Information recommendation method and device

Abstract

An information recommendation method includes: based on content input by a first user, detecting whether the input includes a tourist attraction and a travel time; if so, detecting the status of the tourist attraction at the travel time; and if the tourist attraction is congested at the travel time, recommending a congestion avoidance plan to the first user. This method can provide users with congestion avoidance plans for their planned travel time, thereby improving user experience. This application also provides an information recommendation device capable of implementing the above information recommendation method.

Description

Technical Field

[0001] The present application relates to the field of computers, and in particular to an information recommendation method and device. Background Art

[0002] Input method refers to the encoding method used to enter various characters into the computer.

[0003] In the prior art, an input method program responds to a key operation by a user and outputs characters corresponding to the key.

[0004] However, input method programs can only meet limited user needs and have limitations. Summary of the invention

[0005] In view of this, the present application provides an information recommendation method and device, which can provide users with travel plans that avoid congestion during their planned travel time, thereby improving user experience.

[0006] The first aspect provides an information recommendation method, comprising: based on content input by a first user, detecting whether the input content includes attractions and travel time, and if so, detecting the state of the attraction at the travel time; when the state of the attraction at the travel time is congested, recommending a congestion avoidance plan for the first user.

[0007] Optionally, before detecting whether the input content includes attractions and travel time based on the content input by the first user, the method further includes: obtaining the number of travelers at each attraction at each travel time based on the input content of multiple users; and determining the status of each attraction at each travel time based on the number of travelers at each attraction at each travel time.

[0008] Optionally, obtaining the number of travelers at each scenic spot at each travel time based on input content of multiple users includes: performing semantic analysis on the input content of each user according to a deep learning model to obtain travel information corresponding to the input content of each user, the travel information including scenic spots, travel time and number of travelers; determining the number of travelers at each scenic spot at each travel time based on the travel information corresponding to the input content of each user among the multiple user input contents.

[0009] Optionally, the congestion avoidance scheme includes at least one recommended travel time period and a recommended scenic spot corresponding to each recommended travel time period, and the recommended scenic spot is a scenic spot that is not congested during the corresponding recommended travel time period;

[0010] Optionally, the distance between the recommended scenic spot and the scenic spot in the first user input content is less than a threshold.

[0011] Optionally, the method further includes: providing the first user with a status of the scenic spot at the travel time.

[0012] Optionally, the method further includes: providing the first user with the status of the scenic spot during hotspot time.

[0013] A second aspect provides an information recommendation device, the device comprising a first detection unit, a second detection unit and a recommendation unit;

[0014] The first detection unit is used to detect whether the input content includes scenic spots and travel time based on the content input by the first user;

[0015] The second detection unit is used to detect the state of the scenic spot at the travel time if the input content includes the scenic spot and the travel time;

[0016] The recommendation unit is configured to recommend a congestion avoidance plan to the first user when the scenic spot is congested at the travel time.

[0017] Optionally, before detecting, based on the content input by the first user, whether the input content includes attractions and travel time, the device further includes:

[0018] A first determining unit, used to determine the number of travelers at each scenic spot at each travel time according to input content of multiple users;

[0019] The second determining unit is used to determine the state of each scenic spot at each travel time according to the number of travelers at each scenic spot at each travel time.

[0020] Optionally, the first determination unit is specifically used to perform semantic analysis on the input content of each user according to the deep learning model to obtain travel information corresponding to the input content of each user, the travel information including attractions, travel time and number of travelers; and determine the number of travelers at each attraction at each travel time based on the travel information corresponding to the input content of each user in the multiple user input contents.

[0021] Optionally, the congestion avoidance scheme includes at least one recommended travel time period and a recommended scenic spot corresponding to each recommended travel time period, and the recommended scenic spot is a scenic spot that is not congested during the corresponding recommended travel time period;

[0022] Optionally, the distance between the recommended scenic spot and the scenic spot in the first user input content is less than a threshold.

[0023] Optionally, the recommendation unit is further configured to provide the first user with the status of the scenic spot at the travel time.

[0024] Optionally, the recommendation unit is further configured to provide the first user with the status of the scenic spot during hotspot time.

[0025] The third aspect provides an information recommendation device, comprising a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, wherein the one or more programs include a method for executing the information recommendation method as described in any one of the first aspects.

