are not limiting. Other embodiments obtained, based on the embodiments set forth in the present disclosure, by those with ordinary skill in the art without any creative works are within the scope of the present disclosure.

Moreover, the systems and methods in the present disclosure may be applied to any application scenario in which a user requires to search a POI. For example, the system or method of the present disclosure may be applied to different transportation systems including land, ocean, aerospace, or the like, or any combination thereof. The transportation systems may provide transportation service for users using various vehicles. 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, a bicycle, a tricycle, a motorcycle, or the like, or any combination thereof. The system or method of the present disclosure may be applied to taxi hailing, chauffeur services, delivery service, carpool, bus service, take-out service, driver hiring, vehicle hiring, bicycle sharing service, train service, subway service, shuttle services, location service, or the like. The application scenarios of the system or method of the present disclosure may include a web page, 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.

In an aspect, the present disclosure directs to systems for cross regional POI retrieving. When a user inputs a query to initiate a search for a POI, an on-line service platform may provide a plurality of POIs relating to the query to the user. The on-line service platform may determine a first number of POIs in a local region based on the query after the query initiated in the local region from a terminal device (e.g., the user’s smartphone) is received. The on-line platform may also determine a second number of POIs out of the local region (e.g., according to the user’s cross-regional intention) based on the query, a cross-regional list associated with the local region and the first number. The on-line service platform may merge the first number of POIs and the second number of POIs, and rank the merged POIs according to the query using a learning to rank (LTR) model. The on-line service platform may further display at least a portion of the merged POIs on the terminal device of the user according to the ranking. The user may select one of the displayed one or more POIs for quick input.

FIG. 1 is a schematic diagram of an exemplary on-line service system according to some embodiments of the present disclosure. The on-line service system 100 may include a server 110, a network 120, a storage device 130, and a terminal device 140.

The server 110 may facilitate data processing for the on-line service system 100. In some embodiments, the server 110 may be a single server or a server group. The server group may be centralized, or distributed (e.g., server 110 may be a distributed system) . In some embodiments, the server 110 may be local or remote. For example, the server 110 may access information and/or data stored in the terminal device 140, and/or the storage device 130 via the network 120. As another example, the server 110 may be directly connected to the terminal device 140, and/or the storage device 130 to access stored information and/or data. In some embodiments, the server 110 may 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 server 110 may be implemented on a computing device 200 having one or more components illustrated in FIG. 2 in the present disclosure.

In some embodiments, the server 110 may include a processing engine 112. The processing engine 112 may process information and/or data to perform one or more functions described in the present disclosure. For example, the processing engine 112 may determine a first number of POIs in a local region based on a query. As another example, the processing engine 112 may determine a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number of POIs. As still another example, the processing engine 112 may merge the first number of POIs and the second number of POIs. As still another example, the processing engine 112 may rank merged POIs according to the query. In some embodiments, the processing engine 112 may include one or more processing engines (e.g., single-core processing engine (s) or multi-core processor (s) ) . Merely by way of example, the processing engine 112 may include one or more hardware processors, such as 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 network 120 may facilitate the exchange of information and/or data. In some embodiments, one or more components in the on-line service system 100 (e.g., the server 110, the storage device 130, and the terminal device 140) may send information and/or data to other component (s) in the on-line service system 100 via the network 120. For example, the processing engine 112 may obtain a query (e.g., a user input regarding a destination of his/her trip) from the storage device 130 and/or the terminal device 140 via the network 120. In some embodiments, the network 120 may be any type of wired or wireless network, or a combination thereof. Merely by way of example, the network 120 may include a cable network, a wireline network, an optical fiber network, a telecommunications network, an intranet, the 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 ^TM network, a ZigBee network, a near field communication (NFC) network, or the like, or any combination thereof. In some embodiments, the network 120 may include one or more network access points. For example, the network 120 may include wired or wireless network access points such as base stations and/or internet exchange points 120-1, 120-2, …, through which one or more components of the on-line service system 100 may be connected to the network 120 to exchange data and/or information.

The storage device 130 may store data and/or instructions. In some embodiments, the storage device 130 may store data obtained from the terminal device 140 and/or the processing engine 112. For example, the storage device 130 may store a query obtained from the terminal device 140. As another example, the storage device 130 may store a first number of POIs in a local region and a second number of POIs out of the local region. As still another example, the storage device 130 may store POIs determined by ranking the first number of POIs in the local region and the second number of POIs out of the local region. In some embodiments, the storage device 130 may store data and/or instructions that the server 110 may execute or use to perform exemplary methods described in the present disclosure. For example, the storage device 130 may store instructions that the processing engine 112 may execute or use to determine POIs. In some embodiments, the storage device 130 may include a mass storage, a 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 thyrisor 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 storage device 130 may 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 storage device 130 may be connected to the network 120 to communicate with one or more components in the on-line service system 100 (e.g., the server 110, the terminal device 140, etc. ) . One or more components in the on-line service system 100 may access the data or instructions stored in the storage device 130 via the network 120. In some embodiments, the storage device 130 may be directly connected to or communicate with one or more components in the on-line service system 100 (e.g., the server 110, the terminal device 140) . In some embodiments, the storage device 130 may be part of the server 110.

In some embodiments, the terminal device 140 may include a mobile device 140-1, a tablet computer 140-2, a laptop computer 140-3, or the like, or any combination thereof. In some embodiments, the mobile device 140-1 may include a smart home device, a wearable device, a mobile equipment, 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 bracelet, footgear, glasses, a helmet, a watch, clothing, a backpack, a smart accessory, or the like, or any combination thereof. In some embodiments, the mobile equipment may include a mobile phone, a personal digital assistance (PDA) , a gaming device, a navigation device, a point of sale (POS) device, a laptop, a desktop, 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, augmented reality glasses, 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 ^TM, a RiftCon ^TM, a Fragments ^TM, a Gear VR ^TM, etc. In some embodiments, the on-line service system 100 may be implemented on the terminal device 140.

It should be noted that the on-line service system 100 is merely provided for the purposes of illustration, and is not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations or modifications may be made under the teachings of the present disclosure. For example, the on-line service system 100 may further include a database, an information source, or the like. As another example, the on-line service system 100 may be implemented on other devices to realize similar or different functions. However, those variations and modifications do not depart from the scope of the present disclosure.

