Information recommendation method and device
By dividing the user's concentration duration and adjusting the information value score based on the concentration coefficient, the problem of single information recommendation is solved, and the diversity of information recommendation and the improvement of user experience is achieved.
Patent Information
- Application Number
- CN202510661502.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-21
- Publication Date
- 2025-08-29
AI Technical Summary
In the prior art, the information recommendation method is too single, and only considers the degree of interest of the user, resulting in a lack of diversity in information recommendation.
By obtaining the focus time of the target user, dividing it into multiple time slots, and determining the value score of the information based on the focus coefficient. The focus coefficient is proportional to the information value score, and adjusting the type of information recommendation to adapt to the changes in the user's concentration.
It realizes the diversity of information recommendations at any time based on user concentration, avoids the impulse of information consumption, and improves the diversity of user experience and information recommendations.
Smart Images
Figure CN120561376A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the technical field of information recommendation, and in particular to an information recommendation method and device. Background Art
[0002] Internet content and social media platforms have greatly enriched people's social lives and access to information. They not only strengthen friendships and provide a sense of belonging, but also expand people's social circles. This is especially true for those who may experience social anxiety or introversion in real life, as the internet provides a more relaxed social environment. Furthermore, as a treasure trove of shared resources, the internet has greatly facilitated the dissemination and learning of knowledge, enabling people to quickly find learning materials and fostering the development of thinking and creativity. In the healthcare sector, the application of the internet has improved the efficiency and accessibility of medical services, such as telemedicine and health consultations, significantly improving people's quality of life.
[0003] However, while they offer benefits to the public, internet content and social media platforms also carry a range of negative impacts. Excessive use of these platforms can lead to fragmented time and excessive online time, potentially leading to addiction and addiction, impacting daily life and health. The excessive openness and real-time nature of social media can cause user fatigue, both mental and physical. Algorithmic recommendation systems can limit users to information tailored to their preferences, creating information cocoons and echo chambers, and limiting the diversity of recommended information. Summary of the Invention
[0004] The embodiments of the present application provide an information recommendation method and apparatus to at least solve the technical problem in the related art that the information recommendation method is too single due to only considering the user's interest level.
[0005] According to one aspect of an embodiment of the present application, an information recommendation method is provided, including: obtaining the concentration duration of a target user, wherein the concentration duration is used to represent the total time the user expects to spend processing information within a preset period; dividing the concentration duration into a plurality of duration slots, and determining a concentration coefficient corresponding to each duration slot; and determining a value score of the target information recommended to the target user based on the concentration coefficient, wherein the value score of the target information is proportional to the concentration coefficient.
[0006] Optionally, determining the concentration coefficient corresponding to each time slot includes: respectively obtaining the information score of the target user in each time slot, wherein the information score is used to indicate the user's interest in receiving information; obtaining the initial information score of the target user; and determining the concentration coefficient corresponding to each time slot based on the information score of each time slot and the initial information score.
[0007] Optionally, the value score of the target information recommended to the target user is determined based on the concentration coefficient, including: when the concentration coefficient is greater than a preset threshold, determining that the value score of the target information is greater than a first value score; when the concentration coefficient is less than a preset threshold, determining that the value score of the target information is less than a second value score, wherein the second value score is less than the first value score.
[0008] Optionally, obtaining the information score of the target user in each duration slot includes: obtaining a target duration corresponding to the duration slot; and determining the information score of the target user in each duration slot according to the target duration and a preset half-life formula.
[0009] Optionally, the method further includes: obtaining a user portrait of the target user; determining a score of the target user's interest level in each type of information based on the user portrait of the target user; obtaining the region where the target user is located and the role information of the target user; determining a regional role score for each type of information based on the degree of match between the region where the target user is located and the role information of the target user and each type of information; obtaining an information content quality score for each type of information and a scarcity score for each type of information through a preset model; and determining a value score for each type of information based on the interest level score for each type of information, the regional role score for each type of information, the information content quality score for each type of information, and the scarcity score for each type of information.
