An information recommendation method, device, electronic device and storage medium

Abstract

The present invention discloses an information recommendation method, apparatus, electronic device and storage medium. Among them, the method includes: collecting operation information of a target user on a target display interface within a preset time period, and determining a target public feature attribute that matches the target user from a plurality of to-be-matched public feature attributes according to the operation information; determining at least one to-be-matched user group according to the target public feature attribute; determining a target category subgroup corresponding to the target user in at least one to-be-matched user group according to the user basic information of the target user; determining to-be-displayed information corresponding to the target user according to the historical operation information of each to-be-matched user in the target category subgroup, and displaying the to-be-displayed information on the target display interface. The problem of inaccurate recommended information when making information recommendations based on a single user is solved, and the effect of recommending more matching information to a single user belonging to the same user group is achieved.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of intelligent information recommendation, and in particular, to an information recommendation method, apparatus, electronic device, and storage medium. Background Art

[0002] With the rapid development of the Internet, the Internet is becoming more and more closely related to people's lives. For example, online shopping, online job applications, or browsing online information, etc.

[0003] According to different needs of users in the network, different information can be recommended to users. Currently, when recommending information to users, it is usually by collecting the behavior information of users, and then analyzing the collected behavior information to determine the recommended information that matches the users. However, the needs of users may not be fixed, and the analysis of the user behavior information may be affected by the short-term abnormal behavior of users, which may lead to the problem that the recommended information for users is inaccurate.

[0004] In order to meet the needs of users and recommend more suitable information to users, the information recommendation method can be improved. Summary of the Invention

[0005] The present invention provides an information recommendation method, apparatus, electronic device, and storage medium to achieve the effect of recommending more matching information to a single user belonging to the same user group.

[0006] In a first aspect, an embodiment of the present invention provides an information recommendation method, including:

[0007] Collecting operation information of a target user on a target display interface within a preset duration, and determining a target public characteristic attribute that matches the target user from a plurality of to-be-matched public characteristic attributes according to the operation information;

[0008] Determining at least one to-be-matched user group according to the target public characteristic attribute; wherein, the to-be-matched user group includes at least one to-be-matched user, and the public characteristic attributes corresponding to the to-be-matched user group are the same;

[0009] Determining a target category subgroup corresponding to the target user in the at least one to-be-matched user group according to the user basic information of the target user; wherein, the to-be-matched user group includes a plurality of to-be-matched category subgroups divided according to preset category information;

[0010] Determining to-be-displayed information corresponding to the target user according to the historical operation information of each to-be-matched user in the target category subgroup, and displaying the to-be-displayed information on the target display interface.

[0011] Second aspect, an embodiment of the present invention further provides an information recommendation device, including:

[0012] A target public feature attribute determination module, configured to collect operation information of a target user on a target display interface within a preset duration, and determine a target public feature attribute that matches the target user from a plurality of to-be-matched public feature attributes according to the operation information;

[0013] A to-be-matched user group determination module, configured to determine at least one to-be-matched user group according to the target public feature attribute; wherein, at least one to-be-matched user is included in the to-be-matched user group, and the public feature attributes corresponding to the to-be-matched user group are the same;

[0014] A target category subgroup determination module, configured to determine a target category subgroup corresponding to the target user in the at least one to-be-matched user group according to user basic information of the target user; wherein, a plurality of subgroups divided according to preset category information are included in the to-be-matched user group;

[0015] A to-be-displayed information display module, configured to determine to-be-displayed information corresponding to the target user according to historical operation information of each to-be-matched user in the target category subgroup, and display the to-be-displayed information on the target display interface.

[0016] Third aspect, an embodiment of the present invention further provides an electronic device, the electronic device includes:

[0017] One or more processors;

[0018] A storage device, configured to store one or more programs,

[0019] When the one or more programs are executed by the one or more processors, the one or more processors implement the information recommendation method according to any one of the embodiments of the present invention.

[0020] Fourth aspect, an embodiment of the present invention further provides a storage medium including computer-executable instructions, and the computer-executable instructions are used to execute the information recommendation method according to any one of the embodiments of the present invention when executed by a computer processor.

