CN111382218A

CN111382218A - System and method for point of interest (POI) retrieval

Info

Publication number: CN111382218A
Application number: CN201811639983.8A
Authority: CN
Inventors: 郑万吉; 陈欢; 宋奇; 马利
Original assignee: Beijing Didi Infinity Technology and Development Co Ltd
Current assignee: Beijing Didi Infinity Technology and Development Co Ltd
Priority date: 2018-12-29
Filing date: 2018-12-29
Publication date: 2020-07-07
Anticipated expiration: 2038-12-29
Also published as: WO2020133548A1; CN111382218B

Abstract

The embodiment of the application discloses a system and a method for searching points of interest. The interest point retrieval method comprises the steps of communicating with user terminal equipment through a network to obtain a query word initiated in a local area; determining a first number of points of interest in the local area based on the query term; determining a second number of points of interest outside the local area based on the query term, a cross-area list associated with the local area, and the first number; merging the first quantity of interest points and the second quantity of interest points, and sequencing the merged interest points according to the query terms; and displaying at least a part of the combined interest points on the user terminal equipment according to the sorting result. According to the interest point retrieval method, the cross-region intention of the user can be identified, the local region and the related interest points outside the local region can be recalled together, the ranking recommendation is carried out according to the model, and the cross-region retrieval problem of the user can be solved.

Description

System and method for point of interest (POI) retrieval

Technical Field

The present application relates to map-based services and platforms, and more particularly, to a system and method for retrieving a Point of interest (POI).

Background

With the development of the internet, online services such as taxi services and the like are beginning to play an important role in daily life. When a user inputs a query term related to a travel destination in a taxi service, the server may retrieve POIs and recommend at least two POIs to the user in response to the query term. The POIs retrieved and recommended are determined based on the current location of the user. In some scenarios, a user currently located in a local area may have a cross-regional travel need. For example, a user may search for destinations outside of a local area. However, the server still retrieves and recommends at least two POIs in the local area based on the user's current location. Accordingly, there is a need to provide a system and method that will retrieve POIs in a local area and one or more target areas outside the local area to improve the user experience of an online service platform.

Disclosure of Invention

One of the embodiments of the present application provides a POI retrieval method, including: communicating with terminal equipment of a user through a network to obtain a query word initiated in a local area; determining a first number of POIs in the local area based on the query term; determining a second number of POIs outside the local area based on the query term, a cross-area list associated with the local area, and the first number; merging the first number of POIs and the second number of POIs; sorting the merged POI according to the query word; and displaying at least a part of the merged POI on the terminal equipment of the user according to the sorting result.

One of the embodiments of the present application provides a POI retrieval system, which may include an acquisition module, a processing module, and a communication module. The processing module further comprises a first POI determination unit, a second POI determination unit, a merging unit, and a ranking unit. The acquisition module is used for communicating with terminal equipment of a user through a network to acquire the query words initiated in the local area. The first POI determination unit is configured to determine a first number of POIs in the local area based on the query term. The second POI determining unit is to determine a second number of POIs outside the local area based on the query term, a cross-area list associated with the local area, and the first number. The merging unit is configured to merge the first number of POIs and the second number of POIs. The ranking unit is used for ranking the merged POI according to the query words. And the communication module is used for displaying at least a part of the merged POI on the user terminal equipment according to the sorting result.

In some embodiments, the second POI determination unit is further to: determining whether the first number of POIs is less than a threshold; and in response to the determination that the first number of POIs is less than the threshold, determining a second number of POIs outside the local area based on the query terms and a cross-area list associated with the local area.

In some embodiments, the cross-zone list associated with the local zone includes at least one zone outside the local zone.

In some embodiments, the second POI determination unit is further to: obtaining at least one region outside the local region from a cross-region list associated with the local region; and determining a second number of POIs outside the local area by determining POIs in each of at least one area outside the local area based on the query terms.

In some embodiments, the second POI determination unit is further to: acquiring at least two cross-region orders of the user in a historical time period; determining a number of orders from the local area to each of a plurality of areas based on the at least two cross-area orders; determining a cross-region probability for each of the plurality of regions; and determining at least one region outside the local region based on the cross-region probability of each of the plurality of regions.

In some embodiments, the second POI determination unit is further to: determining whether a cross-region probability of each of the plurality of regions is greater than a preset probability; and in response to the cross-region probability of the determined region being greater than the preset probability, determining the region as one of at least one region outside the local region.

In some embodiments, the sorting unit is further configured to: acquiring a learning sequencing model; and using the learning ranking model to rank the merged POI according to the query words.

In some embodiments, a learned ranking model is trained based on at least one of a distance between the user and a POI, a heat of the POI, a historical click-through rate of the POI, or a text relevance.

One of the embodiments of the present application provides a POI retrieval system that may include at least one computer-readable storage medium, a communication data exchange port connected to a network, and at least one processor configured to communicate with the at least one computer-readable storage medium. The at least one processor may be configured to communicate with a terminal device of a user via a network to obtain a query term initiated in a local area. The at least one processor may be configured to determine a first number of POIs in the local area based on the query term. The at least one processor may be configured to determine a second number of POIs outside the local area based on the query term, a cross-area list associated with the local area, and the first number. The at least one processor may be configured to merge the first number of POIs and the second number of POIs. The at least one processor may be configured to rank the merged POIs according to the query terms. The at least one processor may be configured to display at least a portion of the merged POI on the user terminal device according to the ranking result.

In some embodiments, the at least one processor may be further configured to determine whether the first number of POIs is less than a threshold; and in response to the determination that the first number of POIs is less than the threshold, determining a second number of POIs outside the local area based on the query terms and a cross-area list associated with the local area.

In some embodiments, the at least one processor may be further configured to obtain at least one region outside the local region from a cross-region list associated with the local region; and determining a second number of POIs outside the local area by determining POIs in each of at least one area outside the local area based on the query terms.

In some embodiments, the at least one processor may be further configured to obtain at least two cross-regional orders for the user over a historical period of time; determining a number of orders from the local area to each of a plurality of areas based on the at least two cross-area orders; determining a cross-region probability for each of the plurality of regions; and determining at least one region outside the local region based on the cross-region probability of each of the plurality of regions.

In some embodiments, the at least one processor may be further configured to determine whether a cross-region probability for each of the plurality of regions is greater than a preset probability; and in response to the cross-region probability of the determined region being greater than the preset probability, determining the region as one of at least one region outside the local region.

In some embodiments, the at least one processor may be further configured to obtain a learned ranking model; and using the learning ranking model to rank the merged POI according to the query words.

In some embodiments, the local zone may be determined from location information of the user terminal device.

In some embodiments, the location information includes at least one of: global positioning system information, base station information, wireless fidelity network protocol address information.

One of the embodiments of the present application provides a POI retrieval apparatus, including at least one storage medium and at least one processor, where the at least one storage medium is configured to store computer instructions, and the at least one processor is configured to execute the computer instructions to implement a POI retrieval method.

One of the embodiments of the present application provides a computer-readable storage medium, which stores computer instructions, and when the computer instructions are executed by a processor, the computer instructions can implement a POI retrieval method.

Additional features of the application may be set forth in the description which follows. Additional features of the present application will be set forth in part in the description which follows and in part will be apparent to those having ordinary skill in the art upon examination of the following description and accompanying drawings or may be learned from the manufacture or operation of the embodiments. The features of the present application may be realized and attained by practice or use of the methods, instrumentalities and combinations of the various aspects of the specific embodiments described below.