[0010] Optionally, the method further includes: after recommending the target information to the target user, detecting the information score of the target user at the current moment; and stopping recommending information to the target user if the information score of the target user at the current moment is less than a preset information score threshold.
[0011] Optionally, obtaining the user profile of the target user includes: collecting historical data of the target user, wherein the historical data includes: the target user's consumption time for each type of information, and the target user's interaction behavior data with each type of information; and generating the user profile of the target user based on the historical data.
[0012] According to another aspect of an embodiment of the present application, an information recommendation device is also provided, including: an acquisition module for acquiring the concentration time of a target user, wherein the concentration time is used to represent the total time the user expects to use to process information within a preset period; a determination module for dividing the concentration time into multiple time slots and determining the concentration coefficient corresponding to each time slot; a recommendation module for determining a value score of the target information recommended to the target user based on the concentration coefficient, wherein the value score of the target information is proportional to the concentration coefficient.
[0013] According to another aspect of the embodiments of the present application, a computer device is provided, including: a memory and a processor, wherein the memory is used to store program instructions; and the processor is connected to the memory and is used to execute the above-mentioned information recommendation method.
[0014] According to another aspect of the embodiments of the present application, a non-volatile storage medium is provided, which includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the above-mentioned information recommendation method by running the computer program.
[0015] According to another aspect of the embodiments of the present application, a computer program product is provided, including computer instructions, which implement the above-mentioned information recommendation method when executed by a processor.
[0016] In an embodiment of the present application, the concentration duration of the target user is obtained, wherein the concentration duration is used to represent the total time the user expects to spend processing information within a preset period; the concentration duration is divided into a plurality of duration slots, and the concentration coefficient corresponding to each duration slot is determined; the value score of the target information recommended to the target user is determined based on the concentration coefficient, and the value score of the target information is proportional to the concentration coefficient, thereby achieving the purpose of adjusting the type of recommended information at any time according to the concentration of the target user, thereby achieving the technical effect of increasing the diversity of recommendation methods, and further solving the technical problem in the related art that the information recommendation method is too single due to only considering the user's interest level. BRIEF DESCRIPTION OF THE DRAWINGS
[0017] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:
[0018] Figure 1 is a hardware structure block diagram of a computer terminal for implementing an information recommendation method according to an embodiment of the present application;
[0019] Figure 2is a flowchart of an information recommendation method according to an embodiment of the present application;
[0020] Figure 3 is a structural diagram of an information recommendation system according to an embodiment of the present application;
[0021] Figure 4 4 is a structural diagram of an information recommendation device according to an embodiment of the present application. DETAILED DESCRIPTION
[0022] In order to enable those skilled in the art to better understand the present invention, the following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments in the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of this application.
[0023] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequential order. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in a sequence other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0024] The information collected in the embodiments of the present application is information and data authorized by the user or fully authorized by all parties, and the collection, storage, use, processing, transmission, provision, disclosure and application of the relevant data comply with the relevant laws, regulations and standards of the relevant regions, take necessary confidentiality measures, do not violate public order and good morals, and provide corresponding operation entrances for users to choose to authorize or reject the automated decision results; if the user chooses to reject, the expert decision-making process will be entered.
[0025] In order to solve the problems existing in the related art, the embodiment of the present application provides an information recommendation method, which can be run on Figure 1 In the computer terminal shown, the computer terminal is explained below.
[0026] The information recommendation method embodiments provided in the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Figure 1FIG1 shows a hardware structure block diagram of a computer terminal for implementing an information recommendation method. Figure 1 As shown, the computer terminal 10 may include one or more (illustrated by 102a, 102b, ..., 102n in the figure) processors (the processor may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission module 106 for communication functions connected via a wired and / or wireless network. In addition, it may also include: a display, a keyboard, a cursor control device, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of the I / O interface), a network interface, and a BUS bus. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.