FIG. 2 is a schematic diagram illustrating exemplary components of a computing device on which the server 110, the storage device 130, and/or the terminal device 140 may be implemented according to some embodiments of the present disclosure. The particular system may use a functional block diagram to explain the hardware platform containing one or more user interfaces. The computer may be a computer with general or specific functions. Both types of the computers may be configured to implement any particular system according to some embodiments of the present disclosure. Computing device 200 may be configured to implement any components that perform one or more functions disclosed in the present disclosure. For example, the computing device 200 may implement any component of the on-line service system 100 as described herein. In FIGs. 1-2, only one such computer device is shown purely for convenience purposes. One of ordinary skill in the art would understood at the time of filing of this application that the computer functions relating to the POI determination as described herein may be implemented in a distributed fashion on a number of similar platforms, to distribute the processing load.

The computing device 200, for example, may include COM ports 250 connected to and from a network connected thereto to facilitate data communications. The computing device 200 may also include a processor (e.g., the processor 220) , in the form of one or more processors (e.g., logic circuits) , for executing program instructions. For example, the processor may include interface circuits and processing circuits therein. The interface circuits may be configured to receive electronic signals from a bus 210, wherein the electronic signals encode structured data and/or instructions for the processing circuits to process. The processing circuits may conduct logic calculations, and then determine a conclusion, a result, and/or an instruction encoded as electronic signals. Then the interface circuits may send out the electronic signals from the processing circuits via the bus 210.

The exemplary computing device may include the internal communication bus 210, program storage and data storage of different forms including, for example, a disk 270, 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 computing device. The exemplary computing device may also include program instructions stored in the ROM 230, RAM 240, and/or other type of non-transitory storage medium to be executed by the processor 220. The methods and/or processes of the present disclosure may be implemented as the program instructions. The computing device 200 also includes an I/O component 260, supporting input/output between the computer and other components. The computing device 200 may also receive programming and data via network communications.

Merely for illustration, only one CPU and/or processor is illustrated in FIG. 2. Multiple CPUs and/or processors are also contemplated; thus operations and/or method steps 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, if in the present disclosure the CPU and/or processor of the computing device 200 executes both step A and step B, it should be understood that step A and step B may also be performed by two different CPUs and/or processors jointly or separately in the computing device 200 (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. 3 is a schematic diagram illustrating exemplary hardware and/or software components of an exemplary terminal device according to some embodiments of the present disclosure; on which the terminal device 140 may be implemented according to some embodiments of the present disclosure. As illustrated in FIG. 3, the mobile device 300 may include a communication platform 310, a display 320, a graphic processing unit (GPU) 330, a central processing unit (CPU) 340, an I/O 350, a memory 360, and a storage 390. The CPU 340 may include interface circuits and processing circuits similar to the processor 220. In some embodiments, any other suitable component, including but not limited to a system bus or a controller (not shown) , may also be included in the mobile device 300. In some embodiments, a mobile operating system 370 (e.g., iOS ^TM, Android ^TM, Windows Phone ^TM) and one or more applications 380 may be loaded into the memory 360 from the storage 390 in order to be executed by the CPU 340. The applications 380 may include a browser or any other suitable mobile apps for receiving and rendering information relating to a query or other information from the location based service providing system on the mobile device 300. User interactions with the information stream may be achieved via the I/O devices 350 and provided to the processing engine 112 and/or other components of the on-line service system 100 via the network 120.

In order to implement various modules, units and their functions described above, a computer hardware platform may be used as hardware platforms of one or more elements (e.g., a component of the sever 110 described in FIG. 2) . Since these hardware elements, operating systems, and program languages are common, it may be assumed that persons skilled in the art may be familiar with these techniques and they may be able to provide information required in the POI determination according to the techniques described in the present disclosure. A computer with user interface may be used as a personal computer (PC) , or other types of workstations or terminal devices. After being properly programmed, a computer with user interface may be used as a server. It may be considered that those skilled in the art may also be familiar with such structures, programs, or general operations of this type of computer device. Thus, extra explanations are not described for the figures.

FIG. 4 is a block diagram illustrating an exemplary processing engine 112 according to some embodiments of the present disclosure. The processing engine 112 may include an obtaining module 410, a processing module 420, an I/O module 430, and a communication module 440. The modules may be hardware circuits of at least part of the processing engine 112. The modules may also be implemented as an application or set of instructions read and executed by the processing engine 112. Further, the modules may be any combination of the hardware circuits and the application/instructions. For example, the modules may be the part of the processing engine 112 when the processing engine 112 is executing the application/set of instructions.

The obtaining module 410 may obtain data/signals. The obtaining module 410 may obtain the data/signals from one or more components of the on-line service system 100 (e.g., the terminal device 140, the I/O module 430, the storage device 130) , or an external device (e.g., a cloud database) . Merely by ways of example, the obtained data/signals may include user queries, user instructions, programs, algorithms, or the like, or a combination thereof.

In some embodiments, the obtaining module 410 may obtain a query from the terminal device 140 via the network 120. In some embodiments, the query initiated in a local region may associate with a name of a location, an abbreviation of the location, a notation of the location, a synonym of the location, etc. that are relating to an on-line service (e.g., a taxi-hailing service) . The location may be a start location, a pick-up location, a destination, etc. In some embodiments, the query may be in the form of text, audio, video, or graph. For example, the query may be “Xi’erqi” , “Bank of China” , or “shopping mall” .

In some embodiments, the obtaining module 410 may transfer the obtained query to other units and/or modules of the processing engine 112 for further processing. For example, the obtaining module 410 may transmit the query to the processing module 420 for further processing (e.g., rewrite the query, correct the spelling of the query) . As another example, the obtaining module 410 may transmit the query to a storage device (e.g., the storage device 130) for storage.

The processing module 420 may process data/signals. The processing module 420 may obtain the data/signals from the obtaining module 410, the I/O module 430, and/or any storage devices capable of storing data/signals (e.g., the storage device 130, or an external data source) . In some embodiments, the processing module 420 may determine a first number of POIs in a local region based on a query obtained from the obtaining module 410. In some embodiments, the processing module 420 may determine a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number. In some embodiments, the processing module 420 may determine merged POIs based on the first number of POIs and the second number of POIs. For example, the processing module 420 may determine the merged POIs by combining the first number of POIs with the second number of POIs. In some embodiments, the processing module 420 may rank the merged POIs according to the query using a LTR model. As used herein, the LTR model may be configured to rank a plurality of POIs based on feature information associated with the plurality of POIs and the query.

The processing module 420 may include a hardware processor, such as a microcontroller, a microprocessor, a reduced instruction set computer (RISC) , an application specific integrated circuits (ASICs) , an application-specific instruction-set processor (ASIP) , a central processing unit (CPU) , a graphics processing unit (GPU) , a physics processing unit (PPU) , a microcontroller unit, a digital signal processor (DSP) , a field programmable gate array (FPGA) , an advanced RISC machine (ARM) , a programmable logic device (PLD) , any circuit or processor capable of executing one or more functions, or the like, or any combinations thereof.