Drawings

The present application will be further described by way of exemplary embodiments. These exemplary embodiments will be described in detail by means of the accompanying drawings. The figures are not drawn to scale. These embodiments are not intended to be limiting, and like reference numerals refer to like parts throughout, wherein:

FIG. 1 is a schematic diagram of an exemplary online service system, shown in accordance with some embodiments of the present application;

FIG. 2 is a schematic diagram of exemplary components of a computing device shown in accordance with some embodiments of the present application;

FIG. 3 is a schematic diagram of exemplary hardware and/or software components of an exemplary terminal device shown in accordance with some embodiments of the present application;

FIG. 4 is a block diagram of an exemplary processing engine shown in accordance with some embodiments of the present application;

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

FIG. 6 is a block diagram of an exemplary processing module shown in accordance with some embodiments of the present application;

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

FIG. 8 is a flow diagram illustrating an exemplary process for determining at least one area outside of a local area in accordance with some embodiments of the present application;

FIG. 9 is a schematic diagram of an exemplary user interface of a terminal device displaying query terms and POIs, shown in accordance with some embodiments of the present application; and

FIG. 10 is a schematic diagram illustrating an exemplary process for retrieving one or more POIs based on query terms in accordance with some embodiments of the present application.

Detailed Description

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings used in the description of the embodiments will be briefly introduced below. It is to be understood that the drawings in the following description are merely exemplary or exemplary of the application. It will be clear to a person skilled in the art that the present application can also be applied to other similar scenarios according to these figures without inventive effort. Unless otherwise apparent from the context, or otherwise indicated, like reference numbers in the figures refer to the same structure or operation.

As used in this specification and the claims, the singular forms "a", "an" and "the" may include the plural forms as well, unless expressly specified otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this application, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, components, and/or groups thereof.

Although various references are made herein to certain modules in a system according to embodiments of the present application, any number of different modules may be used and run on the client and/or server. These modules are intended to be illustrative, and not to limit the scope of the present application. Different modules may be used in different aspects of the present systems and methods.

A flowchart is used to illustrate the operations performed by the system, according to some embodiments of the present application. It should be understood that the preceding and following operations are not necessarily performed in order. Rather, various steps may be processed in reverse order or simultaneously. Further, one or more other operations may be added to the flowchart. One or more operations may also be deleted from the flowchart.

Technical solutions of embodiments of the present application are described with reference to the drawings described below. It is to be understood that the described embodiments are not intended to be all-inclusive and not restrictive. Other embodiments, which can be derived by one of ordinary skill in the art without any inventive work based on the embodiments in the present application, are within the scope of the present application.

In addition, the system and the method in the application can be applied to any application scene that a user needs to search for POI. For example, the systems and methods of the present application may be applied to different transportation systems, including terrestrial, marine, aerospace, and the like, or any combination thereof. The transportation system may provide transportation services to users using various vehicles. The vehicles of the transportation service may include taxis, private cars, trailers, buses, trains, motor cars, high-speed rails, subways, ships, airplanes, space vehicles, hot air balloons, unmanned vehicles, bicycles, tricycles, motorcycles, and the like, or any combination thereof. The system or the method can be applied to taxi service, special car service, delivery service, carpooling, public transportation service, takeout service, driver generation driving, vehicle leasing, bicycle sharing service, train service, subway service, regular bus service, positioning service and the like. Application scenarios of the system or method of the present application may include web pages, browser plug-ins, client terminals, client systems, internal analytics systems, artificial intelligence robots, and the like, or any combination thereof.

One aspect of the present application relates to a system for cross-regional POI retrieval. When a user enters a query term to initiate a search for POIs, the online service platform may provide the user with at least two POIs related to the query term. Upon receiving a query term initiated in the local area from a terminal device (e.g., a user's smartphone), the online service platform may determine a first number of POIs in the local area based on the query term. The online platform may also determine a second number of POIs outside the local area (e.g., according to the user's cross-regional intent) based on the query term, the cross-regional list associated with the local area, and the first number. The online service platform may merge the first number of POIs and the second number of POIs, and rank the merged POIs according to the query terms and using a learning ranking (LTR) model. The online service platform can also display at least a part of the merged POI on the user terminal equipment according to the sorting result. The user may select one of the displayed one or more POIs for quick input.

FIG. 1 is a schematic diagram of an exemplary online service system, shown in accordance with some embodiments of the present application. The online 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 of the online service system 100. In some embodiments, the server 110 may be a single server or a group of servers. The set of servers can be centralized or distributed (e.g., the server 110 can be a distributed system). In some embodiments, the server 110 may be local or remote. For example, server 110 may access information and/or data stored in terminal device 140 and/or storage device 130 via network 120. As another example, server 110 may be directly connected to terminal device 140 and/or storage device 130 to access stored information and/or data. In some embodiments, the server 110 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-tiered cloud, and the like, or any combination thereof. In some embodiments, server 110 may execute on computing device 200 described in FIG. 2, which includes one or more components.

In some embodiments, the server 110 may include a processing engine 112. Processing engine 112 may process information and/or data to perform one or more functions described herein. For example, processing engine 112 may determine a first number of POIs in the local area based on the query terms. For another example, the processing engine 112 may determine a second number of POIs in the local area based on the query terms, the cross-area list associated with the local area, and the first number of POIs. As yet another example, the processing engine 112 may merge the first number of POIs and the second number of POIs. As yet another example, the processing engine 112 may rank the merged POIs according to the query terms. In some embodiments, processing engine 112 may include one or more processing engines (e.g., a single core processing engine or a multi-core processor). By way of example only, 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), an image processing unit (GPU), a physical arithmetic 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.

Network 120 may facilitate the exchange of information and/or data. In some embodiments, one or more components in the online 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 components in the online service system 100 over the network 120. For example, processing engine 112 may obtain query terms (e.g., user input regarding his/her travel destination) from storage device 130 and/or terminal device 140 via network 120. In some embodiments, the network 120 may be any one of, or a combination of, a wired network or a wireless network. By way of example only, network 120 may include a cable network, a wired network, a fiber optic 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 Public Switched Telephone Network (PSTN), a bluetooth network, a ZigBee network, a Near Field Communication (NFC) network, the like, or any combination thereof. In some embodiments, network 120 may include one or more network access points. For example, 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 online service system 100 may connect to network 120 to exchange data and/or information.

Storage device 130 may store data and/or instructions. In some embodiments, storage device 130 may store data obtained from end device 140 and/or processing engine 112. For example, the storage device 130 may store the query term acquired from the terminal device 140. As another example, the storage device 130 may store a first number of POIs in a local area and a second number of POIs outside the local area. As yet another example, the storage device 130 may store POIs determined by ranking a first number of POIs in the local area and a second number of POIs outside the local area. In some embodiments, storage device 130 may store data and/or instructions that server 110 uses to perform or use to perform the exemplary methods described in this application. For example, the storage device 130 may store instructions that the processing engine 112 may execute or use to determine POIs. In some embodiments, storage 130 may include mass storage, removable storage, volatile read-write memory, read-only memory (ROM), and the like, or any combination thereof. Exemplary mass storage may include magnetic disks, optical disks, solid state disks, and the like. Exemplary removable memory may include flash drives, floppy disks, optical disks, memory cards, compact disks, magnetic tape, and the like. Exemplary volatile read-only memory can include Random Access Memory (RAM). Exemplary RAM may include Dynamic RAM (DRAM), double-data-rate synchronous dynamic RAM (DDRSDRAM), Static RAM (SRAM), thyristor RAM (T-RAM), zero-capacitance RAM (Z-RAM), and the like. Exemplary ROMs may include Mask ROM (MROM), Programmable ROM (PROM), Erasable Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), compact disk ROM (CD-ROM), digital versatile disk ROM, and the like. In some embodiments, the storage device 130 may be implemented on a cloud platform. By way of example only, the cloud platform may include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-tiered cloud, and the like, or any combination thereof.