[0027] It should be noted that the one or more processors and / or other data processing circuits described above may generally be referred to herein as "data processing circuitry." The data processing circuitry may be embodied in whole or in part as software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuitry may be a single, independent processing module, or may be incorporated in whole or in part into any of the other components of the computer terminal 10. As described in the embodiments of the present application, the data processing circuitry serves as a processor control (e.g., selection of a variable resistor terminal path connected to an interface).
[0028] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the information recommendation method in the embodiment of the present application. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, realizing the above-mentioned information recommendation method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include a memory remotely located relative to the processor, and these remote memories may be connected to the computer terminal 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.
[0029] The transmission module 106 is configured to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the communications provider of the computer terminal 10. In one embodiment, the transmission module 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, the transmission module 106 may be a radio frequency (RF) module, which is configured to communicate with the Internet wirelessly.
[0030] The display may be, for example, a touch screen liquid crystal display (LCD) that enables a user to interact with a user interface of the computer terminal 10 .
[0031] It should be noted that, in some optional embodiments, the above Figure 1 The computer terminal shown may include hardware elements (including circuits), software elements (including computer code stored on a computer-readable medium), or a combination of hardware elements and software elements. Figure 1 This is merely one example of a particular embodiment and is intended to illustrate the types of components that may be present in the computer terminal described above.
[0032] In the above-mentioned operating environment, an embodiment of the present application provides an information recommendation method embodiment. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.
[0033] Figure 2 is a flow chart of an information recommendation method according to an embodiment of the present application. Figure 2 As shown, the method includes the following steps:
[0034] Step S202: Acquire the target user's concentration duration, where the concentration duration is used to represent the total time the user expects to spend processing information within a preset period;
[0035] In step 202, the concentration of each user will decrease with time. The specific concentration time can be set by the user himself, or the system can automatically generate a recommended concentration time based on the collected concentration time data and confirm it by the user himself.
[0036] Step S204: dividing the concentration duration into a plurality of duration slots, and determining a concentration coefficient corresponding to each duration slot;
[0037] In step S204, the duration slots represent the duration intervals during which different users focus on consuming information. Taking a 2-hour concentration duration as an example, the duration slots can be set to 0 minutes, 20 minutes, 30 minutes, 1 hour, 1 hour and 30 minutes, 2 hours, etc. The specific number of duration slots and the duration corresponding to each duration slot can be set according to actual conditions. The concentration coefficient is used to measure the degree of concentration when consuming information.
[0038] Step S206: Determine a value score of the target information recommended to the target user based on the concentration coefficient, wherein the value score of the target information is proportional to the concentration coefficient.
[0039] In step S206 , the value score of the information is used to indicate the user's interest in the information and the scarcity of the information.
[0040] In order to avoid the impulse of information consumption and reduce dependence on information consumption, this application creatively proposes to determine the value score of target information based on the concentration coefficient. It can be understood that the concentration coefficient decreases with time, and the value score of the target information will also decrease with time.
[0041] Through the above steps S202 to S206, the target user's concentration duration is obtained, wherein the concentration duration is used to represent the total time the user expects to spend processing information within a preset period; the concentration duration is divided into multiple duration slots, and the concentration coefficient corresponding to each duration slot is determined; the value score of the target information recommended to the target user is determined based on the concentration coefficient, and the value score of the target information is proportional to the concentration coefficient, thereby achieving the purpose of adjusting the type of recommended information at any time according to the target user's concentration, thereby achieving the technical effect of increasing the diversity of recommendation methods, and further solving the technical problem in the related art that the information recommendation method is too single due to only considering the user's interest level. The following is a detailed description.
[0042] In some embodiments of the present application, the specific steps for determining the concentration coefficient corresponding to each time slot are as follows: respectively obtain the information score of the target user in each time slot, wherein the information score is used to indicate the user's interest in receiving information; obtain the initial information score of the target user; and determine the concentration coefficient corresponding to each time slot based on the information score of each time slot and the initial information score.