[0021] The technical solution of this embodiment is to collect the operation information of the target user on the target display interface within a preset time period, and determine the target public characteristic attribute that matches the target user from multiple to-be-matched public characteristic attributes. By analyzing the collected operation information of the target user and the corresponding relationship between each operation information and the to-be-matched public characteristics, the target public attribute corresponding to the target user can be determined. According to the target public characteristic attribute, at least one to-be-matched user group is determined. That is to say, the to-be-matched user group corresponding to the target user can be one or more. Through the target public characteristic attribute corresponding to the target user and the target attribute label corresponding to the target public attribute, at least one to-be-matched user group corresponding to the target user can be determined. According to the user basic information of the target user, the target category subgroup corresponding to the target user in the at least one to-be-matched user group is determined. Based on the user basic information, the user group to which the target user belongs can be further determined, and then a more suitable user group for the target user can be determined. Based on the information of interest of each to-be-matched user in the same target category subgroup, the information to be recommended is determined. According to the historical operation information of each to-be-matched user in the target category subgroup, the information to be displayed corresponding to the target user is determined, and the information to be displayed is displayed on the target display interface. According to the historical operation information of each to-be-matched user, the satisfaction of each to-be-matched user with the information to be recommended is determined, and then the information to be displayed is determined according to the satisfaction, so as to display it to the target user on the target display interface. This solves the problem of inaccurate recommended information when making information recommendations based on a single user, realizes the analysis of user groups with the same attribute information, and achieves the effect of making information recommendations to users belonging to the same user group according to the analysis results. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the introduced drawings are only the drawings of a part of the embodiments to be described by the present invention, rather than all the drawings. For those of ordinary skill in the art, other drawings can be obtained according to these drawings without creative efforts.

[0023] Figure 1 It is a schematic flowchart of an information recommendation method provided in Embodiment 1 of the present invention;

[0024] Figure 2 It is a schematic flowchart of an information recommendation method provided in Embodiment 2 of the present invention;

[0025] Figure 3 It is a schematic flowchart of an information recommendation method provided in Embodiment 2 of the present invention;

[0026] Figure 4 Schematic structural diagram of an information recommendation device provided in Embodiment 3 of the present invention;

[0027] Figure 5 Schematic structural diagram of an electronic device provided in Embodiment 4 of the present invention. Detailed implementation manners

[0028] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present invention, rather than limiting the present invention. In addition, it should be noted that, for the sake of description, only parts related to the present invention are shown in the accompanying drawings rather than all the structures.

[0029] Before elaborating on the technical solution in detail, the application scenario of the technical solution will be introduced first to better understand the technical solution. To meet the need for providing more matching information to users when they browse information using web pages or application software, information can be recommended to users based on information such as user attributes and interest preferences. Based on this, the technical solution can be applied to scenarios such as users shopping on the network, searching for information, and looking for job information through the network.

[0030] Embodiment 1

[0031] Figure 1 Schematic flowchart of an information recommendation method provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of recommending information to a single user within the same user group based on the characteristics of the user group. The method can be executed by an information recommendation device, and the device can be implemented in the form of software and / or hardware. The hardware can be an electronic device, such as a mobile terminal or a PC, etc.

[0032] As Figure 1 shown, the method includes:

[0033] S110. Collect the operation information of the target user on the target display interface within a preset time period, and determine the target public characteristic attribute that matches the target user from multiple to-be-matched public characteristic attributes according to the operation information.

[0034] Among them, when making information recommendations for users, it is necessary to first collect the operation information of the users, and then analyze the collected operation information to recommend more matching information to the users. When collecting the operation information of users, the duration for collecting operation information can be preset. For example, the preset duration can be set to one week or one month, etc. The target user can be understood as the user for whom information is recommended based on this technical solution. The target display interface can be understood as the display interface of the terminal device or mobile terminal device used by the target user. Various information recommended to the user can be included in the target display interface. In addition, the target user can also perform operation information such as collection, access, viewing, deletion, download, placing an order, or recommending to other users by triggering relevant buttons in the target display interface. In order to determine the information that matches the target user, it is possible to collect and analyze the operation information of multiple users in the target display interface, and group users with common characteristic attributes as a user group. Among them, the common characteristic attributes can be understood as the common attribute characteristics possessed by multiple users in the user group. For example, the common characteristic attributes can be consumption attribute characteristics, interests and hobbies, and job preferences, etc. The specific common characteristic attributes can be set according to actual needs and are not specifically limited here. It can be understood that one or more to-be-matched common characteristic attributes can be obtained according to different common characteristic attributes. That is to say, when determining the target common characteristic attributes corresponding to the target user, according to the attribute characteristics of the target user, the target common characteristic attributes corresponding to the target user can be determined from multiple to-be-matched common characteristic attributes.