In some embodiments, a storage device 130 may be connected to network 120 to communicate with one or more components in online service system 100 (e.g., server 110, terminal device 140, etc.). One or more components in online service system 100 may access data or instructions stored in storage 130 via network 120. In some embodiments, the storage device 130 may be directly connected to or in communication with one or more components in the online service system 100 (e.g., server 110, terminal device 140). In some embodiments, storage device 130 may be part of server 110.

In some embodiments, the end 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, mobile device 140-1 may include a smart home device, a wearable device, a smart mobile device, a virtual reality device, an augmented reality device, and the like, or any combination thereof. In some embodiments, the smart home devices may include smart lighting devices, smart appliance control devices, smart monitoring devices, smart televisions, smart cameras, interphones, and the like, or any combination thereof. In some embodiments, the wearable device may include a bracelet, footwear, glasses, helmet, watch, clothing, backpack, smart accessory, and the like, or any combination thereof. In some embodiments, the mobile device may include a mobile phone, a Personal Digital Assistant (PDA), a gaming device, a navigation device, a point of sale (POS) device, a laptop, a desktop, and the like, or any combination thereof. In some embodiments, the virtual reality device and/or augmented reality device may include a virtual reality helmet, virtual reality glasses, virtual reality eyecups, augmented reality helmets, augmented reality glasses, augmented reality eyecups, and the like, or any combination thereof. For example, the virtual reality device and/or augmented reality device may include a Google Glass^TM、RiftCon^TM、Fragments^TM、Gear VR^TMAnd the like. In some embodiments, the online service system 100 may be implemented on a terminal device 140.

It should be noted that the online service system 100 is provided for illustrative purposes only and is not intended to limit the scope of the present application. Various modifications and changes may occur to those skilled in the art in light of the description herein. For example, the online service system 100 may also include databases, information sources, and the like. As another example, the online service system 100 may be implemented on other devices to perform similar or different functions. However, such modifications and changes do not depart from the scope of the present application.

FIG. 2 is a schematic diagram of exemplary components of a computing device on which server 110, storage device 130, and/or terminal device 140 may be implemented according to some embodiments of the present application. This particular system uses a functional block diagram to explain a hardware platform that includes one or more user interfaces. The computing device may be a general purpose computer or may be a special purpose computer. Both computers may be used to implement the particular system in this embodiment. Computing device 200 may be configured to implement any components that perform one or more of the functions disclosed herein. For example, computing device 200 may implement any of the components of online service system 100 as described herein. In fig. 1-2, only one computing device is shown for convenience. At the time of filing this application, those of ordinary skill in the art will appreciate that the computing functionality associated with determining POIs as described herein may be implemented in a distributed manner across a plurality of similar platforms to distribute processing load.

For example, the computing device 200 may include a Communication (COM) port 250 that connects to a network and facilitates data communication. Computing device 200 may also include a processor (e.g., processor 220) in the form of one or more processors (e.g., logic circuits) for executing program instructions. For example, a processor may include interface circuitry and processing circuitry therein. The interface circuit may be configured to receive electronic signals from bus 210, where the electronic signals encode structured data and/or instructions for processing by the processing circuit. The processing circuitry may perform logical computations and then determine conclusions, results, and/or instructions encoded as electronic signals. The interface circuit may then issue electronic signals from the processing circuit via bus 210.

Exemplary computing devices may include an internal communication bus 210, program storage, and various forms of data storage, including, for example, a hard disk 270, and Read Only Memory (ROM)230 or Random Access Memory (RAM)240 for processing and/or transmitting various data files through the computing device. The exemplary computing platform may also include program instructions stored in ROM230, RAM 240, and/or other forms of non-transitory storage media that are capable of being executed by processor 220. The methods and/or processes of the present application may be embodied in the form of program instructions. Computing device 200 also includes input/output component 260, which supports input/output between the computer and other components. Computing device 200 may also receive programming and data via network communications.

For illustration only, only one CPU and/or processor is shown in FIG. 2. Multiple CPUs and/or processors are also contemplated; thus, operations and/or method steps performed by one CPU and/or processor described herein may also be performed by multiple CPUs and/or processors, either jointly or separately. For example, if in the present application the CPUs and/or processors of computing device 200 perform steps a and B, it should be understood that steps a and B may also be performed by two different CPUs and/or processors of computing device 200, either collectively or independently (e.g., a first processor performing step a, a second processor performing step B, or a first and second processor collectively performing steps a and B).

FIG. 3 is a schematic diagram of exemplary hardware and/or software components of an exemplary terminal device shown in accordance with some embodiments of the present application; according to some embodiments of the present application, terminal device 140 may be implemented thereon. As shown in fig. 3, mobile device 300 may include a communication unit 310, a display 320, a Graphics Processing Unit (GPU)330, a Central Processing Unit (CPU)340, input/output 350, memory 360, and storage 390. CPU 340 may include interface circuitry and processing circuitry similar to 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 mobile device 300. In some embodiments, an operating system 370 (e.g., iOS)^TM、Android^TM、Windows Phone^TM) And one or more application programs 380 may be loaded from storage 390 into memory 360 for execution by CPU 340. Applications 380 may include a browser or any other suitable mobile application for use on mobile device 300 based on locationReceives and displays information related to the query term or other information. User interaction with the information flow may be accomplished via input/output 350 and provided to processing engine 112 and/or other components of online service system 100 via network 120.

To implement the various modules, units and their functionality described above, a computer hardware platform may be used as the hardware platform for one or more elements (e.g., components of server 110 described in fig. 2). Since these hardware elements, operating systems, and programming languages are common, it can be assumed that those skilled in the art are familiar with these techniques and that they are able to provide the information needed in POI determination according to the techniques described in this application. A computer with a user interface may be used as a Personal Computer (PC) or other type of workstation or terminal device. After proper programming, a computer with a user interface may act as a server. It is believed that one skilled in the art may also be familiar with the structure, programming, or general operation of this type of computer device. Therefore, no additional explanation is described with respect to the drawings.

Fig. 4 is a block diagram of an exemplary processing engine 112 shown in accordance with some embodiments of the present application. The processing engine 112 may include an acquisition module 410, a processing module 420, an input/output module 430, and a communication module 440. The module may be at least a portion of a hardware circuit of the processing engine 112. These modules may also be implemented as an application or set of instructions that are read and executed by the processing engine 112. Further, a module may be any combination of hardware circuitry and applications/instructions. For example, a module may be part of processing engine 112 when the processing engine executes an application/set of instructions.

The acquisition module 410 may acquire data/signals. The acquisition module 410 may acquire data/signals from one or more components of the online service system 100 (e.g., the terminal device 140, the input/output module 430, the storage device 130) or external devices (e.g., a cloud database). For example only, the acquired data/signals may include user query terms, user instructions, programs, algorithms, and the like, or any combination thereof.