The I/O module 430 may input or output data or information. For example, the I/O module 430 may input a query of a user. As another example, the I/O module 430 may output one or more POIs. In some embodiments, the I/O module 430 may include an input device and an output device. Exemplary input device may include a keyboard, a mouse, a touch screen, a microphone, or the like, or a combination thereof. Exemplary output device may include a display device, a loudspeaker, a printer, a projector, or the like, or a combination thereof. Exemplary display device may include a liquid crystal display (LCD) , a light-emitting diode (LED) -based display, a flat panel display, a curved screen, a television device, a cathode ray tube (CRT) , or the like, or a combination thereof.

The communication module 440 may be connected to a network (e.g., the network 120) to facilitate data communications. The communication module 440 may establish connections between the processing engine 112 and the terminal device 140, and/or the storage device 130. For example, the communication module 440 may transmit at least a portion of merged POIs (e.g., top 1, top 2, top 5, top 10, top 1%, top 5%, top 10%, top 30%) determined by the processing module 430 to a user interface of the application in the terminal device 140. The connection may be a wired connection, a wireless connection, any other communication connection that can enable data transmission and/or reception, and/or any combination of these connections. The wired connection may include, for example, an electrical cable, an optical cable, a telephone wire, or the like, or any combination thereof. The wireless connection may include, for example, a Bluetooth ^TM link, a Wi-Fi ^TM link, a WiMax ^TM link, a WLAN link, a ZigBee ^TM link, a mobile network link (e.g., 3G, 4G, 5G, etc. ) , or the like, or any combination thereof. In some embodiments, the communication port 207 may be and/or include a standardized communication port, such as RS232, RS485, etc.

It should be noted that the above description of the processing engine 112 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. For example, the processing engine 112 may further include a storage module facilitating data storage. However, those variations and modifications do not depart from the scope of the present disclosure.

FIG. 5 is a flowchart illustrating an exemplary process 500 for displaying one or more merged POIs on a terminal device of a user according to some embodiments of the present disclosure. In some embodiments, the process 500 may be implemented in the on-line service system 100. For example, the process 500 may be stored in the storage device 130 and/or the storage (e.g., the ROM 230, the RAM 240, etc. ) as a form of instructions, and invoked and/or executed by the server 110 (e.g., the processing engine 112 in the server 110, or the processor 220 of the processing engine 112 in the server 110) .

In 510, the processing engine 112 (e.g., the obtaining module 410) may obtain a query from a terminal device of a user. In some embodiments, the obtaining module 410 may obtain the query from the terminal device 140 via the network 120.

The query initiated in a local region may associate with a name of a location, an abbreviation of the location, a notation of the location, a synonym of the location, etc. that are relating to an on-line service (e.g., a taxi-hailing service) . The location may be a start location, a pick-up location, a destination, etc. In some embodiments, the query may be in the form of text, audio, video, or graph. For example, the query may be “Xi’erqi” , “Bank of China” , or “shopping mall” .

In some embodiments, the query may correspond to the local region. In some embodiments, the local region may be an area where the terminal device 140 is located when the user of the terminal device 140 sends the query. For example, the obtaining module 410 may obtain position information (e.g., Global Positioning System (GPS) information, base station information, wireless fidelity (WIFI) Internet protocol (IP) address information) of the terminal device 140 which indicates a current location of the terminal device 140 in real time or substantially in real-time (e.g., 1 second, 10 seconds, 1 minutes) . As another example, the user may select or input the local region when the user inputs the query and initiates a search for a POI. In some embodiments, the local region may be any administrative area, for example, a country, a province, a city, or a district.

In 520, the processing engine 112 (e.g., the processing module 420) may determine one or more merged POIs based on the query.

In some embodiments, the processing module 420 may determine the one or more merged POIs based on a first number of POIs in the local region and a second number of POIs out of the local region. In some embodiments, the processing module 420 may determine the first number of POIs in the local region by comparing the query with POIs in the local region stored in a storage device of the on-line service system 100 (e.g., the storage device 130) or an external storage device. In some embodiments, the processing module 420 may determine the second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number. In some embodiments, the processing module 420 may identify a cross-regional intention associated with the query based on the first number. For example, the processing module 420 may identify the cross-regional intention of the user by determining whether the first number of POIs is smaller than a preset threshold. In response to a determination that the first number of POIs is smaller than the preset threshold, it may indicate that the user has a cross-regional intention. After determining that the user has the cross-regional intention, the processing module 420 may determine the second number of POIs based on the query, and the cross-regional list associated with the local region. The cross-regional list associated with the local region may include at least one region out of the local region. In some embodiments, the at least one region out of the local region may be determined based on a plurality of cross-regional orders of the user in a historical time period using a cross-regional recognition method as described elsewhere in the present disclosure (e.g., FIGs. 7 and 8, and the descriptions thereof) . The processing module 420 may determine the second number of POIs out of the local region by determining POIs in each of the at least one region out of the local region based on the query.

In some embodiments, the processing module 420 may merge the first number of POIs and the second number of POIs, and rank the merged POIs according to the query using a LTR model. In some embodiments, the processing module 420 may determine at least a portion of the merged POIs (e.g., top 1, top 2, top 5, top 10, top 1%, top 5%, top 10%, top 30%) to be displayed on the terminal device of the user.

In 530, the processing engine 112 (e.g., the communication module 440) may display the one or more merged POIs on the terminal device of the user. In some embodiments, the communication module 440 may transmit the at least a portion of the merged POIs (e.g., top 1, top 2, top 5, top 10, top 1%, top 5%, top 10%, top 30%) to a user interface of the application in the terminal device 140.

In some embodiments, the displayed merged POIs may be presented in an order according to the ranking of the merged POIs as described in connection with the operation 520. A POI with a higher rank may be presented on the top of a POI list (e.g., a POI list 930 in FIG. 9) in the user interface of the application in the terminal device 140. For example, the merged POIs may be presented based on historical click rate of the POI. The POI with the highest historical click rate may be presented on the top of the POI list.

It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure.

FIG. 6 is a block diagram illustrating an exemplary processing module according to some embodiments of the present disclosure. In some embodiments, the processing module 420 may include a first POI determination unit 610, a second POI determination unit 620, a merging unit 630, and a ranking unit 640.