[0026] A fourth aspect provides a non-transitory computer-readable storage medium. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device can perform the information recommendation method as described in any one of the first aspects.

[0027] It can be seen from the above technical solution that based on the content input by the first user, it is detected whether the input content includes scenic spots and travel time. If so, the state of the scenic spot at the travel time is detected; when the state of the scenic spot at the travel time is congested, a congestion avoidance plan is recommended to the first user. The above method can provide users with travel plans that avoid congestion at the user's planned travel time, thereby improving user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic diagram of the information recommendation system provided for this application;

[0029] Figure 2 A flowchart of a method for recommending information provided by this application;

[0030] Figure 3 A schematic diagram of an information recommendation device provided for this application;

[0031] Figure 4 A schematic diagram of a recommended device for providing information for this application;

[0032] Figure 5 A schematic diagram of the server provided for this application. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0034] The present application provides an information recommendation method and device, which can recommend congestion avoidance solutions for congested scenic spots to users and improve user experience. The method can be applied to a terminal with an input method, such as a mobile phone, a laptop computer, a desktop computer, a tablet computer, an e-book reader, a Moving Picture Experts Group Audio Layer IV (MP4) player, a wearable device (such as a smart watch), a smart speaker, a laptop computer, a car computer, etc. The application of the input method can be, but is not limited to: text messages, emails, communication software, notepads, Word documents or Excel documents, etc.

[0035] Based on the input method, the user can input content in different ways, such as input through a virtual keyboard, input through a handwriting area, or input through voice, input through copy and paste, input through gestures, or input through image recognition, and the input content can be one or more of text, letters, numbers, symbols, or pictures. For example, when inputting Chinese, the input content processing can be not only text, but also pinyin. In the embodiment of the present application, the input method can include not only common Chinese input methods (such as pinyin input method, Wubi input method, Zhuyin input method, etc.), but also input methods of other languages ​​(such as Japanese Hiragana input method, Korean input method, etc.).

[0036] like Figure 1 As shown, a conversation window of a communication software is displayed in a terminal screen display area. The conversation window includes a conversation record display area 101 and a character editing area 102. The conversation record display area 101 is used to display historical conversation records. The character editing area 102 is used to display characters input by a user, and the user can edit the input characters in the character editing area 102. Figure 1 Only the chat window for sending text is shown. It can be understood that the user can also enter symbols, letters, numbers, insert pictures, etc.

[0037] Take the conversation between user A and user B as an example. User A and user B chat through a communication software. User B inputs characters: Where to go for National Day? User A inputs characters: Go to the Forbidden City at 9 am on October 3rd.

[0038] The input method program can obtain the characters input by user A and user B. By performing semantic analysis on the input characters, it can be determined that the input characters include: October 3rd at 9 am, Forbidden City, thereby determining the travel time to be October 3rd at 9 am, and the attraction to be the Forbidden City.

[0039] According to the above method, the travel time and scenic spots input by all users can be obtained. The number of visitors to each scenic spot at each travel time can be determined based on the travel time and scenic spots input by all or part of the users. Then, the status of the scenic spot can be determined based on the number of visitors and the upper limit of the number of people that the scenic spot can accommodate.

[0040] For example, the Forbidden City is congested during the period from 9:00 to 11:00 on October 3. If user A travels according to the original plan, user A will spend a lot of time queuing or sightseeing. In order to avoid congested attractions, you can obtain non-congested attractions during the period from 9:00 to 11:00 on October 3, such as the Old Summer Palace. Generate a congestion avoidance plan based on 9 am on October 3 and the Old Summer Palace. For example, visit the Old Summer Palace from 9:00 to 11:00 on October 3; visit the Forbidden City from 11:00 to 16:00 on October 3. It should be noted that visiting the Forbidden City from 11:00 to 16:00 on October 3 is an optional option, that is, this application can generate one or more travel plans based on the user's travel time or travel duration to meet the user's travel needs.

[0041] In addition, user A inputs "go to the Summer Palace at 3 pm on October 3" in the character editing area 102. The input method program can also detect that the input characters include: October 3 at 3 pm, Summer Palace. The input method program can determine that the travel time is 3 pm on October 3, and the scenic spot is the Summer Palace. For example, the Summer Palace is congested during the period of 15:00-18:00 on October 3. The status of the Summer Palace during the period of 15:00-18:00 on October 3 is displayed, for example, the Summer Palace is congested during the period of 15:00-18:00 on October 3. In addition, the application can also push suggestion information to the user, for example, it is not recommended to visit the Summer Palace during the period of 15:00-18:00 on October 3.

