Information recommendation, information presentation method, and electronic device

Abstract

This application discloses an information recommendation and information prompting method and electronic device. The information recommendation method includes: identifying service locations associated with a user and related to travel services; obtaining information on service items and / or service facilities related to the service locations; predicting potential risk types in the service locations based on the service item and / or service facility information; determining insurance products whose coverage can cover the risk types; and providing recommendation information of the insurance products to the user. Through this application embodiment, more accurate and personalized insurance product recommendations based on specific service locations can be achieved.

Description

Technical Field

[0001] This application relates to the field of information processing technology, and in particular to methods and electronic devices for information recommendation and information prompting. Background Technology

[0002] In travel-related industries, product information service systems primarily offer users services such as flight and train ticket bookings, hotel reservations, and attraction ticket bookings. In addition to these basic services, they often also provide related insurance product sales services. However, many users may lack understanding of insurance products. They may not know which insurance products are suitable for them, or even be aware of the existence of many insurance products, or lack the awareness to purchase insurance. Consequently, they may only realize the importance of insurance after encountering unexpected events during their travels that result in personal injury or other harm, by which time it may be too late.

[0003] Therefore, product information service systems typically employ a mechanism that combines user booking behavior with insurance product recommendations. For example, during a user's flight booking process, "flight accident insurance" or "flight delay insurance" can be recommended (if the flight is delayed due to unforeseen circumstances such as natural disasters, severe weather, or mechanical failure, the insurance company will provide compensation). During hotel booking, "hotel no-reason cancellation insurance" can be recommended, and so on. This allows users to be more aware of these insurance products during the booking process and to purchase them when deemed necessary, thus better protecting their travel and increasing insurance product sales.

[0004] However, existing recommendation mechanisms are usually limited to a small number of insurance products and are generally coarse-grained recommendations based on industry classifications such as air tickets and hotels. The accuracy of the recommendations is relatively low, resulting in a waste of recommendation resources. Summary of the Invention

[0005] This application provides information recommendation and notification methods and electronic devices that enable more accurate and personalized insurance product recommendations based on specific service locations.

[0006] This application provides the following solution:

[0007] An information recommendation method, comprising:

[0008] Identify the service locations associated with the user that are related to travel services;

[0009] Obtain information on the service items and / or service facilities related to the service location;

[0010] Based on the information on the service items and / or service facilities, the potential risk types in the service locations are predicted;

[0011] The system identifies insurance products whose coverage can encompass the aforementioned risk type and provides recommendations for these insurance products to the user.

[0012] The determination of the service locations associated with the user and related to travel services includes:

[0013] Determine whether the user is currently in a service location related to travel services. If so, identify that service location as the service location associated with the user.

[0014] The step of determining whether the user is currently located in a service location related to travel services includes:

[0015] Based on the user's current geographical location, determine whether the user is currently in a service location related to travel services.

[0016] The step of determining whether the user is currently located in a service location related to travel services includes:

[0017] Based on the service location and time information associated with the user's service booking records, determine whether the user is currently located at a service location related to travel services.

[0018] The determination of the service locations associated with the user and related to travel services includes:

[0019] The service location related to travel services where the user is currently making a booking is identified as the service location associated with the user.

[0020] The determination of the service locations associated with the user and related to travel services includes:

[0021] Obtain information on incomplete travel itineraries associated with the user;

[0022] The service locations related to travel services mentioned in the travel itinerary information are identified as the service locations associated with the user.

[0023] This also includes:

[0024] If the travel itinerary information includes multiple different destinations, the potential risk types during the user's transfer between different destinations are predicted, and the user is provided with recommendations for insurance products that can cover the risk types.

[0025] The step of predicting the potential risk types in the service venue based on the service items and / or service facility information includes:

[0026] The algorithm predicts the probability of corresponding types of risks occurring in the service location using a pre-set algorithm. The input information of the algorithm includes information on the service items and / or service facilities, as well as auxiliary information, which includes one or more of the following: weather conditions, geographical conditions, emergencies, and personalized information of the user in the area where the service location is located.

[0027] The step of predicting the potential risk types in the service venue based on the service items and / or service facility information includes:

[0028] Based on the services and / or facilities available at the service location, predict the probability of personal injury risks that a user may incur while participating in the services and / or using the facilities.