The first POI determination unit 610 may determine a first number of POIs in a local region. In some embodiments, the first POI determination unit 610 may determine the first number of POIs in the local region based on a query initiated in the local region. In some embodiments, the first POI determination unit 610 may determine the first number of POIs in the local region by comparing the query with POIs in the local region stored in a storage device of the on-line service system 100 (e.g., the storage device 130) or an external storage device. For example, the first POI determination unit 610 may determine the first number of POIs in the local region that are the same as or substantially similar to the query. As used herein, “substantially similar” refers to that a similarity between the query and the POI is larger than a threshold (e.g., 98%, 95%, 90%, 85%) , or the query is a synonym of the POI. Merely by way of example, assuming that the query is “bank of china, ” the first POI determination unit 610 determine a plurality of POIs such as “Bank of China bus station, ” “Bank of China subway station, ” “Bank of China Building” as the first number of POIs.

In some embodiments, the first POI determination unit 610 may process the query, and determine the first number of POIs based on the processed query. For example, the first POI determination unit 610 may rewrite the query (e.g., “Bank of China” ) as a synonym (e.g., “BOC” ) . As another example, if the query is misspelled, the first POI determination unit 610 may correct the spelling of the query.

In some embodiments, the first POI determination unit 610 may transfer the first number of POIs to other units and/or modules of the processing engine 112 for further processing. For example, the first POI determination unit 610 may transfer the first number of POIs to the second POI determination unit 620 for determining a second number of POIs out of the local region. As another example, the first POI determination unit 610 may transfer the first number of POIs to the merging unit 630 for merging the first number of POIs and the second number of POIs.

The second POI determination unit 620 may determine a second number of POIs out of the local region. In some embodiments, the second POI determination unit 620 may determine the second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number. In some embodiments, the second POI determination unit 620 may identify a cross-regional intention associated with the query based on the first number. For example, the second POI determination unit 620 may identify the cross-regional intention of the user by determining whether the first number of POIs is smaller than a preset threshold. In response to a determination that the first number of POIs is smaller than the preset threshold, it may indicate that the user has a cross-regional intention. After determining that the user has the cross-regional intention, the second POI determination unit 620 may determine the second number of POIs out of the local region based on the query and the cross-regional list associated with the local region. The cross-regional list associated with the local region may include at least one region out of the local region. In some embodiments, the at least one region out of the local region may be determined based on a plurality of cross-regional orders of the user in a historical time period using a cross-regional recognition method as described elsewhere in the present disclosure (e.g., FIGs. 7 and 8, and the descriptions thereof) . The second POI determination unit 620 may determine the second number of POIs out of the local region by determining POIs in each of the at least one region out of the local region based on the query. Merely by way of example, the second number of POIs out of the local region may be a sum of the number of POIs in each of the at least one region out of the local region.

In some embodiments, the second POI determination unit 620 may transfer the second number of POIs to other units and/or modules of the processing engine 112 for further processing. For example, the second POI determination unit 620 may transfer the second number of POIs to the merging unit 630 for merging the first number of POIs and the second number of POIs.

The merging unit 630 may merge the first number of POIs and the second number of POIs. In some embodiments, the merging unit 630 may determine merged POIs by combining the first number of POIs with the second number of POIs. For example, the merging unit 630 may determine a table including the merged POIs (i.e., the first number of POIs and the second number of POIs) by combining a table including the first number of POIs and a table including the second number of POIs.

In some embodiments, the merging unit 630 may transfer the merged POIs to other units and/or modules of the processing engine 112 for further processing. For example, the merging unit 630 may transfer the merged POIs to the ranking unit 640 for ranking the merged POIs.

The ranking unit 640 may rank the merged POIs. In some embodiments, the ranking unit 640 may rank the merged POIs according to the query using a LTR model. As used herein, the LTR model may be configured to rank a plurality of POIs based on feature information associated with the plurality of POIs and the query. Exemplary feature information associated with a POI may include a distance between the user and the POI, the hot degree of the POI, a historical click rate of the POI, a textual relevance between the POI and the query, or the like, or any combination thereof. In some embodiments, the ranking unit 640 may rank the merged POIs based on the historical click rate of each of the merged POIs using the LTR model. For example, a higher historical click rate of the POI may correspond to a higher ranking of the POI. In some embodiments, the ranking unit 640 may rank the merged POIs based on the distance between the user and each of the merged POIs using the LTR model. For example, the merged POIs may be ranked according to their distances to the user in ascending order.

In some embodiments, the ranking unit 640 may transfer the ranking of the merged POIs to other units and/or modules of the processing engine 112 for further processing. For example, the ranking unit 640 may transfer the ranking of the merged POIs to the communication module 440 for displaying at least a portion of the merged POIs on the terminal device of the user.

It should be noted that the above description of the processing module 420 is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. For example, the first POI determination unit 610 and the second POI determination unit 620 may be merged into a single unit for both determining the first number of POIs in the local region and the second number of POIs out of the local region. However, those variations and modifications do not depart from the scope of the present disclosure.

FIG. 7 is a flowchart illustrating an exemplary process 700 for displaying one or more merged POIs on a terminal device of a user according to some embodiments of the present disclosure. In some embodiments, the process 700 may be implemented in the on-line service system 100. For example, the process 700 may be stored in the storage device 130 and/or the storage (e.g., the ROM 230, the RAM 240, etc. ) as a form of instructions, and invoked and/or executed by the server 110 (e.g., the processing engine 112 in the server 110, or the processor 220 of the processing engine 112 in the server 110) .

In 710, the processing engine 112 (e.g. the obtaining module 410) may obtain a query initiated in a local region via communicating with a terminal device of a user over a network. In some embodiments, the processing engine 112 may obtain the query from the terminal device 140 via the network 120.

In some embodiments, the terminal device 140 may establish a communication (e.g., wireless communication) with the server 110, through an application (e.g., the application 380 in FIG. 3) installed in the terminal device 140 or a webpage in a browser via the network 120. The application may be associated with the on-line service system 100. For example, the application may be a taxi-hailing application associated with the on-line service system 100.

In some embodiments, the user may send a query to the processing engine 112 (e.g., the obtaining module 410) by, for example, pressing a button in an interface of the application after he/she inputs a query. In some embodiments, the application installed in the terminal device 140 may direct the terminal device 140 to monitor, continuously or periodically, the query from the user, and automatically transmit the query to the processing engine 112 via the network 120.

The query may associate with a name of a location, an abbreviation of the location, a notation of the location, a synonym of the location, etc. that are relating to an on-line service (e.g., a taxi-hailing service) . The location may be a start location, a pick-up location, a destination, etc. In some embodiments, the query may be in the form of text, audio, video, or graph. For example, the query may be “Xi’erqi” , “Bank of China” , or “shopping mall” .