[0035] Specifically, within the preset duration, collect the operation information of the target user in the target display interface, such as operation information such as accessing, collecting, viewing, deleting, downloading, placing an order, and recommending to other users for the information displayed in the target display interface. According to the collected operation information of the target user, the common characteristic attributes corresponding to the target user can be determined, and then based on the common characteristic attributes corresponding to the target user, the target common characteristic attributes that match the target user can be determined from multiple to-be-matched common characteristic attributes.

[0036] Optionally, collecting the operation information of the target user in the target display interface within the preset duration and determining the target common characteristic attributes that match the target user from multiple to-be-matched common characteristic attributes according to the operation information include: establishing a correspondence relationship between each to-be-matched common characteristic attribute and the operation information; within the preset duration, when detecting the operation information in the target display interface, determining the to-be-matched common characteristic attribute corresponding to the operation information based on the correspondence relationship; and determining the target common characteristic attributes that match the target user according to the trigger frequency information of the to-be-matched common characteristic attributes.

[0037] Among them, the trigger frequency information can be understood as the number of times when the target user operates on the displayed information in the target display interface and triggers the corresponding public feature attributes to be matched based on each operation information.

[0038] Specifically, before determining the corresponding public feature attributes to be matched according to the operation information, it is first necessary to establish the correspondence between each operation information and the public feature attributes to be matched, so that when the operation information in the target display interface is detected, the public feature attributes to be matched corresponding to the operation information can be determined from multiple public feature information to be matched based on the pre-established correspondence. Then, according to the trigger frequency information of each public feature attribute to be matched, the target public feature information matching the target user is determined. That is to say, not all the public feature attributes to be matched triggered by the operation information can be used as the target public feature attributes corresponding to the target user, but when the number of times the public feature attribute to be matched is triggered meets a certain trigger frequency, the public feature attribute to be matched can be used as the target public feature attribute.

[0039] Exemplarily, when the target user is shopping in the target display interface, multiple product information can be seen in the target display interface. The target user can perform operations such as accessing, collecting, placing an order, or recommending to other users on each product. Taking the consumption attribute when the target user places an order for a product as an example, if the price range of the products ordered by the target user within the preset duration is mostly between 300 and 500, and the price ranges of very few products are higher or lower than the price range of 300 - 500, such as a consumption of more than 5000 yuan, then at this time, it can be considered that the target public attribute corresponding to the target user can be understood as the consumption price range between 300 and 500.

[0040] S120. Determine at least one user group to be matched according to the target public feature attribute; wherein, the user group to be matched includes at least one user to be matched, and the public feature attributes corresponding to the user group to be matched are the same.

[0041] Among them, regarding users with the same public feature attributes as a user group to be matched, it can be understood that the feature attributes in the target public feature attributes corresponding to the target user can include one or multiple, such as the consumption attribute, hobby attribute, or job requirement attribute of the target user, etc. Each feature attribute can correspond to a user group to be matched. That is to say, according to different feature attributes in the target public feature attributes corresponding to the user, at least one user group to be matched corresponding to the target public feature attribute can be determined.

[0042] Specifically, there can be multiple characteristic attributes of the target user. Among the target public characteristic attributes corresponding to the target user, there can be one characteristic attribute or multiple characteristic attributes. Each public characteristic attribute to be matched can correspond to one or more user groups to be matched. That is to say, at least one user group to be matched corresponding to the target public characteristic attribute can be determined based on the target public characteristic attribute.

[0043] Optionally, determining at least one user group to be matched according to the target public characteristic attribute includes: determining at least one user group to be matched that matches the target public characteristic attribute according to the pre-established corresponding relationship and the target attribute label corresponding to the target public characteristic attribute; wherein, the corresponding relationship includes the corresponding relationship between each public characteristic attribute to be matched and each attribute label, and the corresponding relationship between each attribute label and each user group to be matched.

[0044] Among them, the attribute label can be understood as the label information determined according to the keyword information or identification information of each public characteristic attribute to be matched, and the target attribute label can be understood as the label information corresponding to the target public characteristic attribute.