[0029] The step of predicting the potential risk types in the service venue based on the service items and / or service facility information includes:

[0030] Based on whether the service location provides services and / or facilities for storing personal belongings, the probability of loss of personal belongings in the service location is predicted.

[0031] An information prompting method, comprising:

[0032] Identify the service locations associated with the user that are related to travel services;

[0033] Obtain information on the service items and / or service facilities related to the service location;

[0034] Based on the information on the service items and / or service facilities, the potential risk types in the service locations are predicted;

[0035] Based on the type of risk, risk warning information is provided to the user.

[0036] An information recommendation device, comprising:

[0037] The service location determination unit is used to determine the service locations associated with the user and related to travel services.

[0038] A service location information acquisition unit is used to acquire information on service items and / or service facilities related to the service location.

[0039] The risk prediction unit is used to predict the potential risk types in the service venue based on the service items and / or service facility information.

[0040] The insurance product recommendation unit is used to determine insurance products whose coverage can cover the risk type and to provide recommendation information of the insurance products to the user.

[0041] An information prompting device includes:

[0042] The service location determination unit is used to determine the service locations associated with the user and related to travel services.

[0043] A service location information acquisition unit is used to acquire information on service items and / or service facilities related to the service location.

[0044] The risk prediction unit is used to predict the potential risk types in the service venue based on the service items and / or service facility information.

[0045] The notification unit is used to provide risk warning information to the user based on the risk type.

[0046] A computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of any of the preceding methods.

[0047] An electronic device, comprising:

[0048] One or more processors; and

[0049] A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of any of the preceding methods.

[0050] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0051] Through the embodiments of this application, based on the service items and / or service facilities information associated with a user's travel-related service locations, the potential risk types of the user in those service locations can be predicted, and insurance products whose coverage can guarantee the risk types can be identified. Information on these insurance products can then be recommended to the user. In this way, because the recommendation of relevant insurance products is based on the specific service items and / or service facilities in the service location, the recommendation can be refined to the granularity of the user's associated service location, rather than making general recommendations at the industry level. This allows for more accurate and personalized recommendations. Furthermore, since the conditions of different service locations may vary, the types of insurance products suitable for recommendation may also differ, thus giving more insurance products the opportunity to be recommended.

[0052] Of course, any product implementing this application does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0053] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0054] Figure 1 This is a schematic diagram of the system architecture provided in the embodiments of this application;

[0055] Figure 2 This is a flowchart of the first method provided in the embodiments of this application;

[0056] Figure 3 This is a flowchart illustrating a multi-terminal interaction process under one implementation method provided in this application embodiment;

[0057] Figure 4 This is a flowchart of the second method provided in the embodiments of this application;

[0058] Figure 5 This is a schematic diagram of the first device provided in the embodiments of this application;

[0059] Figure 6 This is a schematic diagram of the second device provided in the embodiments of this application;

[0060] Figure 7 This is a schematic diagram of the electronic device provided in the embodiments of this application. Detailed Implementation

[0061] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0062] First, it should be noted that in the process of implementing the embodiments of this application, the inventors discovered that users may encounter unexpected situations during their travels, in addition to accidents caused by transportation, while staying at specific hotels or visiting attractions. For example, some attractions may offer dangerous rides or facilities, and users may suffer injuries during these activities. Some hotels may not provide luggage storage services, and users' personal belongings may be lost, and so on. Furthermore, some insurance products exist that can cover the above risks; that is, corresponding insurance products can provide safety protection for users in the event of the aforementioned situations. However, different hotels, attractions, etc., may offer different services or facilities, and it is not appropriate to recommend insurance products to users in a general way.

[0063] Therefore, in this embodiment, for a specific user, the associated service locations related to travel services can be identified (e.g., the user's current hotel, attraction, etc., or hotels, attractions, etc. involved in the user's upcoming itinerary). Then, by querying previously saved information (the services and facilities offered by multiple specific hotels, attractions, and other travel-related service locations can be saved in advance) or by initiating a real-time online query, the service items and / or facilities offered by the user's associated service locations can be determined. Subsequently, based on these service items and / or facilities, the types of risks the user may encounter at these service locations can be predicted. For example, assuming a hotel offers private beach facilities, the user may face risks such as drowning during their stay at the hotel. If a certain type of risk is predicted to have a high probability, insurance products that cover that type of risk can be identified (e.g., information on the coverage of various insurance products offered by different insurance companies can be collected in advance and saved in a structured data format for easy querying). In this way, relevant insurance product information can be recommended to the user. This approach allows for more precise and personalized recommendations, down to the specific service locations associated with the user. Furthermore, since different service locations may have varying conditions, the types of insurance products suitable for recommendation may also differ, thus increasing the chances of more insurance products being recommended.