In some embodiments, the query may correspond to the local region. In some embodiments, the local region may be an area where the terminal device 140 is located when the user of the terminal device 140 sends the query. For example, the processing engine 112 may obtain position information (e.g., Global Positioning System (GPS) information, base station information, wireless fidelity (WIFI) Internet protocol (IP) address information) of the terminal device 140 which indicates a current location of the terminal device 140 in real time or substantially in real-time (e.g., 1 second, 10 seconds, 1 minutes) . As another example, the user may select or input the local region when the user inputs the query and initiates a search for a POI. In some embodiments, the local region may be any administrative area, for example, a country, a province, a city, or a district.

In 720, the processing engine 112 (e.g. the first POI determination unit 610) may determine a first number of POIs in the local region based on the query. As used herein, a POI may refer to a specific point of location that a user may be interested in. In some embodiments, the POI may be name of a location, a business name (e.g., a name of a company, a name of a shopping mall) , or the like.

In some embodiments, the processing engine 112 may determine the first number of POIs in the local region by comparing the query with POIs in the local region stored in a storage device of the on-line service system 100 (e.g., the storage device 130) or an external storage device. For example, the processing engine 112 may determine the first number of POIs in the local region that are the same as or substantially similar to the query. As used herein, “substantially similar” refers to that a similarity between the query and the POI is larger than a threshold (e.g., 98%, 95%, 90%, 85%) , or the query is a synonym of the POI. Merely by way of example, assuming that the query is “Bank of China, ” the processing engine 112 may determine a plurality of POIs such as “Bank of China bus station, ” “Bank of China subway station, ” “Bank of China Building” as the first number of POIs.

In some embodiments, the processing engine 112 may process the query, and determine the first number of POIs based on the processed query. For example, the processing engine 112 may rewrite the query (e.g., “Bank of China” ) as a synonym (e.g., “BOC” ) . As another example, if the query is misspelled, the processing engine 112 may correct the spelling of the query.

In 730, the processing engine 112 (e.g. the second POI determination unit 620) may determine a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number.

In some embodiments, the processing engine 112 may determine whether the first number of POIs is smaller than a threshold. The threshold may be set by a user, according to default settings of the on-line service system 100, or adjusted under different situations. For example, the threshold may range from 15 to 20. In response to a determination that the first number of POIs is smaller than the threshold, the processing engine 112 may determine the second number of POIs out of the local region based on the query and the cross-regional list associated with the local region.

The cross-regional list associated with the local region may include at least one region out of the local region. In some embodiments, the at least one region out of the local region may be determined based on a cross-regional recognition method. For example, the processing engine 112 may obtain historical orders including a plurality of cross-regional orders of the user in a historical time period. The processing engine 112 may determine the number of orders directed, from the local region, to each of multiple regions based on the plurality of cross-regional orders. The processing engine 112 may further determine the at least one region out of the local region based on a cross-regional rate of each of the multiple regions. More descriptions of the determination of the cross-regional list may be found elsewhere in the present disclosure (e.g., FIG. 8 and the descriptions thereof) .

In some embodiments, the processing engine 112 may determine the second number of POIs out of the local region based on the query and the cross-regional list associated with the local region. For example, the processing engine 112 may obtain the at least one region out of the local region from the cross-regional list associated with the local region. The processing engine 112 may determine the second number of POIs out of the local region by determining POIs in each of the at least one region out of the local region based on the query. Merely by way of example, the second number of POIs out of the local region may be a sum of the number of POIs in each of the at least one region out of the local region. In some embodiments, the processing engine 112 may determine POIs in each of the at least one region out of the local region by comparing the query with POIs in each of the at least one region out of the local region stored in a storage device of the on-line service system 100 (e.g., the storage device 130) or an external storage device as described in connection with operation 720.

In 740, the processing engine 112 (e.g. the merging unit 630) may merge the first number of POIs and the second number of POIs. In some embodiments, the processing engine 112 may determine merged POIs by combining the first number of POIs with the second number of POIs. For example, the processing engine 112 may determine a table including the merged POIs (i.e., the first number of POIs and the second number of POIs) by combining a table including the first number of POIs and a table including the second number of POIs.

In 750, the processing engine 112 (e.g. the ranking unit 640) may rank the merged POIs according to the query.

In some embodiments, the processing engine 112 may rank the merged POIs based on a learning to rank (LTR) model. As used herein, the LTR model may be configured to rank a plurality of POIs based on feature information associated with the plurality of POIs and the query. Exemplary feature information associated with a POI may include a distance between the user and the POI, the hot degree of the POI, a historical click rate of the POI, a textual relevance between the POI and the query, or the like, or any combination thereof. As used herein, the distance between the user and the POI may refer to a straight-line distance or an actual travel distance from the location of the user to the POI. The hot degree of the POI may indicate the popularity of the POI. For example, the hot degree of the POI may refer to a number of times that a POI is selected by users in a certain time period. The historical click rate of a POI may refer to a probability that the POI is selected by users when a plurality of POIs are displayed on the terminal devices of the users. Higher historical click rate of the POI may correspond to a higher probability that the POI is selected by users. For example, when users in Beijing input a query “Tianjin airport” , most of the users select “terminal of Tianjin airport” , when “terminal of Tianjin airport” and “terminal of Beijing airport” are both displayed on the terminal devices of the users. In this situation, the historical click rate of the “terminal of Tianjin airport” is higher than the historical click rate of the “terminal of Beijing airport” in terms of the query “Tianjin airport” .

In some embodiments, the LTR model may be trained based on historical queries of users, historical POIs that are selected by the users based on the historical queries, and feature information associated with the historical POIs. In some embodiments, the user may input a historical query through the application in the terminal device 140. The on-line service system 100 may send a plurality of relevant historical POIs to be displayed on a user interface of the application implemented in the terminal device 140 based on the historical query. The user may select one of the relevant historical POIs that he/she is interested in through the user interface of the application implemented in the terminal device 140. The processing engine 112 may store the historical query, and the selected historical POI associated with the historical query in a storage device (e.g., the storage device 130, the storage 390) of the on-line service system 100 and/or an external data source.

In some embodiments, the processing engine 112 may obtain the LTR model. In some embodiments, the processing engine 112 may obtain the LTR model from a storage device in the on-line service system 100 (e.g., the storage device 130, the storage 390) and/or an external data source (not shown) via the network 120. For example, the LTR model may be pre-trained (by the processing engine 112 or any other platforms or devices) and stored in the storage device in the on-line service system 100. The processing engine 112 may access the storage device and retrieve the trained LTR model. The processing engine 112 may rank, using the LTR model, the merged POIs according to the query. In some embodiments, the processing engine 112 may rank the merged POIs based on the historical click rate of each of the merged POIs using the LTR model. For example, a higher historical click rate of the POI may correspond to a higher ranking of the POI. In some embodiments, the processing engine 112 may rank the merged POIs based on the distance between the user and each of the merged POIs using the LTR model. For example, the merged POIs may be ranked according to their distances to the user in ascending order.