[0045] Specifically, different attribute labels can be set for each public characteristic attribute to be matched, and the corresponding relationship between each public characteristic attribute to be matched and each attribute label, and the corresponding relationship between each attribute label and each user group to be matched can be established. Based on this, at least one user group to be matched corresponding to the target public characteristic attribute can be determined according to the pre-established corresponding relationship and the target attribute label corresponding to the target public characteristic attribute.

[0046] Exemplarily, if the target attribute label corresponding to the target public characteristic attribute of the target user is college student and loves reading, then at least one user group to be matched corresponding to each attribute label can be determined according to the pre-set corresponding relationship between the target public characteristic attribute and the target attribute label. Among them, the corresponding relationship includes the corresponding relationship between each public characteristic attribute to be matched and each attribute label, and the corresponding relationship between each attribute label and each user group to be matched.

[0047] S130. Determine the target category subgroup corresponding to the target user in the at least one user group to be matched; wherein, the user group to be matched includes multiple category subgroups to be matched divided according to the preset category information.

[0048] Among them, in each user group to be matched, it can be further divided according to the user basic information characteristics of each user to be matched. For example, gender, age, occupation, education level, etc. At least one sub-group to be matched can be determined according to these user basic information characteristics. The target sub-group can be understood as the sub-group to be matched corresponding to the target user determined in at least one user group to be matched according to the user basic information characteristics of the target user.

[0049] Specifically, each user group to be matched is divided according to the preset category information based on the user basic information, and at least one sub-group to be matched is obtained. Then, after determining at least one user group to be matched that matches the target user, the target sub-group corresponding to the target user is determined according to the user basic information of the target user.

[0050] Exemplarily, when the target user browses commodity information on the target display page, it can be determined that the consumption range corresponding to the target user is between 300 and 500 according to the target public characteristic attributes corresponding to the target user. Then, the user group to be matched corresponding to the target user is the user group with a consumption range between 300 and 500. Further, according to the user basic information of the target user, such as age being 20 - 25 years old, gender being female, and identity being a professional woman, etc., based on these user basic information, category information can be preset in advance. Then, multiple sub-groups to be matched are obtained according to the preset category information. After obtaining the basic information corresponding to the target user, the target sub-group corresponding to the target user can be determined in at least one user group to be matched.

[0051] S140. Determine the information to be displayed corresponding to the target user according to the historical operation information of each user to be matched in the target sub-group, and display the information to be displayed on the target display interface.

[0052] Among them, the historical operation information can be understood as the operation information of each historical user collected based on the target display interface, and the information to be displayed can be understood as the information that will be displayed on the target display interface. It can be understood that the information to be displayed is the information that matches the target user determined based on the operation information corresponding to the target user.

[0053] Specifically, the target category subgroup corresponding to the target user may include multiple users, and the users belonging to the target category subgroup have the same target public characteristic attributes as the target user and are also consistent with the user basic information of the target user. For example, if the public characteristic attribute of the target user is loving reading, the user group to be matched corresponding to the target user is the user group who loves reading. Then, according to the preset category information, the user group to be matched is divided into different sub-groups to be matched. For example, if the preset category information is age category, occupation category, and gender category, then according to the age, occupation, and gender in the user basic information corresponding to the target user, the target category subgroup corresponding to the target user can be determined.

[0054] Optionally, determining the information to be displayed corresponding to the target user according to the historical operation information of each user to be matched in the target category subgroup, and displaying the information to be displayed on the target display interface includes: determining the information to be recommended for each user to be matched according to the historical operation information of each user to be matched; wherein, the historical operation information includes at least one of browsing information, click information, and access information; determining the information to be displayed that matches the target user according to the operation information of the target user on the display interface and the information to be recommended for each user to be matched in the corresponding target category subgroup; displaying the information to be displayed on the target display interface to display the information to be displayed to the target user.

[0055] Among them, the information to be recommended can be understood as the information to be recommended to the target user.