[0043] For example, if the initial information score is 100, then the user is most interested in the information and is most willing to receive it. The duration slot corresponding to the initial information score indicates the time when the user is most willing to receive the information.
[0044] In some embodiments of the present application, the specific steps for determining the value score of the target information recommended to the target user based on the concentration coefficient are as follows: when the concentration coefficient is greater than a preset threshold, determining that the value score of the target information is greater than a first value score; when the concentration coefficient is less than a preset threshold, determining that the value score of the target information is less than a second value score, wherein the second value score is less than the first value score.
[0045] In an optional manner, the concentration coefficient can be determined by the ratio of the information score corresponding to the current duration slot to the initial information score.
[0046] Taking the preset threshold of 0.5 as an example, if the concentration coefficient is greater than 0.5, the target information's value score is determined to be greater than the first value score. If the concentration coefficient is less than 0.5, the target information's value score is determined to be less than the second value score. For example, the first value score is 70 and the second value score is 30.
[0047] In some embodiments of the present application, the specific steps for obtaining the information score of the target user in each time slot are as follows: obtaining the target time slot corresponding to the time slot; determining the information score of the target user in each time slot according to the target time slot and a preset half-life formula.
[0048] The default half-life formula is as follows:
[0049]
[0050] In the formula, t represents the target duration corresponding to the duration slot, t 0.5 It represents the time required for the information score to be reduced to half of the initial information score, N(t) represents the information score corresponding to the target time, and N0 represents the initial information score.
[0051] For example: The target user has consumed information for 1 hour (the target duration corresponding to the duration slot), t 0.5 Taking 2 hours as an example, the N(t) of the target user at the current moment (the target duration corresponding to the duration slot is 1 hour) is 70.7, and the concentration coefficient is 0.707.
[0052] It should be noted that the value score of information can be determined in the following ways: obtaining the user portrait of the target user; determining the target user's interest score for each type of information based on the target user's user portrait; obtaining the region where the target user is located and the target user's role information; determining the regional role score for each type of information based on the degree of match between the target user's region and the target user's role information and each type of information; obtaining the information content quality score for each type of information and the scarcity score for each type of information through a preset model; determining the value score for each type of information based on the interest score for each type of information, the regional role score for each type of information, the information content quality score for each type of information and the scarcity score for each type of information.
[0053] For example: if the target user's role information is a teacher, then the value score of educational information that matches teachers will be increased; if the target role is located in a target area, then the value score of information that matches the target area will be increased.
[0054] In an optional manner, the value score of each type of information may be determined by weighted summing the interest score of each type of information, the regional role score of each type of information, the information content quality score of each type of information, and the scarcity score of each type of information.
[0055] It should be noted that the user portrait includes multi-dimensional data such as the user's basic information, interests and hobbies, active time periods, etc., which is used to accurately understand user needs.
[0056] For example, if Xiao Li logs into the platform at 9 pm, the system recommends information. Based on Xiao Li's user profile (highly interested in technology and environmental protection), location (located in City A), role (social activist), and current focus level, the system selects the following categories of information and assigns them a value rating:
[0057] In-depth articles on technological innovation: interest level 80 points, regional role score 90 points, content quality score 95 points, scarcity score 85 points.
[0058] News reports on environmental protection activities in City A scored 95 points for interest, 95 points for regional role, 80 points for content quality, and 90 points for scarcity. Combining the value scores of these information types yields a final value score of 87 for the technological innovation article and 90 for the environmental protection news. In this case, considering Xiao Li's interests and current context, the environmental protection news will be recommended first, as it has a higher overall value score and better meets Xiao Li's immediate needs and preferences.
[0059] In this way, the platform can provide users with more personalized, valuable and moderately scarce information recommendations, thereby improving user experience, promoting healthy information consumption habits, and avoiding the troubles of information overload and repeated information.
[0060] After recommending the target information to the target user, detecting the information score of the target user at the current moment; if the information score of the target user at the current moment is less than a preset information score threshold, stopping recommending information to the target user.