[0064] From a system architecture perspective, see Figure 1This application embodiment may involve a client and a server of a commodity information service system. The client primarily runs on a user terminal device and is used to interact with the user. In this embodiment, to determine whether a user is located in a service location, the client, with the user's permission, can upload the user's geographical location information to the server. This allows the server to provide the user with insurance product recommendations using LBS (Location Based Services) (other methods can also be used, as detailed later). Additionally, the client can be used to deliver recommendations, for example, through a message center within the client, providing users with recommendations for specific insurance products. The server can be deployed in the cloud, primarily for storing specific data, predicting potential risks to the user, preserving information about insurance products, matching risk types with insurance products, and generating specific recommendations, etc. After generating the recommendations, the server can deliver them to the user in various ways, such as by sending push messages from the aforementioned client, or by sending short messages, etc.

[0065] The specific implementation schemes provided in the embodiments of this application will be described in detail below.

[0066] Example 1

[0067] First, from the perspective of the aforementioned server, Embodiment 1 of this application provides an information recommendation method, see [link to embodiment]. Figure 2 The method may specifically include:

[0068] S201: Identify the service locations associated with the user and related to travel services;

[0069] Specifically, the service locations related to travel services can include hotels, tourist attractions, airports, etc. The specific service location associated with a user can refer to a particular hotel, tourist attraction, airport, etc., associated with that user. In other words, this embodiment does not recommend related insurance products for a general category of service locations, but rather provides more granular and personalized insurance product recommendations for a specific hotel, tourist attraction, airport, etc.

[0070] Specifically, there are several ways to determine the service location associated with a user. For example, one method is to determine whether the user is currently in a service location related to travel services. If so, that service location can be identified as the service location associated with the user. In other words, if the user is currently in a hotel or tourist attraction, then that hotel or tourist attraction can be considered associated with the user.

[0071] Specifically, there are several ways to determine whether a user is currently located in a service location related to travel services. For example, one method is to determine this based on the user's current geographical location. That is, with prior authorization from the user, the client can upload the user's geographical location information, including latitude and longitude. The server can then determine whether the user is located in a specific service location based on this information. Specifically, the server can pre-store the geographical location information associated with multiple service locations in a database. This allows it to query the database to find service locations matching the user's current location. Alternatively, another method is to use the query portal of an electronic map system to find service locations matching the user's current location, and so on.

[0072] In this scenario where a user's geographic location information is used to determine the associated service location, relevant recommendations can still be provided to the user even if they have not made any reservations for services at that location through the current system. For example, if a user purchases a ticket to a tourist attraction through another channel and is visiting the attraction, the system in this embodiment determines that the user is located at that attraction and predicts that they may be subject to some kind of risk. As long as the user is a user of the system in this embodiment, relevant recommendations or prompts can be provided to the user through the system in this embodiment.

[0073] Besides determining a user's current service location based on their current location, other methods can also be used. For example, the location and time information associated with the user's service booking records can be used to determine whether the user is currently located at a service location related to travel services. Specifically, since this application embodiment can provide related insurance product recommendation services in a specific product information service system, users can also book air tickets, hotels, and attraction tickets through this system or related systems. Bookings may be associated with specific dates or times, and these times can be used to estimate whether the user will be at a certain service location at a certain time. For example, if a user books a hotel and selects check-in and check-out times, it can be determined that the user may be at the hotel during the time between check-in and check-out times. Or, if a user books attraction tickets and selects a usage date, it can be determined that the user will be at the attraction on that date, and so on.

[0074] In addition to determining whether a user is located at a service location, other factors can also be considered to identify the service location associated with the user. For example, the service location where the user is currently making a booking can be identified as the service location associated with the user. Specifically, if the user is currently booking a hotel or attraction tickets, that hotel or attraction can be identified as the service location associated with the user.