In some embodiments, the obtaining module 410 may obtain the query term from the terminal device 140 via the network 120. In some embodiments, the query term initiated in the local region may be a location name, location abbreviation, location symbol, synonym of location, etc. related to the online service (e.g., taxi service). The location may be a starting location, a boarding location, a destination, etc. In some embodiments, the query terms may be in the form of text, audio, video, or graphics. For example, the query term may be "west two flag", "chinese bank", or "shopping mall".

In some embodiments, the retrieval module 410 may send the retrieved query terms to other units and/or modules of the processing engine 112 for further processing. For example, the acquisition module 410 may send the query term to the processing module 420 for further processing (e.g., rewriting the query term, correcting the spelling of the query term). As another example, the retrieval module 410 may send the query term to a storage device (e.g., storage device 130) for storage.

The processing module 420 may process the data/signals. The processing module 420 may retrieve the data/signals from the retrieval module 410, the input/output module 430, and/or any storage device 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 the local area based on the query terms obtained from the obtaining module 410. In some embodiments, the processing module 420 may determine a second number of POIs outside the local area based on the query term, the cross-area list associated with the local area, and the first number. In some embodiments, the processing module 420 may determine a merged POI based on the first number of POIs and the second number of POIs. For example, the processing module 420 may determine a merged POI by combining the first number of POIs with the second number of POIs. In some embodiments, the processing module 420 may use the LTR model to rank the merged POIs according to query terms. As used herein, the LTR model may be configured to rank POIs based on feature information and query terms associated with at least two POIs.

Processing module 420 may include a hardware processor such as a microcontroller, microprocessor, Reduced Instruction Set Computer (RISC), Application Specific Integrated Circuit (ASIC), application specific instruction set processor (ASIP), Central Processing Unit (CPU), Graphics Processing Unit (GPU), Physical Processing Unit (PPU), microcontroller unit, Digital Signal Processor (DSP), Field Programmable Gate Array (FPGA), Advanced RISC Machine (ARM), Programmable Logic Device (PLD), any circuit or processor capable of performing one or more functions, and the like or any combination thereof.

The input/output module 430 may input or output data or information. For example, the input/output module 430 may input a query term of the user. As another example, the input/output module 430 may output one or more POIs. In some embodiments, the input/output module 430 may include an input device and an output device. Exemplary input devices may include a keyboard, mouse, touch screen, microphone, etc., or a combination thereof. Exemplary output devices may include a display device, speakers, printer, projector, etc., or any combination thereof. Exemplary display devices may include Liquid Crystal Displays (LCDs), Light Emitting Diode (LED) based displays, flat panel displays, curved screens, television devices, Cathode Ray Tubes (CRTs), and the like, or combinations thereof.

The communication module 440 may be connected to a network (e.g., network 120) to facilitate data communication. Communication module 440 may establish a connection between processing engine 112 and end device 140 and/or storage device 130. For example, the communication module 440 may send at least a portion of the merged POI (e.g., top 1, top 2, top 5, top 10, top 1%, top 5%, top 10%, top 30%) determined by the processing module 420 to the user interface of the application in the terminal device 140. The connection may be a wired connection, a wireless connection, any other communication connection capable of data transmission and/or reception, and/or any combination of these connections. For example, the wired connection may include an electrical cable, an optical cable, a telephone line, etc., or any combination thereof. The wireless connection may include, for example, a bluetooth connection, a wireless network connection, a WLAN link, a zigbee (tm) connection, a mobile network connection (e.g., a 3G, 4G, 5G network, 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, and the like.

It should be noted that the above description of the processing module 420 is merely a specific example and should not be considered the only possible implementation. Various modifications and changes may occur to those skilled in the art in light of the description herein. For example, processing engine 112 may also include a storage module that facilitates data storage. However, such modifications and changes do not depart from the scope of the present application.

Fig. 5 is a flow diagram illustrating an exemplary process 500 for displaying one or more merged POIs on a user terminal device, in accordance with some embodiments of the present application. In some embodiments, process 500 may be implemented in online service system 100. For example, process 500 may be stored as instructions in storage device 130 and/or memory (e.g., ROM230, RAM 240, etc.) and invoked and/or executed by server 110 (e.g., processing engine 112 in server 110 or processor 220 of processing engine 112 in server 110).

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

The query term initiated in the local area may be a location name, a location abbreviation, a location symbol, a synonym of a location, etc. related to an online service (e.g., a taxi service). The location may be a starting location, a boarding location, a destination, etc. In some embodiments, the query terms may be in the form of text, audio, video, or graphics. For example, the query term may be "west two flag", "chinese bank", or "shopping mall".

In some embodiments, the query terms may correspond to a local region. In some embodiments, the local region may be a region where the terminal device 140 is located when the user of the terminal device 140 transmits the query term. For example, acquisition module 410 may acquire location information (e.g., Global Positioning System (GPS) information, base station information, wireless fidelity (WIFI) network protocol (IP) address information) of terminal device 140 that may display the current location of terminal device 140 in real-time or substantially real-time (e.g., 1 second, 10 seconds, 1 minute). As another example, when a user enters a query term and begins searching for POIs, the user may select or enter a local area. In some embodiments, the local region may be any administrative region, such as a country, province, city, or district.

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

In some embodiments, the processing module 420 may determine one or more merged POIs based on a first number of POIs in the local area and a second number of POIs outside the local area. In some embodiments, the processing module 420 may determine the first number of POIs in the local area by comparing the query terms to POIs in the local area stored in a storage device (e.g., storage device 130) of the online service system 100 or an external storage device. In some embodiments, the processing module 420 may determine a second number of POIs outside the local area based on the query term, the cross-area list associated with the local area, and the first number. In some embodiments, the processing module 420 may identify a cross-region intent associated with the query term based on the first quantity. For example, the processing module 420 may identify a cross-region intent of the user by determining whether the first number of POIs is less than a preset threshold. In response to determining that the first number of POIs is less than a preset threshold, indicating that the user has cross-region intent. After determining that the user has a cross-region intent, the processing module 420 may determine a second number of POIs based on the query terms, and a cross-region list associated with the local region. The cross-zone list associated with the local zone may include at least one zone outside the local zone. In some embodiments, at least one of the local areas (e.g., fig. 7 and 8, and the description thereof) may be determined based on at least two cross-area orders by the user over a historical period of time using a cross-area identification method described elsewhere in this application. The processing module 420 may determine a second number of POIs outside the local area by determining POIs in each of at least one area outside the local area based on the query terms.

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 query terms using the LTR model. In some embodiments, the processing module 420 may determine at least a portion of the merged POI (e.g., top 1, top 2, top 5, top 10, top 1%, top 5%, top 10%, top 30%) to be displayed on the user's terminal device.

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

In some embodiments, the displayed merged POIs may be displayed in order according to the ranking results of the merged POIs, as described in connection with step 520. In the user interface of the application in the terminal device 140, the top of the POI list (e.g., POI list 930 in fig. 9) displays the top ranked POIs. For example, based on historical click rates of POIs, the merged POIs are displayed. The POI with the highest historical click through rate may be displayed at the top of the POI list.

It should be noted that the foregoing description is provided for the purpose of illustration only, and is not intended to limit the scope of the present application. Various modifications and changes may occur to those skilled in the art in light of the description herein. However, such modifications and changes do not depart from the scope of the present application.