In 760, the processing engine 112 (e.g. the communication module 440) may display at least a portion of the merged POIs on the terminal device of the user according to the ranking.

In some embodiments, the processing engine 112 may transmit at least a portion of the merged POIs (e.g., top 1, top 2, top 5, top 10, top 1%, top 5%, top 10%, top 30%) to a user interface of the application in the terminal device 140. More descriptions of the user interface displaying the query and the one or more merged POIs may be found elsewhere in the present disclosure (e.g., FIG. 9 and the description thereof) .

In some embodiments, the displayed merged POIs may be presented in an order according to the ranking of the merged POIs as described in connection with operation 750. A POI with a higher rank may be presented on the top of a POI list (e.g., a POI list 930 in FIG. 9) in the user interface of the application in the terminal device 140. For example, the merged POIs may be presented based on the historical click rate of the POI. The POI with the highest historical click rate may be presented on the top of the POI list.

It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. In some embodiments, one or more operations may be added or omitted. For example, the process 700 may further include an operation for preprocessing the query, e.g., correct the query, or rewrite the query. As another example, if the first number of POIs is greater than the threshold, operation 730 and operation 740 may be omitted. However, those variations and modifications do not depart from the scope of the present disclosure.

FIG. 8 is a flowchart illustrating an exemplary process 800 for determining at least one region out of a local region according to some embodiments of the present disclosure. In some embodiments, the process 800 may be implemented in the on-line service system 100. For example, the process 800 may be stored in the storage device 130 and/or the storage (e.g., the ROM 230, the RAM 240, etc. ) as a form of instructions, and invoked and/or executed by the server 110 (e.g., the processing engine 112 in the server 110, or the processor 220 of the processing engine 112 in the server 110) .

In 810, the processing engine 112 (e.g. the second POI determination unit 620) may obtain a plurality of cross-regional orders of a user in a historical time period. The processing engine 112 may obtain the plurality of cross-regional orders of the user from a storage device in the on-line service system 100 (e.g., the storage device 130) and/or an external data source (not shown) via the network 120.

In some embodiments, the plurality of cross-regional orders may be associated with an on-line service (e.g., a taxi-hailing service, a delivery service) . Take the taxi-hailing service as an example, a cross-regional order may refer to an order directed from a first region to a second region. The first region may be different from the second region. That is, a start location and a destination of the cross-regional order are not in a same region. In some embodiments, the processing engine 112 may determine the plurality of cross-regional orders in which the user has manually switched the region of the destinations. For example, when the user located in region A initiates an order via a user interface of the terminal device, the user may switch the region of the destination of the order from region A to region B. In some embodiments, each of the plurality of cross-regional orders may include user’s identity information (e.g., an identification (ID) , a telephone number, a user’s name) , a query from the user, one or more retrieved POIs associated with the query, a POI selected by the user from the one or more retrieved POIs as a service location (e.g., the start location, the destination) of the cross-regional order, a start time point, an end time point, the start location, the destination, or the like, or any combination thereof. As used herein, the “retrieved POIs associated with the query” may refer to POIs determined by the processing engine 112 in response to the query. The start time point may refer to a time point when a service provider starts to provide the service. The end time point may refer to a time point when the service provider ends the service. The start location may refer to a position where the service provider starts to provide the service. The destination may refer to a position where the service provider ends the service.

In some embodiments, the plurality of cross-regional orders of the user may be completed in the historical time period. The historical time period may be default settings of the on-line service system 100, or may be adjustable under different situations. For example, the historical time period may be last one week, last one month, last six months, or the like.

In 820, the processing engine 112 (e.g. the second POI determination unit 620) may determine the number of orders directed, from a local region, to each of multiple regions based on the plurality of cross-regional orders.

In some embodiments, the processing engine 112 may select, from the plurality of cross-regional orders, orders directed from the local region to multiple regions other than the local region. That is, the start locations of the selected orders may be in the local region, and the destinations of the selected orders may be in the multiple regions other than the local region. For each of the multiple regions, the processing engine 112 may determine the number of orders directed from the local region to the region other than the local region. Merely for illustration purposes, assuming that the local region is region A, the processing engine 112 may select orders directed from region A to region B, region C, and region D other than region A. The processing engine 112 may further determine the number of orders directed from region A to region B, the number of orders directed from region A to region C, and the number of orders directed from region A to region D.

In 830, the processing engine 112 (e.g. the second POI determination unit 620) may determine a cross-regional rate of each of the multiple regions other than the local region.

In some embodiments, the cross-regional rate of each region may be determined based on the number of the cross-regional orders and the number of orders directed from the local region to the each region. For example, the cross-regional rate of a region may be a ratio of the number of orders directed from the local region to the region to the number of cross-regional orders. Merely for illustration purposes, assuming that the local region is region A, and the multiple regions include region B, region C, and region D. The cross-regional rate of region B may be a ratio of the number of orders directed from region A to region B (e.g., 100) and the number of orders directed from region A to region B, region C, and region D (e.g., 1000) . That is, the cross-regional rate of region B may be 0.1 (100/1000=0.1) .

In 840, the processing engine 112 (e.g. the second POI determination unit 620) may determine the at least one region out of the local region based on the cross-regional rate of each of the multiple regions.

In some embodiments, the processing engine 112 may determine the at least one region out of the local region based on the cross-regional rate of each of the multiple regions and a preset rate. The preset rate may be set by a user, according to default settings of the on-line service system 100, or adjusted under different situations. For example, the processing engine 112 may determine whether the cross-regional rate of each of the multiple regions is larger than the preset rate. In response to a determination that the cross-regional rate of a region is larger than the preset rate, the processing engine 112 may determine the region as one of the at least one region out of the local region. For example, the at least one region out of the local region may be determined according to Equation (1) :

P (city _B|city _A) >θ, (1)

where city _A refers to the local region, city _B refers to a region in the multiple regions, P (city _B|city _A) refers to the cross-regional rate of city B, and θ refers to the preset rate.

In some embodiments, the processing engine 112 may determine a cross-regional list associated with the local region based on the at least one region out of the local region. For example, after the processing engine 112 determines the at least one region out of the local region (e.g., region A) includes region B, region C, and region D, the processing engine 112 may determine that the cross-regional list associated with the region A may include region A-region B, region A-region C, and region A-region D.