[0075] Alternatively, information on incomplete travel itineraries associated with the user can be obtained through various means (e.g., based on the user's service booking status in the current product information service system, or by querying related systems). This travel itinerary information may include the specific travel date, selected mode of transportation, departure and arrival airports or stations, and the hotel to be checked into. Thus, if there are incomplete travel itineraries (e.g., not yet started, or in progress), the service locations related to travel services mentioned in the travel itinerary information can be identified as the service locations associated with the user. In other words, even if the user has not yet checked into a hotel, arrived at an airport, or entered a tourist attraction, these locations are service locations the user will visit at some point in the future according to their planned itinerary; therefore, they can also be identified as service locations associated with the user. Specific travel itinerary information may include multiple different service locations; in this case, all of these service locations can be identified as service locations associated with the user. Of course, if the specific travel itinerary is in progress (for example, a five-day trip has reached its second day, etc.), then the relevant service locations in the remaining part of the trip can be identified as associated service locations.

[0076] S202: Obtain information on service items and / or service facilities related to the service location;

[0077] Once the service locations associated with a user are identified, information about the services and / or facilities associated with those locations can be obtained. That is, it can be determined whether a specific service location offers or does not offer certain services and / or facilities. For example, for hotels, it can be determined whether they offer valuables storage services, private beaches, swimming pools, etc.; for tourist attractions, it can be determined whether they offer extreme sports entertainment projects or facilities, and so on.

[0078] In practice, information on service items and / or facilities at various service locations can be collected in advance and stored in a database on the server side. Then, once a user's associated service location is identified, the database can be queried to determine the specific service items and / or facilities associated with that location. Alternatively, the information can be obtained by querying the service interfaces of relevant systems, and so on.

[0079] S203: Based on the information on the service items and / or service facilities, predict the potential risk types in the service location;

[0080] Once the service items and / or service facilities associated with a specific service location are identified, the potential types of risks within that service location can be predicted. Specifically, various service items and / or service facilities can be collected in advance, and based on prior experience or statistical information, the types of risks that may arise can be determined and stored in a relevant database. Thus, after identifying the service items and / or service facilities associated with a specific service location, the types of risks that a user may encounter at that service location can be predicted by querying this database.

[0081] Alternatively, besides directly querying the database, specific prediction processes can be implemented through relevant algorithms. When using algorithms for prediction, more information can be incorporated to predict the probability of potential risks in the service location. For example, in addition to information such as the specific services and facilities offered at the service location, this information can also include the current season, weather conditions, geographical conditions, unforeseen events (e.g., robberies), and personalized user information (including whether the user is traveling with elderly people or children). In this way, a comprehensive judgment can be made through specific algorithms to output the probability of the corresponding type of risk.

[0082] For example, specifically, based on the services and / or facilities offered by the service venue, the probability of personal injury risks that may arise to users while participating in the services and / or using the facilities can be predicted. Alternatively, the probability of risks to personal belongings can be predicted based on whether the service venue provides services and / or facilities for storing personal items, and so on.

[0083] It should be noted that if the service location is determined based on the user's incomplete travel itinerary information, multiple different destinations can be obtained from the itinerary information. For example, during the specific trip, the user may need to travel from one city to another, etc. Therefore, the potential types of risks during the user's transfer between different destinations can also be predicted. Specifically, if the user's itinerary information includes transportation methods between different destinations, predictions can be made directly based on the transportation methods, as well as the terrain, weather conditions, etc. If the itinerary information does not include booking transportation between the aforementioned different destinations, the user's possible transportation methods can be predicted based on the distance between the two locations, and then combined with the aforementioned terrain, weather conditions, etc., for a comprehensive prediction and judgment.

[0084] S204: Determine an insurance product whose coverage can cover the risk type, and provide the user with information about the insurance product.

[0085] After identifying the potential risk types in the service location, specific insurance products covering those risk types can be determined and recommended to the user. Specifically, as mentioned earlier, information on specific insurance products offered by multiple insurance service providers can be collected in advance, including details of their coverage, and stored in a structured data format. Thus, after determining the types of risks a user may face, this structured data can be used to identify specific insurance products that cover those risks, which can then be recommended to the user.

[0086] In practice, there may be multiple insurance products that can cover the currently predicted risk types. For example, different insurance providers may offer insurance products with similar coverage, resulting in several different products that can cover the predicted risk types. In this case, information such as the user's preferences when purchasing insurance products, their spending power, and their demographic group can be considered to select insurance products that may be more interesting or suitable for the user, and then these products can be recommended to them.