Fig. 6 is a block diagram of an exemplary processing module shown in accordance with some embodiments of the present application. In some embodiments, the processing module 420 includes a first POI determination unit 610, a second POI determination unit 620, a merging unit 630, and a ranking unit 640.

The first POI determining unit 610 may determine a first number of POIs in the local area. In some embodiments, the first POI determination unit 610 may determine a first number of POIs in the local area based on a query term initiated in the local area. In some embodiments, the first POI determination unit 610 may determine the first number of POIs in the local area by comparing the query term with POIs in the local area stored in a storage device (e.g., the storage device 130) of the online service system 100 or an external storage device. For example, the first POI determining unit 610 may determine a first number of POIs in the local area that are the same as or substantially similar to the query term. As used herein, "substantially similar" means that the similarity between the query term and the POI is greater than a threshold (e.g., 98%, 95%, 90%, 85%), or that the query term and the POI are synonyms. For example only, assuming that the query word is "chinese bank", the first POI determination unit 610 determines at least two POIs, for example, "chinese bank bus station", "chinese bank subway station", "chinese bank building" as the first number of POIs.

In some embodiments, the first POI determination unit 610 may process the query term and determine the first number of POIs based on the processed query term. For example, the first POI determination unit 610 may rewrite a query word (e.g., "chinese bank") as a synonym (e.g., "BOC"). For another example, if the query word is misspelled, the first POI determination unit 610 may correct the spelling of the query word.

In some embodiments, the first POI determination unit 610 may send 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 transmit the first number of POIs to the second POI determination unit 620 to determine a second number of POIs outside the local area. For another example, the first POI determination unit 610 may transmit the first number of POIs to the merging unit 630 to merge the first number of POIs and the second number of POIs.

The second POI determining unit 620 may determine a second number of POIs outside the local area. In some embodiments, the second POI determination unit 620 may determine a second number of POIs outside the local area based on the query term, the cross-area list associated with the local area, and the first number. In some embodiments, the second POI determination unit 620 can identify the cross-region intent associated with the query term based on the first quantity. For example, the second POI determination unit 620 may identify the cross-region intention of the user by determining whether the first number of POIs is less than a preset threshold. In response to determining that the first number of POIs is less than a preset threshold, indicating that the user has cross-region intent. After determining that the user has the cross-region intent, the second POI determination unit 620 may determine a second number of POIs outside the local region based on the query terms and the cross-region list associated with the local region. The cross-zone list associated with the local zone may include at least one zone outside the local zone. In some embodiments, at least one of the local areas (e.g., fig. 7 and 8, and the description thereof) may be determined based on at least two cross-area orders by the user over a historical period of time using a cross-area identification method described elsewhere in this application. The second POI determining unit 620 may determine a second number of POIs outside the local area by determining POIs in each of at least one area outside the local area based on the query word. For example only, the second number of POIs outside the local area may be a sum of the number of POIs in each of the at least one area outside the local area.

In some embodiments, the second POI determination unit 620 can send the second number of POIs to other units and/or modules of the processing engine 112 for further processing. For example, the second POI determining unit 620 may transmit the second number of POIs to the merging unit 630 to merge 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 the merged POI by combining the first number of POIs with the second number of POIs. For example, the merging unit 630 may determine the merged table of POIs (i.e., the first number of POIs and the second number of POIs) by combining the table including the first number of POIs and the table including the second number of POIs.

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

The ranking unit 640 may rank the merged POIs. In some embodiments, the ranking unit 640 may rank the merged POIs according to query terms using the LTR model. As used herein, the LTR model is configured to rank at least two POIs based on feature information and query terms associated with the at least two POIs. Exemplary characteristic information associated with a POI may include a distance between the user and the POI, a popularity of the POI, a historical click-through rate of the POI, a textual relevance between the POI and query terms, and the like, or any combination thereof. In some embodiments, the ranking unit 640 may rank the merged POIs based on the historical click-through rate of each merged POI using the LTR model. For example, POIs with higher historical click-through rates may correspond to higher POI rankings. In some embodiments, the ranking unit 640 may rank the merged POIs based on a distance between the user and each of the merged POIs using the LTR model. For example, the merged POIs may be sorted in ascending order according to their distance from the user.

In some embodiments, the ranking unit 640 may send the ranking results 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 send the ranking result of the merged POI to the communication module 440 for displaying at least a part of the merged POI on the user terminal device.

It should be noted that the above description of the processing module 420 is merely a specific example and should not be considered the only possible implementation. Various modifications and changes may occur to those skilled in the art in light of the description herein. For example, the first POI determination unit 610 and the second POI determination unit 620 may be combined into one unit for determining a first number of POIs in the local area and a second number of POIs outside the local area. However, such modifications and changes do not depart from the scope of the present application.

Fig. 7 is a flow diagram illustrating an exemplary process 700 for displaying one or more merged POIs on a user terminal device, in accordance with some embodiments of the present application. In some embodiments, process 700 may be implemented in online service system 100. For example, process 700 may be stored in storage device 130 and/or memory (e.g., ROM230, RAM 240, etc.) in the form of instructions and invoked and/or executed by server 110 (e.g., processing engine 112 in server 110 or processor 220 of processing engine 112 in server 110).

At 710, the processing engine 112 (e.g., the obtaining module 410) may communicate with a terminal device of a user over a network to obtain query terms originating in a local area. In some embodiments, the processing engine 112 may obtain the query terms from the terminal device 140 via the network 120.

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

In some embodiments, for example, the user may send the query term to the processing engine 112 (e.g., the acquisition module 410) by pressing a button in the application interface after he/she enters the query term. In some embodiments, an application installed in the terminal device 140 may instruct the terminal device 140 to continuously or periodically monitor the user's query terms and automatically send the query terms to the processing engine 112 via the network 120.

The query term may be a location name, a location abbreviation, a location symbol, a synonym of a location, etc. related to an online service (e.g., a taxi service). The location may be a starting location, a boarding location, a destination, etc. In some embodiments, the query terms may be in the form of text, audio, video, or graphics. For example, the query term may be "west two flag", "chinese bank", or "shopping mall".

In some embodiments, the query terms may correspond to a local region. In some embodiments, the local region may be a region where the terminal device 140 is located when the user of the terminal device 140 transmits the query term. For example, processing engine 112 may obtain location information (e.g., GPS information, base station information, wireless fidelity (WIFI) network protocol (IP) address information) for terminal device 140 that may display the current location of terminal device 140 in real-time or substantially real-time (e.g., 1 second, 10 seconds, 1 minute). As another example, when a user enters a query term and begins searching for POIs, the user may select or enter a local area. In some embodiments, the local region may be any administrative region, such as a country, province, city, or district.

At 720, the processing engine 112 (e.g., the first POI determination unit 610) may determine a first number of POIs in the local area based on the query terms. As used herein, a POI may refer to a particular location point that may be of interest to a user. In some embodiments, the POI may be a location name, a business name (e.g., a company name, a shopping mall name), and so forth.