It should be noted that the above description is merely provided for the purposes of illustration, and not intended to limit the scope of the present disclosure. For persons having ordinary skills in the art, multiple variations and modifications may be made under the teachings of the present disclosure. However, those variations and modifications do not depart from the scope of the present disclosure. In some embodiments, after it is determined that the cross- regional rate of a region is larger than the preset rate, the processing engine 112 may further determine whether the distance between the local region and the region is less than a predetermined distance (e.g., 200 km) . If the distance is less than the predetermined distance, the processing engine 112 may determine the region as one of the at least one region out of the local region.

FIG. 9 is a schematic diagram illustrating an exemplary user interface of a terminal device displaying a query and POIs according to some embodiments of the present disclosure. As illustrated in FIG. 9, the user interface 900 may include a location box 910, a search box 920, and a POI list 930. The location box 910 may display a local region (e.g., determined based on the current location of the user) associated with a query. The search box 920 may display the query. The POI list 930 may display one or more POIs relating to the query. The user may select a POI that he/she is interested in from the POI list 930. For example, assuming that the query of the user is “Bank of China” and the local region associated with the query is “Beijing, ” the POIs may be “Bank of China subway station, Haidian District, Beijing, ” “Bank of China bus station, Haidian District, Beijing, ” “Bank of China building, Haidian District, Beijing, ” “Bank of China, Zhaoyang District, Beijing, ” “Bank of China, Wuqing District, Tianjing, ” as illustrated in FIG. 9.

The POIs displayed in the POI list 930 may include first POIs (e.g., “Bank of China subway station, Haidian District, Beijing, ” “Bank of China bus station, Haidian District, Beijing, ” “Bank of China building, Haidian District, Beijing, ” “Bank of China, Zhaoyang District, Beijing” ) in the local region (e.g., Beijing) and second POIs (e.g., “Bank of China, Wuqing District, Tianjing” ) out of the local region. The first POIs and the second POIs may be determined based on a first number of POIs in the local region and a second number of POIs out of the local region as described elsewhere in the present disclosure (e.g., FIGs. 7, 8, and the descriptions thereof) . In some embodiment, the first number of POIs in the local region may be determined by comparing the query (e.g., “Bank of China” ) with POIs in the local region stored in a storage device of the on-line service system 100 (e.g., the storage device 130) or an external storage device. The second number of POIs out of the local region may be determined based on the query, a cross-regional list associated with the local region, and the first number. Merged POIs may be determined by combining the first number of POIs and the second number of POIs. The merged POIs may be ranked according to the query using a LTR model. Finally, at least a portion of the merged POIs (e.g., the first POIs, the second POIs) may be displayed in the POI list 930 according to the ranking.

FIG. 10 is a schematic diagram illustrating an exemplary process for retrieving one or more POIs based on a query according to some embodiments of the present disclosure. In some embodiments, process 1000 may illustrate the process for displaying one or more POIs on a terminal device of a user in combination with process 700 in FIG. 7. As illustrated in FIG. 10, the processing engine 112 may obtain a query from a terminal device of a user in 1010. The query initiated in a local region may associate with a name of a location, an abbreviation of the location, a notation of the location, a synonym of the location, etc. that are relating to an on-line service (e.g., a taxi-hailing service) . The location may be a start location, a pick-up location, a destination, etc. The processing engine 112 may determine a first number of POIs in the local region based on the query in 1020. In some embodiments, the processing engine 112 may determine the first number of POIs in the local region by comparing the query with POIs in the local region stored in a storage device of the on-line service system 100 (e.g., the storage device 130) or an external storage device. The processing engine 112 may identify a cross-regional intention associated with the query in 1030. In some embodiments, the processing engine 112 may identify a cross-regional intention of the user by determining whether the first number of POIs is smaller than a preset threshold. If the first number of POIs is smaller than the preset threshold, it may indicate that the user has a cross-regional intention. In some embodiments, the processing engine 112 may determine a cross-regional list associated with the local region based on a plurality of cross-regional orders of the user in a historical time period. The cross-regional list associated with the local region may include at least one region out of the local region. The processing engine 112 may determine a second number of POIs out of the local region by determining POIs in each of the at least one region out of the local region based on the query in 1040. The processing engine 112 may merge the first number of POIs and the second number of POIs, and rank the merged POIs according to the query using a LTR model in 1050. Finally, the processing engine 112 may display one or more ranked POIs (e.g., top 1, top 2, top 5, top 10, top 1%, top 5%, top 10%, top 30%) on the terminal device of the user according to the ranking in 1060.

Having thus described the basic concepts, it may be rather apparent to those skilled in the art after reading this detailed disclosure that the foregoing detailed disclosure is intended to be presented by way of example only and is not limiting. Various alterations, improvements, and modifications may occur and are intended to those skilled in the art, though not expressly stated herein. These alterations, improvements, and modifications are intended to be suggested by this disclosure, and are within the spirit and scope of the exemplary embodiments of this disclosure.

Moreover, certain terminology has been used to describe embodiments of the present disclosure. For example, the terms “one embodiment, ” “an embodiment, ” and “some embodiments” mean that a particular feature, structure or characteristic described in connection with the embodiment is included in at least one embodiment of the present disclosure. Therefore, it is emphasized and should be appreciated that two or more references to “an embodiment” or “one embodiment” or “an alternative embodiment” in various portions of this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures or characteristics may be combined as suitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects of the present disclosure may be illustrated and described herein in any of a number of patentable classes or context including any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof. Accordingly, aspects of the present disclosure may be implemented entirely hardware, entirely software (including firmware, resident software, micro-code, etc. ) or combining software and hardware implementation that may all generally be referred to herein as a “module, ” “unit, ” “component, ” “device, ” or “system. ” Furthermore, aspects of the present disclosure may take the form of a computer program product embodied in one or more computer readable media having computer readable program code embodied thereon.

A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including electro-magnetic, optical, or the like, or any suitable combination thereof. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that may communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable signal medium may be transmitted using any appropriate medium, including wireless, wireline, optical fiber cable, RF, or the like, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Scala, Smalltalk, Eiffel, JADE, Emerald, C++, C#, VB. NET, Python or the like, conventional procedural programming languages, such as the "C" programming language, Visual Basic, Fortran 2003, Perl, COBOL 2002, PHP, ABAP, dynamic programming languages such as Python, Ruby and Groovy, or other programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN) , or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider) or in a cloud computing environment or offered as a service such as a Software as a Service (SaaS) .