[0042] From the above, it can be seen that the present application can provide solutions to avoid congested attractions, or suggestions for avoiding congested attractions, thereby improving the user experience.

[0043] Before implementing the information recommendation method of the present application, the above method also includes: determining the number of travelers at each scenic spot at each travel time based on the input content of multiple users; determining the status of each scenic spot at each travel time based on the number of travelers at each scenic spot at each travel time.

[0044] The multiple users may be all users or a certain number of users set according to actual conditions. Semantic analysis is performed on the input content of each user to obtain the scenic spots and travel time included in the input content; then the scenic spots and travel time included in the input content of all or part of the users are counted. For example, a travel time and a scenic spot are taken as a record. For a certain scenic spot at a certain travel time, the number of travelers at the above scenic spot at the above travel time can be determined based on the number of records, and then the state of the above scenic spot at the above travel time can be determined based on the number of travelers and the upper limit of the number of people that the scenic spot can accommodate.

[0045] For example, for a certain travel time, when the ratio of the number of travelers to the upper limit of the number of people that the scenic spot can accommodate is greater than or equal to a preset ratio threshold, the state of the scenic spot is determined to be congested; when the ratio of the number of travelers to the upper limit of the number of people that the scenic spot can accommodate is less than the preset ratio threshold, the state of the scenic spot is determined to be not congested. The state can also be subdivided into more types, such as: congested, suitable and scarce. It is understandable that the subdivision of the state is not limited to two or three, but can also be four or more. The scenic spot, travel time and state and the corresponding relationship of the above information can be saved in a database or a data table.

[0046] Since users usually look up attractions and travel times, or input travel plans before or during a trip, a large amount of travel information can be obtained through the input method program. The travel information can be obtained to determine the number of travelers at each attraction at each travel time, and then the status of the attraction at the travel time can be determined based on the number of travelers at each attraction at each travel time, thereby providing users with reliable travel information.

[0047] It should be noted that when the travel time and attractions input by the user are the same multiple times within a period of time, the multiple input travel time and attractions are recorded as one record according to the time of the input travel time and attractions. Specifically, for the same travel plan, the time difference between the two input travel time and attractions is compared with the preset time. If it is greater than or equal to the preset time, the two input travel time and attractions are determined to be two records. If it is less than the preset time, the two input travel time and attractions are determined to be one travel plan. In this way, repeated calculations can be avoided, thereby improving the accuracy of the number of travelers.

[0048] Optionally, determining the number of travelers at each scenic spot at each travel time based on input content of multiple users includes: performing semantic analysis on the input content of each user according to a deep learning model to obtain travel information corresponding to each user's input content, the travel information including scenic spots, travel time and number of travelers; determining the number of travelers at each scenic spot at each travel time based on the travel information corresponding to each user's input content among multiple user input contents.

[0049] Specifically, the user's input content is used as a training sample, and the travel information corresponding to the input content is used as an output result, and the training sample is trained according to a deep learning model. The deep learning model can be a convolutional neural network, a deep belief network, etc.

[0050] After obtaining the travel information corresponding to each user input content, the scenic spots, travel time and number of travelers in the multiple user input contents are counted, thereby obtaining the number of travelers at each scenic spot at each travel time. The deep learning model can accurately identify whether the input content includes travel information, so it has the advantage of high accuracy.

[0051] Next, the information recommendation method provided by the present application is described in conjunction with the accompanying drawings. Figure 2 , an embodiment of the information recommendation method provided by the present application includes:

[0052] Step 201 : Based on the content input by the first user, detect whether the input content includes attractions and travel time. If so, execute step 202 ; if not, execute step 204 .

[0053] In this embodiment, the first user may be any user who uses the input method program. The semantic analysis of the content input by the user may detect whether the input content includes the scenic spot and the travel time corresponding to the scenic spot. When it is detected that the input content includes the scenic spot and the travel time, step 202 is executed; when it is detected that the input content does not include the scenic spot and the travel time, step 204 is executed.