In some embodiments, the processing engine 112 may determine a first number of POIs in the local area by comparing the query terms to POIs in the local area stored in a storage device (e.g., storage device 130) of the online service system 100 or an external storage device. For example, processing engine 112 may determine a first number of POIs in the local area that are the same as or substantially similar to the query term. As used herein, "substantially similar" means that the similarity between the query term and the POI is greater than a threshold (e.g., 98%, 95%, 90%, 85%), or the query term is a synonym of the POI. For example only, assuming the query term is "chinese bank," processing engine 112 may determine at least two POIs, such as "chinese bank bus station," "chinese bank subway station," "chinese bank building," as the first number of POIs.

In some embodiments, processing engine 112 may process the query terms and determine a first number of POIs based on the processed query terms. For example, the processing engine 112 may rewrite a query term (e.g., "chinese bank") to a synonym (e.g., "BOC"). As another example, if the query term is misspelled, the processing engine 112 may correct the spelling of the query term.

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

In some embodiments, processing engine 112 may determine whether the first number of POIs is less than a threshold. The threshold may be set by the user according to default settings of the online service system 100 or adjusted in different situations. For example, the threshold may be between 15 and 20. In response to determining that the first number of POIs is less than the threshold, processing engine 112 may determine a second number of POIs outside the local area based on the query terms and the cross-area list associated with the local area.

The cross-zone list associated with the local zone may include at least one zone outside the local zone. In some embodiments, at least one of the local regions may be determined based on a cross-region identification method. For example, the processing engine 112 may retrieve historical orders that include at least two cross-regional orders for the user over a historical period of time. Processing engine 112 may determine an order quantity from the local area to each of the plurality of areas based on the at least two cross-area orders. The processing engine 112 may also determine at least one region outside the local region based on the cross-region probability for each of the plurality of regions. More description of determining a cross-region list may be found elsewhere in this application (e.g., fig. 8 and its description).

In some embodiments, processing engine 112 may determine a second number of POIs outside the local area based on the query terms and the cross-area list associated with the local area. For example, processing engine 112 may retrieve at least one of the local regions from a cross-region list associated with the local region. The processing engine 112 may determine a second number of POIs outside the local area by determining POIs in each of at least one area outside the local area based on the query terms. For example only, the second number of POIs outside the local area may be a sum of the number of POIs in each of at least one area outside the local area. In some embodiments, the processing engine 112 may determine the POIs in each of the at least one area outside the local area by comparing the query terms to the POIs stored in each of the at least one area outside the local area in a storage device (e.g., storage device 130) of the online service system 100 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 the merged POI by combining the first number of POIs with the second number of POIs. For example, the processing engine 112 may determine the table that includes the merged POI (i.e., the first number of POIs and the second number of POIs) by combining the table that includes the first number of POIs with the table that includes the second number of POIs.

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

In some embodiments, the processing engine 112 may rank the merged POIs based on a learned ranking (LTR) model. As used herein, the LTR model is configured to rank at least two POIs based on query terms and feature information associated with the at least two POIs. Exemplary characteristic information associated with a POI may include a distance between the user and the POI, a popularity of the POI, a historical click-through rate of the POI, a textual relevance between the POI and query terms, and the like, or any combination thereof. As used herein, the distance between a user and a POI may refer to a straight line distance or actual travel distance from the user's location to the POI. The popularity of a POI may indicate the popularity of the POI. For example, the popularity of a POI may refer to the number of times the user selects the POI within a particular time period. The historical click rate of the POI may refer to a probability that the user selects at least two POIs when the POIs are displayed on the user terminal apparatus. POIs with higher historical click rates correspond to higher user selection probabilities. For example, when the user inputs the query word "tianjin airport" in beijing, most users select "tianjin airport terminal" when both "tianjin airport terminal" and "beijing airport terminal" are displayed on the terminal device. In this case, the historical click rate of "tianjin airport terminal" is higher than the historical click rate of "beijing airport terminal" under the condition that the query word is "tianjin airport".

In some embodiments, the LTR model may be trained based on historical query terms of the user, historical POIs selected by the user based on the historical query terms, and feature information associated with the historical POIs. In some embodiments, the user may enter the historical query terms through an application in terminal device 140. The online service system 100 may transmit at least two associated historical POIs for display on the user interface of the application program in the terminal device 140 based on the historical query terms. The user may select one of the associated historical POIs of interest to him/her through a user interface of an application in the terminal device 140. The processing engine 112 may store the historical query terms and the selected historical POIs associated with the historical query terms in a storage device (e.g., storage device 130, memory 390) of the online service system 100 and/or an external data source.

In some embodiments, the processing engine 112 may retrieve the LTR model. In some embodiments, the processing engine 112 may retrieve the LTR model from a storage device (e.g., storage device 130, memory 390) of the online service system 100 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 platform or device) and stored in a storage device in the online service system 100. The processing engine 112 may access the storage device and retrieve the trained LTR model. The processing engine 112 may use the LTR model to rank the merged POIs according to query terms. In some embodiments, the processing engine 112 may rank the merged POIs based on the historical click-through rate of each merged POI using the LTR model. For example, POIs with higher historical click-through rates may correspond to higher POI rankings. In some embodiments, the processing engine 112 may rank the merged POIs based on the distance between the user and each merged POI using the LTR model. For example, the POIs may be sorted in an ascending order according to the distance between the merged POIs and the user.

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

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

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

It should be noted that the foregoing description is provided for illustrative purposes only, and is not intended to limit the scope of the present application. Various modifications and changes may occur to those skilled in the art in light of the description herein. In some embodiments, one or more steps may be added or omitted. For example, process 700 may also include the step of preprocessing the query term, e.g., correcting the query term or rewriting the query term. For another example, if the first number of POIs is greater than the threshold value, steps 730 and 740 may be omitted. However, such modifications and changes do not depart from the scope of the present application.

Fig. 8 is a flow diagram illustrating an exemplary process 800 for determining at least one area outside of a local area in accordance with some embodiments of the present application. In some embodiments, process 800 may be implemented in online service system 100. For example, process 800 may be stored in storage device 130 and/or memory (e.g., ROM230, RAM 240, etc.) in the form of instructions and invoked and/or executed by server 110 (e.g., processing engine 112 in server 110 or processor 220 of processing engine 112 in server 110).

At 810, the processing engine 112 (e.g., the second POI determination unit 620) may obtain at least two cross-region orders for the user over a historical period of time. Processing engine 112 may retrieve at least two cross-regional orders for a user from a storage device (e.g., storage device 130) and/or an external data source (not shown) of online service system 100 via network 120.

In some embodiments, the at least two cross-regional orders may be associated with an online service (e.g., a taxi service, a delivery service). For example, a cross-regional order may refer to an order from a first region to a second region, taking a taxi service as an example. The first region is different from the second region. That is, the starting location and destination of the cross-regional order are not in the same region. In some embodiments, the processing engine 112 may obtain a cross-regional order that the user has manually switched city operations within a historical period of time. For example, the user places the order in area a, and the user switches the area from area a to area B when inputting the destination. In some embodiments, each of the at least two cross-region orders may include identity information of the user (e.g., Identification (ID), phone number, user name), a query term from the user, one or more retrieved POIs associated with the query term, a POI selected by the user from the one or more retrieved POIs as a cross-region order service location (e.g., start location, destination), a start time point, an end time point, a start location, a destination, and the like, or any combination thereof. As used herein, the term "retrieved POI associated with a query term" refers to a POI determined by a processing engine in response to the query term 112. The start time point may refer to a time point at which the service provider starts providing the service. The end time point may refer to a time point at which the service provider ends the service. The starting location may refer to a location where the service provider starts providing the service. The destination may refer to a location where the service provider ends the service.