[0056] Specifically, after determining the target category subgroup corresponding to the target user, in order to be able to recommend more suitable information to the target user, the information that each user to be matched in the target category subgroup to which the target user belongs is interested in is recommended to the target user. That is to say, the information required by each user to be matched in the target category subgroup corresponding to the target user is relatively similar. Based on this, the information that the users to be matched in the same sub-group to be matched as the target user are interested in can be used as the information to be recommended and recommended to the target user. In order to be able to determine the information that each user to be matched in the target category subgroup is interested in, the historical operation information of each user to be matched can be used, such as browsing information, click information, access information, order placement information, and consultation information on the target interface. According to the trigger frequency of each operation information, the degree of interest of each user to be matched in the information to be recommended can be determined. Furthermore, after collecting the operation information of the target user on the target display interface, the information to be recommended that matches the target user can be recommended to the target user.

[0057] It should be noted that after determining the information to be recommended corresponding to the target user, the information to be recommended can be sorted according to the satisfaction of each information by each user to be matched. For example, taking the product information displayed when purchasing a product as an example, the product information corresponding to the product with more purchase times is preferentially recommended to the target user, and the sorted information to be recommended is displayed as the information to be displayed on the target display interface.

[0058] Optionally, before collecting the operation information of the target user on the target display interface within a preset duration and determining the target public characteristic attribute matching the target user from multiple public characteristic attributes to be matched, it further includes: presetting the attribute tags corresponding to each public characteristic attribute to be matched, and establishing the corresponding relationship between the attribute tags and each user group to be matched; pre-classifying each user group to be matched based on a preset category, and determining the sub-group to be matched corresponding to the preset category.

[0059] In practical applications, in order to determine the information matching the target user, it is necessary to match the target public characteristic attribute corresponding to the target user and the user basic information corresponding to the target user. Before matching, at least one public characteristic attribute to be matched needs to be preset, and at the same time, the attribute tags corresponding to each public characteristic attribute to be matched, and the corresponding relationship between each attribute tag and each user group to be matched are set, so as to determine at least one user group to be matched corresponding to the target user based on the target public characteristic attribute corresponding to the target user.

[0060] Furthermore, in order to determine the sub-group of the target category corresponding to the target user based on the user basic information of the target user after determining the user group to be matched to which the target user belongs, it is necessary to preset the corresponding category information according to the user basic information. Then, each user group to be matched is classified based on a preset category to obtain at least one sub-group to be matched of the category, so that after obtaining the user basic information corresponding to the target user, the sub-group of the target category corresponding to the target user can be determined according to the identification information corresponding to the preset category in the user basic information.

[0061] The technical solution of this embodiment is to collect the operation information of the target user on the target display interface within a preset time period, and determine the target public characteristic attribute that matches the target user from multiple to-be-matched public characteristic attributes. By analyzing the collected operation information of the target user and the corresponding relationship between each operation information and the to-be-matched public characteristics, the target public attribute corresponding to the target user can be determined. According to the target public characteristic attribute, at least one to-be-matched user group is determined. That is to say, the to-be-matched user group corresponding to the target user can be one or more. Through the target public characteristic attribute corresponding to the target user and the target attribute label corresponding to the target public attribute, at least one to-be-matched user group corresponding to the target user can be determined. According to the user basic information of the target user, the target category subgroup corresponding to the target user in the at least one to-be-matched user group is determined. Based on the user basic information, the user group to which the target user belongs can be further determined, and then a more suitable user group for the target user can be determined. Based on the information of interest of each to-be-matched user in the same target category subgroup, information to be recommended is determined. According to the historical operation information of each to-be-matched user in the target category subgroup, the information to be displayed corresponding to the target user is determined, and the information to be displayed is displayed on the target display interface. According to the historical operation information of each to-be-matched user, the satisfaction of each to-be-matched user with the information to be recommended is determined, and then the information to be displayed is determined according to the satisfaction, so as to display it to the target user on the target display interface. This solves the problem of inaccurate recommended information when making information recommendations based on a single user, and realizes the effect of analyzing user groups with the same attribute information and making information recommendations to users belonging to the same user group according to the analysis results.

[0062] Embodiment 2

[0063] As an optional embodiment of the above embodiment, Figure 2 It is a schematic flowchart of an information recommendation method provided by Embodiment 2 of the present invention. Optionally, the step of determining the target category subgroup corresponding to the target user in the at least one to-be-matched user group according to the user basic information of the target user is refined.

[0064] As Figure 2 shown, the method includes:

[0065] S210. Collect the operation information of the target user on the target display interface within a preset time period, and determine the target public characteristic attribute that matches the target user from multiple to-be-matched public characteristic attributes.