Furthermore, the recited order of processing elements or sequences, or the use of numbers, letters, or other designations therefore, is not intended to limit the claimed processes and methods to any order except as may be specified in the claims. Although the above disclosure discusses through various examples what is currently considered to be a variety of useful embodiments of the disclosure, it is to be understood that such detail is solely for that purpose, and that the appended claims are not limited to the disclosed embodiments, but, on the contrary, are intended to cover modifications and equivalent arrangements that are within the spirit and scope of the disclosed embodiments. For example, although the implementation of various components described above may be embodied in a hardware device, it may also be implemented as a software only solution, e.g., an installation on an existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description of embodiments of the present disclosure, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure aiding in the understanding of one or more of the various embodiments. This method of disclosure, however, is not to be interpreted as reflecting an intention that the claimed subject matter requires more features than are expressly recited in each claim. Rather, claim subject matter lie in less than all features of a single foregoing disclosed embodiment.

Claims

A method implemented on a computing device having at least one processor, at least one computer-readable storage medium, and a data exchange port communicatively connected to a network for POI retrieving, the method comprising:

obtaining a query initiated in a local region via communicating with a terminal device of a user over a network;

determining a first number of points of interest (POIs) in the local region based on the query;

determining a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number;

merging the first number of POIs and the second number of POIs;

ranking the merged POIs according to the query; and

displaying at least a portion of the merged POIs on the terminal device of the user according to the ranking.
The method of claim 1, wherein determining the second number of POIs out of the local region based on the query, the cross-regional list associated with the local region, and the first number includes:

determining whether the first number of POIs is smaller than a threshold; and

in response to the determination that the first number of POIs is smaller than the threshold,

determining the second number of POIs out of the local region based on the query and the cross-regional list associated with the local region.
The method of claim 2, wherein the cross-regional list associated with the local region includes at least one region out of the local region.
The method of claim 3, wherein determining the second number of POIs out of the local region based on the query and the cross-regional list associated with the local region includes:

obtaining the at least one region out of the local region from the cross-regional list associated with the local region; and

determining the second number of POIs out of the local region by determining POIs in each of the at least one region out of the local region based on the query.
The method of claim 3, wherein the at least one region out of the local region is determined using a cross-regional recognition method, the cross-regional recognition method including:

obtaining a plurality of cross-regional orders of the user in a historical time period;

determining the number of orders directed, from the local region, to each of multiple regions based on the plurality of cross-regional orders;

determining a cross-regional rate of each of the multiple regions; and

determining the at least one region out of the local region based on the cross-regional rate of each of the multiple regions.
The method of claim 5, wherein determining the at least one region out of the local region based on the cross-regional rate of each of the multiple regions includes:

determining whether the cross-regional rate of each of the multiple regions is larger than a preset rate; and

in response to the determination that the cross-regional rate of a region is larger than the preset rate,

determining the region as one of the at least one region out of the local region.
The method of claim 1, wherein ranking the merged POIs according to the query includes:

obtaining a learning to rank (LTR) model; and

ranking, using the LTR model, the merged POIs according to the query.
The method of claim 7, wherein LTR model is trained according to at least one of a distance between the user and a POI, hot degree of a POI, a historical click rate of a POI, or a textual relevance.
The method of any one of claims 1 to 8, wherein the local region is determined based on location information of the terminal device of the user.
The method of claim 9, wherein the location information includes at least one of Global Positioning System (GPS) information, base station information, or wireless fidelity (WIFI) Internet protocol (IP) address information.
A system for POI retrieving, comprising:

at least one computer-readable storage medium;

a data exchange port communicatively connected to a network; and

at least one processor configured to communicate with the at least one computer-readable storage medium, wherein when executing the set of instructions, the at least one processor is directed to:

obtain a query initiated in a local region via communicating with a terminal device of a user over a network;

determine a first number of points of interest (POIs) in the local region based on the query;

determine a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number;

merge the first number of POIs and the second number of POIs;

rank the merged POIs according to the query; and

display at least a portion of the merged POIs on the terminal device of the user according to the ranking.
The system of claim 11, wherein to determine the second number of POIs out of the local region based on the query, the cross-regional list associated with the local region, and the first number, the at least one processor is directed to:

determine whether the first number of POIs is smaller than a threshold; and

in response to the determination that the first number of POIs is smaller than the threshold,

determine the second number of POIs out of the local region based on the query and the cross-regional list associated with the local region.
The system of claim 12, wherein the cross-regional list associated with the local region includes at least one region out of the local region.
The system of claim 13, wherein to determine the second number of POIs out of the local region based on the query and the cross-regional list associated with the local region, the at least one processor is directed to:

obtain the at least one region out of the local region from the cross-regional list associated with the local region; and

determine the second number of POIs out of the local region by determining POIs in each of the at least one region out of the local region based on the query.
The system of claim 13, wherein the at least one region out of the local region is determined using a cross-regional recognition method, the at least one processor is directed to:

obtain a plurality of cross-regional orders of the user in a historical time period;

determine the number of orders directed, from the local region, to each of multiple regions based on the plurality of cross-regional orders;

determine a cross-regional rate of each of the multiple regions; and

determine the at least one region out of the local region based on the cross-regional rate of each of the multiple regions.
The system of claim 15, wherein to determine the at least one region out of the local region based on the cross-regional rate of each of the multiple regions, the at least one processor is directed to:

determine whether the cross-regional rate of each of the multiple regions is larger than a preset rate; and

in response to the determination that the cross-regional rate of a region is larger than the preset rate,

determine the region as one of the at least one region out of the local region.
The system of claim 11, wherein to rank the merged POIs according to the query, the at least one processor is directed to:

obtain a learning to rank (LTR) model; and

rank, using the LTR model, the merged POIs according to the query.
The system of claim 17, wherein LTR model is trained according to at least one of a distance between the user and a POI, hot degree of a POI, a historical click rate of a POI, or a textual relevance.
The system of any one of claims 11 to 18, wherein the local region is determined based on location information of the terminal device of the user.
The system of claim 19, wherein the location information includes at least one of Global Positioning System (GPS) information, base station information, or wireless fidelity (WIFI) Internet protocol (IP) address information.
A non-transitory computer readable medium, comprising at least one set of instructions for POI retrieving, wherein when executed by at least one processor of a computing device, the at least one set of instructions directs the at least one processor to perform a method, the method comprising:

obtaining a query initiated in a local region via communicating with a terminal device of a user over a network;

determining a first number of points of interest (POIs) in the local region based on the query;

determining a second number of POIs out of the local region based on the query, a cross-regional list associated with the local region, and the first number;

merging the first number of POIs and the second number of POIs;

ranking the merged POIs according to the query; and

displaying at least a portion of the merged POIs on the terminal device of the user according to the ranking.