In some embodiments, the user completes the at least two cross-regional orders within a historical period of time. The historical time period may be a default setting for the online service system 100 or may be adjusted in different circumstances. For example, the historical time period may be the previous week, the previous month, the previous six months, and the like.

In 820, the processing engine 112 (e.g., the second POI determination unit 620) can determine an order quantity from the local area to each of the plurality of areas based on the at least two cross-area orders.

In some embodiments, processing engine 112 may select an order from a local area to a plurality of areas other than the local area from the at least two cross-area orders. That is, the start position of the selected order is in the local area, and the destination of the selected order is in a plurality of areas other than the local area. For each of the plurality of regions, the processing engine 112 may determine an order quantity from the local region to a region other than the local region. Assuming for purposes of illustration only that the local area is area a, processing engine 112 may select orders from area a to areas B, C, and D other than area a. Processing engine 112 may also determine the order quantity from area a to area B, the order quantity from area a to area C, and the order quantity from area a to area D.

At 830, the processing engine 112 (e.g., the second POI determination unit 620) can determine a cross-region probability for each of the plurality of regions other than the local region.

In some embodiments, the cross-region probability for each region may be determined based on the number of orders across the region and the number of orders to each region from the local region. For example, the cross-regional probability for a region may be the ratio of the number of orders from the local region to the number of orders across the region. For purposes of illustration only, it is assumed that the local area is area a and the plurality of areas includes area B, area C, and area D. The cross-region probability for region B may be a ratio of the number of orders from region a to region B (e.g., 100) to the number of orders from region a to region B, region C, and region D (e.g., 1000). That is, the cross-region probability of the 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 at least one area outside the local area based on the cross-area probability for each of the plurality of areas.

In some embodiments, the processing engine 112 may determine at least one region outside the local region based on the cross-region probability and the preset probability for each of the plurality of regions. The preset probability may be set by the user according to a default setting of the online service system 100 or adjusted in different cases. For example, the processing engine 112 may determine whether the cross-region probability for each of the plurality of regions is greater than a preset probability. In response to determining that the cross-region probability for the region is greater than the preset probability, the processing engine 112 may determine the region as one of at least one region outside the local region. For example, at least one region outside the local region may be determined according to equation (1):

P(city_B|city_A)＞θ (1)

wherein, the city_ARefers to a local area, city_BRefers to one of a plurality of areas outside the local area, P (city)_B|city_A) The cross-regional probability of the city B is indicated, and theta is a preset probability.

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

It should be noted that the foregoing description is provided for illustrative purposes only, and is not intended to limit the scope of the present application. Various modifications and changes may occur to those skilled in the art in light of the description herein. However, such modifications and changes do not depart from the scope of the present application. In some embodiments, after determining that the cross-region probability for an area is greater than the preset probability, the processing engine 112 may further determine whether the distance between the local area and the area is less than a predetermined distance (e.g., 200 kilometers). If the distance is less than the predetermined distance, the processing engine 112 may determine the region as one of at least one region outside the local region.

FIG. 9 is a schematic diagram of an exemplary user interface of a terminal device displaying query terms and POIs, shown in accordance with some embodiments of the present application. As shown 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 associated with the query term (e.g., determined based on the user's current location). The search box 920 may display the query term. The POI list 930 may display one or more POIs related to the query term. The user may select POIs of interest to him/her from the POI list 930. For example, assuming that the query word of the user is "chinese bank" and the local area associated with the query word is "beijing", the POI may be "chinese bank subway station, beijing city hai lake district", "chinese bank public transportation station, beijing city hai lake district", "chinese bank mansion, beijing city hai lake district", "chinese bank, beijing city sunny district", "chinese bank, tianjin city wuqing district", as shown in fig. 9.

The POIs displayed in the POI list 930 may include a first POI (e.g., "chinese bank subway station, beijing city hai lake district," "chinese bank public transit station, beijing city hai lake district," "chinese bank mansion, beijing city hai lake district," "chinese bank, beijing city sunny district") in a local area (e.g., beijing) and a second POI (e.g., "chinese bank, tianjin city wuqing district") outside the local area. The first POI and the second POI may be determined based on a first number of POIs in the local area and a second number of POIs outside the local area, as described elsewhere in this application (e.g., fig. 7, 8, and description thereof). In some embodiments, a first number of POIs in a local area is determined by comparing a query term (e.g., "chinese bank") to local area POIs stored in a storage device (e.g., storage device 130) in the online service system 100 or an external storage device. A second number of POIs outside the local area may be determined based on the query term, the cross-regional list associated with the local area, and the first number. The merged POI may be determined by combining the first number of POIs and the second number of POIs. The merged POIs may be ranked according to query terms using the LTR model. Finally, at least a portion of the merged POIs (e.g., first POI, second POI) may be displayed in the POI list 930 according to the ranking results.

FIG. 10 is a schematic diagram of an exemplary process for retrieving one or more POIs based on query terms in accordance with some embodiments of the present application. In some embodiments, process 1000 may be combined with the process of displaying one or more POIs on a user terminal device as illustrated by process 700 in FIG. 7. As shown in fig. 10, at 1010, the processing engine 112 may obtain a query term from a user terminal device. The query term initiated in the local area may be a location name, a location abbreviation, a location symbol, a synonym of a location, etc. related to an online service (e.g., a taxi service). The location may be a starting location, a boarding location, a destination, etc. At 1020, the processing engine 112 may determine a first number of POIs in the local area based on the query terms. In some embodiments, the processing engine 112 may compare the query terms to POIs in a local area stored in a storage device (e.g., storage device 130) of the online service system 100 or an external storage device to determine a first number of POIs in the local area. In 1030, the processing engine 112 can identify a cross-region intent associated with the query term. In some embodiments, the processing engine 112 may identify the cross-region intent of the user by determining whether the first number of POIs is less than a preset threshold. If the first number of POIs is less than a preset threshold, it indicates that the user has a cross-regional intent. In some embodiments, processing engine 112 may determine a cross-regional list associated with the local region based on at least two cross-regional orders by the user over a historical period of time. The cross-zone list associated with the local zone may include at least one zone outside the local zone. In 1040, the processing engine 112 may determine a second number of POIs outside the local area by determining POIs in each of at least one area outside the local area based on the query term. In 1050, the processing engine 112 may merge the first number of POIs and the second number of POIs and use the LTR model to rank the merged POIs according to the query terms. Finally, at 1060, 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 user's terminal device according to the ranking results.

The application embodiment may bring beneficial effects including but not limited to: (1) the cross-region retrieval problem solving effect is obvious; (2) compared with the national index mode, the machines and the memory used by the scheme have no obvious increase; (3) the sequencing of the recalled POI is realized through a model, no artificial rule is used, and the sequencing model can continuously learn and optimize by self; (4) the cross-region identification is based on a list form, and manual intervention is quick and convenient. It is to be noted that different embodiments may produce different advantages, and in different embodiments, any one or combination of the above advantages may be produced, or any other advantages may be obtained.

It should be noted that the foregoing description is provided for illustrative purposes only, and is not intended to limit the scope of the present application. Various modifications and changes may occur to those skilled in the art in light of the description herein. However, such modifications and changes do not depart from the scope of the present application.