[0061] Specifically, when the user's information consumption time reaches a set value, such as the concentration time, N(t) is close to 0, and the information that the user is interested in will be intercepted to reduce the impulse of information consumption.
[0062] In some embodiments of the present application, the specific steps for obtaining the user portrait of the target user are as follows: collecting historical data of the target user, wherein the historical data includes: the target user's consumption time for each type of information, and the target user's interaction behavior data with each type of information; generating a user portrait of the target user based on the historical data.
[0063] The present application also provides an information recommendation system. Figure 3 As shown, it includes: user registration and configuration module, intelligent agent module, information value scoring module, user customizable intelligent agent module, intelligent agent market module, and user behavior collection module;
[0064] The User Registration and Configuration module is used to create an intelligent agent control module for users when they register on the platform and set the user's concentration time.
[0065] The intelligent agent module is used to set the initial information score and use the half-life formula to calculate the decay of the information score. When the user's information consumption time reaches the set value, the information score is close to 0, intercepting the information that the user is interested in to reduce the impulse of information consumption.
[0066] The information value scoring module is used to evaluate content and scarcity to obtain an information value score.
[0067] It should be noted that if the popularity is high but the scarcity of the same type of content is low, the score will also be low; otherwise, the score will be high.
[0068] User-customizable intelligent agents are used to provide user-customizable intelligent agents.
[0069] The intelligent agent market module is used to customize personalized information management needs.
[0070] The user behavior collection module is used to collect user consumption time, comments, likes, reposts and other platform interaction behaviors, calculate the user's personal preferences as input for various intelligent agents.
[0071] In actual application scenarios, taking the target user as an example, during the target user registration process, the system asks the target user whether he is willing to set his concentration time; the target user sets his concentration time to 2 hours. The system defaults the initial information score (N0) of all information to 100 points; when the target user browses the platform for 30 minutes, assuming the half-life t 0.5 For example, if the target user's current concentration coefficient is 0.707 after browsing for one hour, the concentration coefficient drops to 0.5, significantly reducing their information receptivity. At this point, we select suboptimal but still valuable information for recommendation based on the new rating, adapting to the target user's current state of concentration. When the concentration coefficient drops to 0.25, we begin blocking most information, displaying only the highest-rated content, and sending a break reminder to the target user, encouraging them to temporarily leave the platform for a rest or other activity.
[0072] In other embodiments, the system can receive information input from target users and, based on specific factors such as their interests and geographic location, re-evaluate the value of the information and calculate the attention coefficient to provide more customized information recommendation services. The system can also adjust its evaluation model based on target user feedback (such as likes, comments, and reposts), learning that target users prefer information with high scarcity, providing a basis for future recommendations.
[0073] Figure 4 An information recommendation device according to an embodiment of the present application includes:
[0074] An acquisition module 40 is configured to acquire the target user's concentration duration, wherein the concentration duration is used to represent the total time the user expects to spend processing information within a preset period;
[0075] A determination module 42 is configured to divide the concentration duration into a plurality of duration slots and determine a concentration coefficient corresponding to each duration slot;
[0076] The recommendation module 44 is configured to determine a value score of the target information recommended to the target user based on the concentration coefficient, wherein the value score of the target information is proportional to the concentration coefficient.
[0077] Through the above-mentioned information recommendation device, the concentration duration of the target user is obtained, wherein the concentration duration is used to represent the total time the user expects to use to process information within a preset period; the concentration duration is divided into multiple duration slots, and the concentration coefficient corresponding to each duration slot is determined; the value score of the target information recommended to the target user is determined based on the concentration coefficient, and the value score of the target information is proportional to the concentration coefficient, thereby achieving the purpose of adjusting the type of recommended information at any time according to the concentration of the target user, thereby achieving the technical effect of improving the diversity of recommendation methods, and further solving the technical problem in the related art that the information recommendation method is too single due to only considering the user's interest level.