[0087] There are several ways to provide recommendation information to users. For example, one approach is to send a push notification to the user via a client, allowing the user to open the client to view the detailed recommendation information after receiving the notification. Alternatively, recommendation information can be sent to users via SMS or other similar methods.

[0088] To better understand the solutions provided in the embodiments of this application, the following describes the various terminals involved in the implementation of the embodiments of this application and their interaction processes, taking a specific implementation method that can be selected in a specific application as an example.

[0089] For details, see Figure 3 The specific interaction process may include:

[0090] 1. First, the client can upload the user's location information to the server;

[0091] 2. After receiving the user's location information, the server can determine whether the user is located in a certain service location by querying the database, etc.

[0092] 3. The database returns matching service location information;

[0093] 4. The server sends another query to the database to determine the service items and / or service facilities information related to the service location;

[0094] 5. The database returns information on the service items and / or service facilities related to the service location;

[0095] 6. The server uses service items and / or service facility information as parameters to call relevant algorithms to predict potential risks in the service location;

[0096] 7. The algorithm returns risk prediction results, including information such as the types of potential risks;

[0097] 8. The server queries the database again to determine which insurance products can cover the corresponding risks;

[0098] 9. The database returns matching insurance products;

[0099] 10. Return information on the matched insurance products to the client so that they can be recommended to the user.

[0100] It should be noted that the above Figure 3The server-side components and algorithms described herein can correspond to different applications, and both can be deployed on one or more servers (the servers can be cloud servers, local servers, dedicated servers, physical servers, etc.). The server-side can call specific algorithms. Of course, in practice, the specific algorithm logic can also be implemented directly in the server-side code; this is not a limitation here. Furthermore, in Figure 3 For ease of description, the same database is used in this example. However, in practice, multiple databases can be used to store information such as service location, the correspondence between service locations and service items and / or service settings, and the correspondence between insurance products and covered risk types. Furthermore, the above... Figure 3 The example shown is only one embodiment of the present application. In actual implementation, other embodiments are also possible. Figure 3 The interactive process shown should not be regarded as a limitation on the scope of protection of the embodiments of this application.

[0101] In summary, through the embodiments of this application, potential risk types in service locations associated with a user's travel services can be predicted based on relevant service items and / or service facility information. Furthermore, insurance products whose coverage can encompass these risk types can be identified, and information on these insurance products can be recommended to the user. Because the recommendation of relevant insurance products is based on the specific service items and / or service facilities in a particular service location, the recommendation can be refined to the granularity of the user's associated service location, rather than making general recommendations at the industry level. This allows for more accurate and personalized recommendations. Additionally, since different service locations may have different conditions, the types of insurance products suitable for recommendation may also differ, thus increasing the opportunities for more insurance products to be recommended.

[0102] Example 2

[0103] In the aforementioned Embodiment 1, after predicting potential risks such as losses to the user based on the travel-related service locations associated with the user, relevant insurance products can be recommended. Alternatively, after predicting potential risks such as losses to the user, risk warning information can be provided without associating specific insurance products. Or, the risk warning information can include an option to obtain relevant insurance product recommendations, and only when the user selects a recommendation will relevant insurance product recommendations be provided, and so on. Therefore, in Embodiment 2 of this application, an information prompting method is also provided, see [link to embodiment]. Figure 4 The method may specifically include:

[0104] S401: Identify the service locations associated with the user and related to travel services;

[0105] S402: Obtain information on service items and / or service facilities related to the service location;

[0106] S403: Based on the service items and / or service facility information, predict the potential risk types in the service location;

[0107] S404: Provide risk warning information to the user based on the risk type.

[0108] Specific notification messages can be pushed to users via the client or sent via SMS, etc.

[0109] For the parts of this embodiment that are not described in detail, please refer to the description in embodiment one and other parts of this specification, which will not be repeated here.

[0110] It should be noted that the embodiments of this application may involve the use of user data. In practical applications, user-specific personal data may be used in the scheme described herein within the scope permitted by applicable laws and regulations, provided that it complies with the applicable laws and regulations of the country (e.g., with the user's explicit consent, with the user being properly notified, etc.).