[0054] It should be noted that when the user input includes multiple scenic spots and multiple travel times, the deep learning model can determine the travel time corresponding to each scenic spot. The travel time can include the travel date, and can also include the travel time, travel period, a combination of the travel time and travel duration, etc. It is understandable that the travel date can include the year and month of the travel, etc.

[0055] It should be noted that the information recommendation device can obtain content based on any form of user input through the input method. For example, the content input by the user through the input method, the content copied and pasted by the user, the content input by gesture, the content recognized by the inserted image, etc. Image recognition can be optical character recognition (OCR), which converts the text of various bills, newspapers, books, manuscripts and other printed materials into image information through optical input methods such as scanning, and then uses text recognition technology to convert the image information into a usable computer input technology. For example, by scanning the attraction ticket information, or performing image recognition on the attraction ticket image, it is possible to identify the attractions included in the attraction ticket, travel time and number of travelers, etc.

[0056] Step 202: If the input content includes scenic spots and travel time, the status of the scenic spots during the travel time is detected.

[0057] From the above, it can be known that the scenic spots, travel time and status, and the corresponding relationship between the above information are stored in the database or data table.

[0058] When it is detected that the input content includes attractions and travel time, the state corresponding to the attractions and travel time is queried in the above database or data table according to the attractions and travel time. When the state corresponding to the attractions and travel time is congested, step 203 is executed; when the state corresponding to the attractions and travel time is not congested, step 204 can be executed.

[0059] Step 203: When the state of the scenic spot is congested during the travel time, recommend a congestion avoidance plan to the first user.

[0060] When the state of the scenic spot corresponding to the travel time is congested, a congestion avoidance plan including non-congested scenic spots and travel times is generated. Optionally, the congestion avoidance plan includes at least one recommended travel time period and recommended scenic spots corresponding to each recommended travel time period, and the recommended scenic spots are scenic spots that are not congested during the corresponding recommended travel time period. Specifically, the recommended travel time period in the congestion avoidance plan can be determined according to the travel time included in the user input content. For example, the starting time of the recommended travel time period in the congestion avoidance plan is the travel time included in the user input content, or the recommended travel time period in the congestion avoidance plan is the travel time included in the user input content; or, the recommended travel time in the congestion avoidance plan includes the travel time and travel duration included in the user input content. The latter recommended travel time period and the former recommended travel time period can be adjacent or separated.

[0061] Optionally, the congestion avoidance plan also includes a travel order. Specifically, a corresponding number is set for each recommended travel time and each recommended scenic spot corresponding to the recommended time period to indicate the travel order of each recommended travel time and recommended scenic spot. For example, (1) visit the Old Summer Palace from 9:00 to 11:00 on October 3; (2) visit the Forbidden City from 11:00 to 16:00 on October 3. The numbering format and quantity are not limited to the above examples.

[0062] Optionally, the distance between the recommended scenic spot and the scenic spot in the first user input content is less than a threshold. Specifically, a non-congested scenic spot near the scenic spot included in the user input content is selected as the non-congested scenic spot in the congestion avoidance solution. For example, a non-congested scenic spot in the same city (or urban area) as the congested scenic spot, or a non-congested scenic spot in a city adjacent to the city where the congested scenic spot is located.

[0063] After the traffic jam avoidance plan is generated, the traffic jam avoidance plan is recommended to the user. The traffic jam avoidance plan can be recommended by displaying it on the conversation interface of the communication tool, or by pushing it in the form of voice broadcast, or by sending it in the form of email or SMS, or by displaying it in a pop-up window.

[0064] It should be noted that the present application can also determine whether the travel time included in the user input content is a past travel time or a future travel time through semantic analysis. No congestion avoidance scheme is generated for past travel time and scenic spots, but a congestion avoidance scheme is generated for future travel time and scenic spots, and the congestion avoidance scheme is displayed to the user.

[0065] Step 204: If the input content does not include scenic spots and travel time, no traffic avoidance plan is generated.

[0066] If the input content does not include attractions and travel time, it means that the input content does not involve tourism information and no traffic avoidance plan may be generated.

[0067] This embodiment can obtain information about congested attractions and non-congested attractions, and provide users with travel plans that avoid congestion during their planned travel time, thereby improving user experience.

[0068] In another possible implementation manner, the method further includes: providing the first user with a status of the scenic spot during the travel time.