[0078] The determination module 42 includes: a determination submodule for determining the concentration coefficient corresponding to each time slot, including: respectively obtaining the information score of the target user in each time slot, wherein the information score is used to indicate the user's interest in receiving information; obtaining the initial information score of the target user; and determining the concentration coefficient corresponding to each time slot based on the information score of each time slot and the initial information score.
[0079] The determination submodule includes: a scoring unit and an acquisition unit, wherein the scoring unit is used to determine the value score of the target information recommended to the target user based on the concentration coefficient, including: when the concentration coefficient is greater than a preset threshold, determining that the value score of the target information is greater than a first value score; when the concentration coefficient is less than a preset threshold, determining that the value score of the target information is less than a second value score, wherein the second value score is less than the first value score.
[0080] An acquisition unit is used to obtain the information score of the target user in each time slot, including: obtaining the target time slot corresponding to the target time slot; and determining the information score of the target user in each time slot according to the target time slot and a preset half-life formula.
[0081] The above-mentioned information recommendation device also includes a value scoring submodule, which is used to obtain a user portrait of the target user; determine the target user's interest level score for each type of information based on the target user's user portrait; obtain the target user's region and the target user's role information; determine the regional role score for each type of information based on the degree of match between the target user's region and the target user's role information and each type of information; obtain the information content quality score of each type of information and the scarcity score of each type of information through a preset model; and determine the value score of each type of information based on the interest level score of each type of information, the regional role score of each type of information, the information content quality score of each type of information, and the scarcity score of each type of information.
[0082] The above-mentioned information recommendation device also includes an interception submodule, which is used to detect the information score of the target user at the current moment after recommending the target information to the target user; if the information score of the target user at the current moment is less than a preset information score threshold, stop recommending information to the target user.
[0083] The value scoring submodule includes: a portrait unit for obtaining a user portrait of the target user, including: collecting historical data of the target user, wherein the historical data includes: the target user's consumption time for each type of information, and the target user's interaction behavior data with each type of information; generating a user portrait of the target user based on the historical data.
[0084] It should be noted that Figure 4 The information recommendation device shown is used to perform Figure 2 The information recommendation method shown in the figure, therefore the relevant explanations in the above information recommendation method are also applicable to the information recommendation device, and will not be repeated here.
[0085] An embodiment of the present application further provides a computer device, comprising: a memory and a processor, wherein the memory is used to store program instructions; and the processor is connected to the memory and is used to execute the above-mentioned information recommendation method.
[0086] The information recommendation method executed by the above-mentioned computer device obtains the concentration time of the target user, wherein the concentration time is used to represent the total time the user expects to spend on processing information within a preset period; divides the concentration time into multiple time slots, and determines the concentration coefficient corresponding to each time slot; determines the value score of the target information recommended to the target user based on the concentration coefficient, and the value score of the target information is proportional to the concentration coefficient, thereby achieving the purpose of adjusting the type of recommended information at any time according to the concentration of the target user, thereby achieving the technical effect of increasing the diversity of recommendation methods, and further solving the technical problem in the related art that the information recommendation method is too single due to only considering the user's interest level.
[0087] An embodiment of the present application further provides a non-volatile storage medium, which includes a stored computer program, wherein the device where the non-volatile storage medium is located executes the above-mentioned information recommendation method by running the computer program.
[0088] The information recommendation method stored in the above-mentioned non-volatile storage medium obtains the concentration time of the target user, wherein the concentration time is used to represent the total time the user expects to use to process information within a preset period; the concentration time is divided into multiple time slots, and the concentration coefficient corresponding to each time slot is determined; the value score of the target information recommended to the target user is determined according to the concentration coefficient, and the value score of the target information is proportional to the concentration coefficient, thereby achieving the purpose of adjusting the type of recommended information at any time according to the concentration of the target user, thereby realizing the technical effect of improving the diversity of recommendation methods, and further solving the technical problem in the related art that the information recommendation method is too single due to only considering the user's interest level.