[0111] Corresponding to Embodiment 1, this application also provides an information recommendation device, see [link to embodiment 1]. Figure 5 The device may specifically include:

[0112] Service location determination unit 501 is used to determine the service locations associated with the user and related to travel services;

[0113] Service venue information acquisition unit 502 is used to acquire service items and / or service facilities information related to the service venue;

[0114] The risk prediction unit 503 is used to predict the potential risk types in the service venue based on the service items and / or service facility information;

[0115] The insurance product recommendation unit 504 is used to determine insurance products whose coverage can cover the risk type and to provide recommendation information to the user.

[0116] Specifically, the service location determination unit can be used for:

[0117] Determine whether the user is currently in a service location related to travel services. If so, identify that service location as the service location associated with the user.

[0118] Specifically, based on the user's current geographical location, it can be determined whether the user is currently in a service location related to travel services.

[0119] Alternatively, based on the service location and time information associated with the user's service booking records, determine whether the user is currently located at a service location related to the travel service.

[0120] In another embodiment, the service location determination unit can specifically be used for:

[0121] The service location related to travel services where the user is currently making a booking is identified as the service location associated with the user.

[0122] Alternatively, in another embodiment, the service location determination unit may be specifically used for:

[0123] Obtain information on incomplete travel itineraries associated with the user;

[0124] The service locations related to travel services mentioned in the travel itinerary information are identified as the service locations associated with the user.

[0125] In addition, under the above circumstances, the risk prediction unit can also be used for:

[0126] If the travel itinerary information includes multiple different destinations, the potential risk types during the user's transfer between different destinations are predicted, and the user is provided with recommendations for insurance products that can cover the risk types.

[0127] In specific implementation, the risk prediction unit can be used for:

[0128] The algorithm predicts the probability of corresponding types of risks occurring in the service location using a pre-set algorithm. The input information of the algorithm includes information on the service items and / or service facilities, as well as auxiliary information, which includes one or more of the following: weather conditions, geographical conditions, emergencies, and personalized information of the user in the area where the service location is located.

[0129] Specifically, the risk prediction unit can be used for:

[0130] Based on the services and / or facilities available at the service location, predict the probability of personal injury risks that a user may incur while participating in the services and / or using the facilities.

[0131] Alternatively, the risk prediction unit can be specifically used for:

[0132] Based on whether the service location provides services and / or facilities for storing personal belongings, the probability of loss of personal belongings at the service location is predicted.

[0133] Corresponding to Embodiment 2, this application also provides an information prompting device, see [link to Embodiment 2]. Figure 6 The device may include:

[0134] Service location determination unit 601 is used to determine the service locations associated with the user and related to travel services;

[0135] Service venue information acquisition unit 602 is used to acquire information on service items and / or service facilities related to the service venue;

[0136] The risk prediction unit 603 is used to predict the potential risk types in the service location based on the service items and / or service facility information;

[0137] The prompting unit 604 is used to provide risk prompt information to the user according to the risk type.

[0138] In addition, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described in any of the foregoing method embodiments.

[0139] And an electronic device, comprising:

[0140] One or more processors; and

[0141] A memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method described in any of the foregoing method embodiments.

[0142] in, Figure 7 An exemplary architecture of an electronic device is shown, which may include a processor 710, a video display adapter 711, a disk drive 712, an input / output interface 713, a network interface 714, and a memory 720. The processor 710, video display adapter 711, disk drive 712, input / output interface 713, network interface 714, and memory 720 can communicate with each other via a communication bus 730.

[0143] The processor 710 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to achieve the technical solution provided in this application.

[0144] The memory 720 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 720 can store the operating system 721 for controlling the operation of the electronic device 700, and the basic input / output system (BIOS) for controlling the low-level operations of the electronic device 700. Additionally, it can store a web browser 723, a data storage management system 724, and an information recommendation processing system 725, etc. The aforementioned information recommendation processing system 725 can be the application program that specifically implements the aforementioned steps in this embodiment. In summary, when the technical solution provided in this application is implemented through software or firmware, the relevant program code is stored in the memory 720 and is called and executed by the processor 710.

[0145] Input / output interface 713 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

[0146] Network interface 714 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0147] Bus 730 includes a pathway for transmitting information between various components of the device, such as processor 710, video display adapter 711, disk drive 712, input / output interface 713, network interface 714, and memory 720.

[0148] It should be noted that although the above-described device only shows the processor 710, video display adapter 711, disk drive 712, input / output interface 713, network interface 714, memory 720, bus 730, etc., in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the solution of this application, and does not necessarily include all the components shown in the figures.