[0069] When the state of the scenic spot during the above travel time is congested, the state of the scenic spot during the travel time can be obtained as congested, and the state of the scenic spot during the above travel time (i.e., the congested state) is pushed to the user, so that the user can timely know the congested state of the scenic spot during the travel time, and the user can adjust the travel plan according to the congested state of the scenic spot. When the scenic spot is not congested during the above travel time, the information that the scenic spot is not congested can also be provided to the user, helping the user to timely understand the state of the scenic spot during the travel time. It can be seen that the information provided by this application can enhance the user experience.

[0070] In another possible implementation, the method further includes: providing the first user with the state of the scenic spot during hot time. Hot time refers to holidays, such as Saturday, Sunday, National Day holiday, Spring Festival holiday, etc.

[0071] In this application, according to the correspondence between the scenic spot, travel time and status stored in the database or data table, the status of the scenic spot at the hot time can be obtained, and then the status of the scenic spot at the hot time can be pushed to the user. Alternatively, when the user enters the scenic spot and does not enter the travel time, the status of the scenic spot at the hot time is obtained, and the status of the scenic spot at the hot time is pushed to the user. In addition, other information about the scenic spot at the hot time, such as weather, etc., can also be pushed to the user.

[0072] In addition to pushing the status of attractions during travel time or hot spot time to users, one or more of the following information can also be pushed to users: the weather at the above-mentioned congested attractions during the above-mentioned travel time, the flow of people at the above-mentioned congested attractions during the above-mentioned travel time, the flow of people at the non-congested attractions during the above-mentioned travel time, the status of non-congested attractions at the above-mentioned travel time, the weather at the non-congested attractions during the above-mentioned travel time, etc.

[0073] The above is an introduction to the information recommendation method provided by the present application. The following is an introduction to the information recommendation device provided by the present application.

[0074] Figure 3 A schematic diagram of the structure of the information recommendation device provided in this application. The information recommendation device includes: a first detection unit 301, a second detection unit 302 and a recommendation unit 303;

[0075] A first detection unit 301 is used to detect whether the input content includes attractions and travel time based on the content input by the first user;

[0076] A second detection unit 302, configured to detect the state of the scenic spot at the travel time if the input content includes the scenic spot and the travel time;

[0077] The recommendation unit 303 is configured to recommend a congestion avoidance plan to the first user when the scenic spot is congested during the travel time.

[0078] Optionally, before detecting whether the input content includes scenic spots and travel time based on the content input by the first user, the information recommendation device further includes:

[0079] A first determining unit, used to determine the number of travelers at each scenic spot at each travel time according to input content of multiple users;

[0080] The second determining unit is used to determine the state of each scenic spot at each travel time according to the number of travelers at each scenic spot at each travel time.

[0081] Optionally, the first determination unit is specifically used to perform semantic analysis on the input content of each user according to the deep learning model to obtain travel information corresponding to each user input content, the travel information including attractions, travel time and number of travelers; based on the travel information corresponding to each user input content among multiple user input contents, determine the number of travelers at each attraction at each travel time.

[0082] Optionally, the congestion avoidance scheme includes at least one recommended travel time period and a recommended scenic spot corresponding to each recommended travel time period, and the recommended scenic spot is a scenic spot that is not congested during the corresponding recommended travel time period;

[0083] Optionally, the distance between the recommended scenic spot and the scenic spot in the first user input content is less than a threshold.

[0084] Optionally, the recommendation unit is further configured to provide the first user with the status of the scenic spot during the travel time.

[0085] Optionally, the recommendation unit is further configured to provide the first user with the status of the scenic spot during hot time.

[0086] Figure 4 The information recommendation device 400 may be a mobile phone, a computer, a digital broadcast terminal, a message transceiver, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, a car computer, etc.

[0087] The information recommendation device 400 may include a processing component 402 , a memory 404 , a power component 406 , a multimedia component 408 , an audio component 410 , an input / output (I / O) interface 412 , a sensor component 414 , and a communication component 416 .

[0088] The processing component 402 generally controls the overall operation of the device 400, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 402 may include one or more processors 420 to execute instructions to complete all or part of the steps of the above-mentioned method. In addition, the processing component 402 may include one or more modules to facilitate the interaction between the processing component 402 and other components. For example, the processing component 402 may include a multimedia module to facilitate the interaction between the multimedia component 406 and the processing component 402.