[0089] An embodiment of the present application further provides a computer program product, comprising computer instructions, which, when executed by a processor, implement the steps of the information recommendation method in the present application.
[0090] The serial numbers of the above embodiments of the present application are for description only and do not represent the advantages or disadvantages of the embodiments.
[0091] In the above embodiments of the present application, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.
[0092] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. Among them, the device embodiments described above are only exemplary. For example, the division of the units can be a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of units or modules, which can be electrical or other forms.
[0093] The units described as separate components may or may not be physically separate, and 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 units. Some or all of the units may be selected according to actual needs to achieve the purpose of the present embodiment.
[0094] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.
[0095] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for enabling a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.
[0096] The above is only a preferred embodiment of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present application. These improvements and modifications should also be regarded as the scope of protection of the present application.
Claims
1. An information recommendation method, characterized in that: include: Obtaining the target user's concentration duration, where the concentration duration is used to represent the total time the user expects to spend processing information within a preset period; Dividing the concentration duration into a plurality of duration slots, and determining a concentration coefficient corresponding to each duration slot; A value score of the target information recommended to the target user is determined according to the concentration coefficient, and the value score of the target information is proportional to the concentration coefficient.
2. The method according to claim 1, characterized in that Determine the concentration coefficient corresponding to each time slot, including: Obtaining the information score of the target user at each time slot, wherein the information score is used to indicate the user's interest in receiving the information; Obtaining an initial information score of the target user; The concentration coefficient corresponding to each time slot is determined according to the information score of each time slot and the initial information score.
3. The method according to claim 2, characterized in that Determining a value score of the target information recommended to the target user according to the concentration coefficient includes: When the concentration coefficient is greater than a preset threshold, determining that the value score of the target information is greater than the first value score; When the concentration coefficient is less than a preset threshold, it is determined that the value score of the target information is less than a second value score, wherein the second value score is less than the first value score.
4. The method according to claim 2, characterized in that Obtaining the information score of the target user at each time slot includes: Obtain the target duration corresponding to the duration slot; The information score of the target user in each time slot is determined according to the target time and a preset half-life formula.
5. The method according to claim 1, wherein The method further comprises: Obtaining a user profile of the target user; Determining a score of the target user's interest in each type of information based on the target user's user profile; Obtaining the region where the target user is located and the role information of the target user; Determining a regional role score for each type of information based on the region where the target user is located and the degree of matching between the role information of the target user and each type of information; Obtaining, by means of a preset model, an information content quality score and a scarcity score for each type of information; The value score of each type of information is determined according to the interest score of each type of information, the regional role score of each type of information, the information content quality score of each type of information, and the scarcity score of each type of information.
6. The method according to claim 1, characterized in that The method further comprises: After recommending the target information to the target user, detecting the information score of the target user at the current moment; When the information score of the target user at the current moment is less than a preset information score threshold, stop recommending information to the target user.
7. The method according to claim 5, characterized in that Obtaining a user profile of the target user, including: Collecting historical data of the target user, wherein the historical data includes: the target user's consumption time for each type of information, and the target user's interaction behavior data with each type of information; Generate a user profile of the target user based on the historical data.
8. An information recommendation device, characterized in that: include: An acquisition module, configured to acquire the target user's concentration duration, wherein the concentration duration is used to represent the total time the user expects to spend processing information within a preset period; a determination module, configured to divide the concentration duration into a plurality of duration slots and determine a concentration coefficient corresponding to each duration slot; A recommendation module is used to determine a value score of the target information recommended to the target user based on the concentration coefficient, where the value score of the target information is proportional to the concentration coefficient.
9. A computer device, characterized in that: include: A memory and a processor, wherein the memory is used to store program instructions; The processor is connected to the memory and is configured to execute the information recommendation method according to any one of claims 1 to 7.
10. A computer program product comprising computer instructions, characterized in that When the computer instructions are executed by a processor, the information recommendation method according to any one of claims 1 to 7 is implemented.