Having thus described the basic concepts, it will be apparent to those of ordinary skill in the art having read this application that the foregoing disclosure is to be construed as illustrative only and is not limiting of the application. Various modifications, improvements and adaptations to the present application may occur to those skilled in the art, although not explicitly described herein. Such modifications, improvements and adaptations are proposed in the present application and thus fall within the spirit and scope of the exemplary embodiments of the present application.

Also, this application uses specific language to describe embodiments of the application. For example, "one embodiment," "an embodiment," and/or "some embodiments" means a certain feature, structure, or characteristic described in connection with at least one embodiment of the application. 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 places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, some features, structures, or characteristics may be combined as suitable in one or more embodiments of the application.

Moreover, those of ordinary skill in the art will understand that aspects of the present application may be illustrated and described in terms of several patentable species or contexts, including any new and useful combination of processes, machines, articles, or materials, or any new and useful modification thereof. Accordingly, various aspects of the present application may be embodied entirely in hardware, entirely in software (including firmware, resident software, micro-code, etc.) or in a combination of hardware and software that may be referred to as a "module," unit, "" component, "" device "or" system. Furthermore, aspects of the present application may be represented as a computer product, including computer readable program code, embodied in one or more computer readable media.

A computer readable signal medium may comprise a propagated data signal with computer program code embodied therein, for example, on a baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including electro-magnetic, optical, etc., or any suitable combination. A computer readable signal medium may be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code on a computer readable signal medium may be propagated over any suitable medium, including radio, electrical cable, fiber optic cable, RF, or the like, or any combination of the preceding.

Computer program code required for the operation of aspects of the present application 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 similar conventional programming languages, such as the "C" programming language, Visual Basic, Fortran2003, 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 case, the remote calculator may be connected to the user calculator through any form of network, for example, a Local Area Network (LAN) or a Wide Area Network (WAN), or connected to an external calculator (for example, through the internet), or in a cloud computing environment, or used as a service such as software as a service (SaaS).

Additionally, the order in which elements and sequences of the processes described herein are processed, the use of alphanumeric characters, or the use of other designations, is not intended to limit the order of the processes and methods described herein, unless explicitly claimed. While various presently contemplated embodiments of the invention have been discussed in the foregoing disclosure by way of example, 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 all modifications and equivalent arrangements that are within the spirit and scope of the embodiments of the disclosure. For example, although the system components described above may be implemented by being installed in a hardware device, they may also be implemented by a software-only solution, such as installing the described system on an existing server or mobile device.

Similarly, it should be noted that in the preceding description of embodiments of the application, various features are sometimes grouped together in a single embodiment, figure, or description thereof for the purpose of streamlining the disclosure and aiding in the understanding of one or more of the embodiments. This method of disclosure, however, is not intended to require more features than are expressly recited in the claims. Indeed, the embodiments may be characterized as having less than all of the features of a single embodiment disclosed above.

Claims

1. A method for retrieving a point of interest, comprising:

communicating with user terminal equipment through a network to obtain a query word initiated in a local area;

determining a first number of points of interest in the local area based on the query term;

determining a second number of points of interest outside the local area based on the query term, a cross-area list associated with the local area, and the first number;

merging the first number of points of interest and the second number of points of interest;

sorting the combined interest points according to the query words; and

and displaying at least one part of the combined interest points on the user terminal equipment according to the sorting result.

2. The method of claim 1, wherein determining a second number of points of interest outside the local region based on the query term, a cross-region list associated with the local region, and the first number comprises:

determining whether the first number of points of interest is less than a threshold; and

in response to the determination that the first number of points of interest is less than the threshold,

determining a second number of points of interest outside the local area based on the query terms and a cross-area list associated with the local area.

3. The method of claim 2, wherein the cross-zone list associated with the local zone comprises at least one zone outside the local zone.

4. The method of claim 3, wherein determining a second number of points of interest outside the local region based on the query term and a cross-region list associated with the local region comprises:

obtaining at least one region outside the local region from a cross-region list associated with the local region; and

determining a second number of points of interest outside the local area by determining points of interest in each of at least one area outside the local area based on the query terms.

5. The method of claim 3, wherein at least one region outside the local region is determined using a cross-region identification method, the cross-region identification method comprising:

acquiring at least two cross-region orders of the user in a historical time period;

determining a number of orders from the local area to each of a plurality of areas based on the at least two cross-area orders;

determining a cross-region probability for each of the plurality of regions; and

determining at least one region outside the local region based on the cross-region probability for each of the plurality of regions.

6. The method of claim 5, wherein determining at least one region outside the local region based on the cross-region probability for each of the plurality of regions comprises:

determining whether a cross-region probability of each of the plurality of regions is greater than a preset probability; and

in response to the cross-region probability for the determined region being greater than the preset probability,

determining the region as one of at least one region outside the local region.

7. The method of claim 1, wherein ranking the merged points of interest according to the query term comprises:

acquiring a learning sequencing model; and

and using the learning sequencing model to sequence the combined interest points according to the query words.

8. The method of claim 7, wherein a learning ranking model is trained based on at least one of a distance between the user and a point of interest, a heat of the point of interest, a historical click rate of the point of interest, or a text relevance.

9. Method according to any of claims 1-8, characterized in that the local area is determined based on location information of the user terminal equipment.

10. The method of claim 9, wherein the location information comprises at least one of: global positioning system information, base station information, wireless fidelity network protocol address information.

11. An interest point retrieval system is characterized by comprising an acquisition module, a processing module and a communication module; the processing module further comprises a first interest point determining unit, a second interest point determining unit, a merging unit and a sorting unit;

the acquisition module is used for communicating with terminal equipment of a user through a network to acquire a query word initiated in a local area;

the first interest point determining unit is used for determining a first number of interest points in the local area based on the query term;

the second interest point determining unit is used for determining a second number of interest points outside the local area based on the query word, the cross-area list associated with the local area and the first number;

the merging unit is configured to merge the first number of interest points and the second number of interest points;

the sorting unit is used for sorting the combined interest points according to the query words; and

the communication module is used for displaying at least a part of the combined interest points on the user terminal equipment according to the sorting result.

12. The system of claim 11, wherein the second point of interest determination unit is further configured to:

13. The system of claim 12, wherein the cross-zone list associated with the local zone comprises at least one zone outside the local zone.

14. The system of claim 13, wherein the second point of interest determination unit is further configured to:

15. The system of claim 13, wherein the second point of interest determination unit is further configured to:

16. The system of claim 15, wherein the second point of interest determination unit is further configured to:

determining the region as one of at least one region outside the local region.

17. The system of claim 11, wherein the ordering unit is further configured to:

acquiring a learning sequencing model; and

18. The system of claim 17, wherein a learning ranking model is trained based on at least one of a distance between the user and a point of interest, a heat of the point of interest, a historical click rate of the point of interest, or a text relevance.

19. A system according to any of claims 11-18, characterized in that the local area is determined on the basis of location information of the user terminal equipment.

20. The system of claim 19, wherein the location information comprises at least one of: global positioning system information, base station information, wireless fidelity network protocol address information.

21. A point-of-interest retrieval apparatus comprising at least one storage medium and at least one processor;

the at least one storage medium is configured to store computer instructions;

the at least one processor is configured to execute the computer instructions to implement the point of interest retrieval method of any of claims 1-10.

22. A computer readable storage medium storing computer instructions which, when executed by a processor, implement a point of interest retrieval method as claimed in any one of claims 1-10.