[0089] The memory 404 is configured to store various types of data to support operations on the device 400. Examples of such data include instructions for any application or method operating on the device 400, contact data, phone book data, messages, pictures, videos, etc. The memory 404 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0090] The power supply component 406 provides power to the various components of the device 400. The power supply component 406 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power to the device 400.

[0091] The multimedia component 408 includes a screen that provides an output interface between the device 400 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 408 includes a front camera and / or a rear camera. When the device 400 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0092] The audio component 410 is configured to output and / or input audio signals. For example, the audio component 410 includes a microphone (MIC), and when the device 400 is in an operating mode, such as a call mode, a recording mode, and a speech recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 404 or sent via the communication component 416. In some embodiments, the audio component 410 also includes a speaker for outputting audio signals.

[0093] I / O interface 412 provides an interface between processing component 402 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: a home button, a volume button, a start button, and a lock button.

[0094] The sensor assembly 414 includes one or more sensors for providing various aspects of status assessment for the device 400. For example, the sensor assembly 414 can detect the open / closed state of the device 400, the relative positioning of components, such as the display and keypad of the device 400, and the sensor assembly 414 can also detect the position change of the device 400 or a component in the device 400, the presence or absence of user contact with the device 400, the orientation or acceleration / deceleration of the device 400, and the temperature change of the device 400. The sensor assembly 414 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 414 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 414 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0095] The communication component 416 is configured to facilitate wired or wireless communication between the device 400 and other devices. The device 400 can access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In an exemplary embodiment, the communication component 416 receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 416 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0096] In an exemplary embodiment, the apparatus 400 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above method.

[0097] The embodiment of the present application also provides a non-transitory computer-readable storage medium including instructions, such as a memory 404 including instructions, and the instructions can be executed by the processor 420 of the device 400 to complete the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0098] A non-temporary computer-readable storage medium, when the instructions in the storage medium are executed by a processor of an electronic device, enables the electronic device to execute an information recommendation method, the method comprising: based on the content input by a first user, detecting whether the input content includes attractions and travel time, and if so, detecting the state of the attraction at the travel time; when the state of the attraction at the travel time is congested, recommending a congestion avoidance plan to the first user.

[0099] It should be noted that the computer storage medium can also be used to implement the Figure 2 The information recommendation method in various possible implementations of the illustrated embodiment.

[0100] Figure 5: is a schematic diagram of the structure of the server in the embodiment of the present application. The server 500 may have relatively large differences due to different configurations or performances, and may include one or more central processing units (CPU) 522 (for example, one or more processors) and memory 532, and one or more storage media 530 (for example, one or more mass storage devices) storing application programs 542 or data 544. Among them, the memory 532 and the storage medium 530 can be short-term storage or permanent storage. The program stored in the storage medium 530 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations on the server. Furthermore, the central processing unit 522 can be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the server 500 to achieve Figure 2 The information recommendation method in the illustrated embodiment or various possible implementations.

[0101] The server 500 may also include one or more power supplies 526, one or more wired or wireless network interfaces 550, one or more input and output interfaces 558, one or more keyboards 556, and / or one or more operating systems 541, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

[0102] A person of ordinary skill in the art can understand that all or part of the steps of implementing the above-mentioned method embodiment can be completed by hardware related to program instructions, and the above-mentioned program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps of the above-mentioned method embodiment; and the above-mentioned storage medium can be at least one of the following media: read-only memory (ROM), RAM, magnetic disk or optical disk, etc., various media that can store program codes.

[0103] It should be noted that each embodiment in this specification is described in a progressive manner, and the same and similar parts between the embodiments can refer to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device and system embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments. The device and system embodiments described above are merely schematic, in which the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. Ordinary technicians in this field can understand and implement it without paying creative work.