[0149] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0150] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for system or system embodiments, since they are basically similar to method embodiments, the description is relatively simple, and relevant parts can be referred to the descriptions in the method embodiments. The systems and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0151] The foregoing has provided a detailed description of the information recommendation and notification methods and electronic devices provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An information recommendation method characterized by comprising: The method is applied to a commodity information service system related to the travel industry, and the service provided by the commodity information service system includes a service place reservation service related to travel services; the method comprises: determining a service place associated with the user and related to travel services according to the service place reservation of the user in the commodity information service system related to the travel industry; obtaining service item and / or service facility information that can or cannot be provided in the service place; predicting potential risk types in the service place according to the service item and / or service facility information; the potential risk types include risks generated by the user participating in the service item that can be provided and / or using the service facility that can be provided, or risks generated by the service item and / or service facility that cannot be provided; determining an insurance product whose guarantee range can cover the risk types, and providing recommendation information to the user according to the information of the insurance product.

2. The method of claim 1, wherein determining a service place associated with the user and related to travel services according to the service place reservation of the user in the commodity information service system related to the travel industry comprises: determining whether the user is currently located in a service place related to travel services, and if so, determining the service place as the service place associated with the user.

3. The method of claim 2, wherein determining whether the user is currently located in a service place related to travel services comprises: determining whether the user is currently located in a service place related to travel services according to the geographical location information of the user.

4. The method of claim 2, wherein determining whether the user is currently located in a service place related to travel services comprises: determining whether the user is currently located in a service place related to travel services according to the service place and time information associated in the service place reservation record of the user.

5. The method of claim 1, wherein determining a service place associated with the user and related to travel services according to the service place reservation of the user in the commodity information service system related to the travel industry comprises: determining a service place related to travel services in which the user is currently performing a reservation operation as the service place associated with the user.

6. The method of claim 1, wherein determining a service place associated with the user and related to travel services according to the service place reservation of the user in the commodity information service system related to the travel industry comprises: obtaining travel itinerary information associated with the user and in an incomplete state; determining a service place related to travel services involved in the travel itinerary information as the service place associated with the user.

7. The method of claim 6, wherein, Further comprising: if the travel itinerary information includes multiple different destinations, predicting potential risk types in the transfer process of the user between different destinations, and providing the user with recommendation information about an insurance product that can cover the risk types.

8. The method of any one of claims 1 to 7, wherein the predicting the potential risk types in the service site based on the service item and / or service facility information comprises: predicting, by a pre-set algorithm, a probability of a risk of a corresponding type occurring in the service site, wherein the algorithm takes as input the service item and / or service facility information and auxiliary information including one or more of the following: weather conditions, geographical conditions, unexpected events in a region where the service site is located, and personalized information of the user.

9. The method of any one of claims 1 to 7, wherein the predicting the potential risk types in the service site based on the service item and / or service facility information comprises: predicting, based on the service item and / or service facility information available in the service site, a probability of a personal injury type of risk arising from the user’s participation in a service item available in the service site and / or use of a service facility available in the service site.

10. The method of any one of claims 1 to 7, wherein the predicting the potential risk types in the service site based on the service item and / or service facility information comprises: predicting, based on a service item and / or service facility not available in the service site, a probability of a personal item loss type of risk arising from the user’s presence in the service site due to the service item and / or service facility of the personal item storage type not available in the service site. The method is applied to a commodity information service system related to the travel industry, which provides services including service site booking services related to travel services; the method comprises: determining, based on a service booking of the user in the commodity information service system related to the travel industry, a service site associated with the user and related to travel services; obtaining service item and / or service facility information available or not available in the service site; 11. An information presentation method characterized by comprising: predicting, based on the service item and / or service facility information, potential risk types in the service site, including risks arising from the user’s participation in a service item available in the service site and / or use of a service facility available in the service site, or risks arising from a service item and / or service facility not available in the service site; providing, based on the risk types, risk prompt information to the user. The program, when executed by a processor, implements the steps of the method of any one of claims 1 to 11. comprises: one or more processors; and 12. A computer readable storage medium having stored thereon a computer program, characterized in that, a memory associated with the one or more processors, the memory storing program instructions that, when read and executed by the one or more processors, perform the steps of the method of any one of claims 1 to 11.

13. An electronic device, comprising: ​ ​ ​ ​

Images