[0104] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any changes or substitutions that can be easily thought of by a person skilled in the art within the technical scope disclosed in the present application should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. An information recommendation method, characterized in that: The method is applied to an input method program, and the method comprises: In a conversation scenario, input contents edited by multiple users are obtained, and the number of travelers at each scenic spot at each travel time is determined according to the input contents; for the same travel plan of the same user, the time difference between two input travel times and scenic spots is compared with a preset time length, and if the time difference is greater than or equal to the preset time length, the two input travel times and scenic spots are determined to be two records, and if the time difference is less than the preset time length, the two input travel times and scenic spots are determined to be one record; According to the number of travelers at each scenic spot at each travel time, determine the status of each scenic spot at each travel time; Based on the content input by the first user, detecting whether the input content includes the scenic spot and the travel time, and if the scenic spot and the travel time are not included, not generating the congestion avoidance plan; if the scenic spot and the travel time are included, in response to the travel time being a past travel time, not generating the congestion avoidance plan, and in response to the travel time being a future travel time, detecting the state of the scenic spot at the travel time, and displaying the state of the scenic spot at the travel time; When the state of the scenic spot at the travel time is congested, recommend the congestion avoidance plan to the first user; the congestion avoidance plan includes at least one recommended travel time period and a recommended scenic spot corresponding to each recommended travel time period, the recommended scenic spot is a scenic spot included in the content, or a scenic spot not included in the content, the recommended scenic spot is a scenic spot that is not congested during the corresponding recommended travel time period, and the distance between the recommended scenic spot and the scenic spot in the content input by the first user is less than a threshold; When the state of the scenic spot at the travel time is not congested, the congestion avoidance plan is not generated.

2. The method according to claim 1, characterized in that Determining the number of travelers at each scenic spot at each travel time according to the input content of multiple users includes: Perform semantic analysis on the input content of each user according to the deep learning model to obtain travel information corresponding to the input content of each user, wherein the travel information includes scenic spots, travel time and number of travelers; The number of travelers at each scenic spot at each travel time is determined according to the travel information corresponding to each user input content among the multiple user input contents.

3. The method according to any one of claims 1 to 2, characterized in that The method further comprises: The status of the scenic spot at the travel time is provided to the first user.

4. The method according to any one of claims 1 to 2, characterized in that The method further comprises: The first user is provided with the status of the scenic spot during the hot time.

5. An information recommendation device, characterized in that: The device is applied to an input method program, and comprises a first detection unit, a second detection unit and a recommendation unit; The first detection unit is used to detect whether the input content includes scenic spots and travel time based on the content input by the first user; The second detection unit is configured to: if the scenic spot and the travel time are not included, not generate the congestion avoidance plan; if the scenic spot and the travel time are included, in response to the travel time being a past travel time, not generate the congestion avoidance plan; in response to the travel time being a future travel time, detect the state of the scenic spot at the travel time and display the state of the scenic spot at the travel time; The recommendation unit is used to recommend the congestion avoidance plan to the first user when the state of the scenic spot at the travel time is congested; the congestion avoidance plan includes at least one recommended travel time period and a recommended scenic spot corresponding to each recommended travel time period, the recommended scenic spot is a scenic spot included in the content, or a scenic spot not included in the content, the recommended scenic spot is a scenic spot that is not congested in the corresponding recommended travel time period, and the distance between the recommended scenic spot and the scenic spot in the content input by the first user is less than a threshold; when the state of the scenic spot at the travel time is not congested, the congestion avoidance plan is not generated; A first determination unit is used to obtain input content edited by multiple users in a conversation scenario, and determine the number of travelers at each scenic spot at each travel time according to the input content; for the same travel plan of the same user, compare the time difference between two input travel times and scenic spots with a preset time length, and if the time difference is greater than or equal to the preset time length, determine that the two input travel times and scenic spots are two records; if the time difference is less than the preset time length, determine that the two input travel times and scenic spots are one record; The second determining unit is used to determine the state of each scenic spot at each travel time according to the number of travelers at each scenic spot at each travel time.

6. Device according to claim 5, characterized in that The first determination unit is specifically used to perform semantic analysis on the input content of each user according to the deep learning model to obtain travel information corresponding to each user input content, where the travel information includes scenic spots, travel time and number of travelers; based on the travel information corresponding to each user input content in multiple user input contents, determine the number of travelers at each scenic spot at each travel time.

7. The device according to any one of claims 5 to 6, characterized in that: The recommendation unit is further configured to provide the first user with the status of the scenic spot during the travel time.

8. The device according to any one of claims 5 to 6, characterized in that: The recommendation unit is further configured to provide the first user with the status of the scenic spot during the hotspot time.

9. An information recommendation device, characterized in that: It includes a memory and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by one or more processors, including for executing the information recommendation method as described in any one of claims 1 to 4.

10. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to execute the information recommendation method as described in any one of claims 1 to 4.

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