[0066] S220. Determine at least one user group to be matched that matches the target common feature attribute according to the pre-established corresponding relationship and the attribute label corresponding to the target common feature attribute.

[0067] S230. Determine the preset category corresponding to the category identifier in the at least one user group to be matched according to the category identifier carried in the target user basic information; wherein, the category identifier matches the preset category.

[0068] Among them, the category identifier can be understood as the identification information corresponding to the user basic information, and can be the keyword information corresponding to the basic information, such as name, ID number, age or occupation, etc., to determine the corresponding user basic information according to the category identifier.

[0069] Specifically, when determining the target category subgroup corresponding to the target user in at least one user group to be matched, it can be determined according to the category identifier carried in the user basic information. It can be understood that when classifying each user in each user group to be matched, the users in the user group to be matched are classified based on the preset category, and the preset category is matched with the category identifier carried in the user basic information. After obtaining the user basic information of the target user, based on the matching relationship between the category identifier and the preset category, at least one user group to be matched corresponding to the target user can be determined.

[0070] Exemplarily, taking the target user as an example of applying for a job online based on the network, before the target user browses the display information in the target display interface, when the target user logs in to the web page or application software, based on the information filled in by the target user on the login page, determine the target common feature attributes corresponding to the target user, such as expected position, expected city, and expected salary, etc., to determine the user group to be matched corresponding to the target user. Then, based on the obtained user basic information and the carried category identifier, such as name, age, ID number, and mobile phone number, etc., determine the target category subgroup corresponding to the target user based on each category identifier and the preset category. It should be noted that before recommending the online job application information, category information can be set according to common information, so as to classify each user group to be matched based on the preset category to obtain at least one user subgroup to be matched.

[0071] Optionally, the determining the preset category corresponding to the category identifier according to the category identifier carried in the target user basic information includes: taking the category identifier that appears for the first time as the new category identifier; updating the preset category according to the new category identifier to obtain the new preset category, and determining the new preset category corresponding to the new category identifier, so as to update each user subgroup to be matched based on the new preset category.

[0072] Among them, the newly added category identifier can be understood as a category identifier newly added based on the original category identifier. The newly added preset category can be understood as a preset category newly added based on the original preset category, and the newly added preset category is updated based on the newly added category identifier. That is to say, when the user basic information of the target user carries the newly added category identifier, the corresponding newly added preset category can be determined based on the newly added category identifier, and then at least one to-be-matched user group corresponding to the target user can be determined based on the newly added category identifier carried in the user basic information of the target user.

[0073] Specifically, in order to accurately match the user basic information of the target user with each to-be-matched category subgroup based on the category identifier, when the newly added category identifier is detected, correspondingly, it is necessary to update the preset category according to the newly added category identifier to obtain the newly added preset category, and then update each to-be-matched category subgroup according to the newly added preset category, so that when the newly added category identifier in the user basic information of the target user is detected, the target category subgroup corresponding to the target user can be determined based on the corresponding relationship between the newly added category identifier and the newly added preset category.

[0074] S240. Determine the target category subgroup corresponding to the target user according to the corresponding relationship between the preset category and the to-be-matched category subgroup set in advance.

[0075] Specifically, category information can be set in advance according to the user basic information, and then the users in the to-be-matched user group can be segmented based on the preset category to obtain at least one to-be-matched category subgroup, and each to-be-matched category subgroup matches each preset category. At the same time, the preset category also matches the category identifier carried in the user basic information. When the category identifier carried in the user basic information of the target user is detected, the preset category corresponding to the category identifier can be determined, and then the to-be-matched category subgroup corresponding to the preset category can be further determined. Based on this, the target category subgroup corresponding to the target user can be determined.

[0076] S250. Determine the to-be-displayed information corresponding to the target user according to the historical operation information of each to-be-matched user in the target category subgroup, and display the to-be-displayed information on the target display interface.

[0077] In a specific example, in order to recommend more suitable information to the target user, the users with the same characteristics as the target user can be analyzed, and then the information that the users in the same user group are interested in can be recommended to the target user. For example Figure 3As shown in the figure, first, the operation information of the target user in the target display interface is collected, and the collected operation information is placed in the matching pool for the waiting-to-be-matched group to determine the user portrait group corresponding to the target user, that is, the user group with the same characteristic attributes as the target user. According to the operation information of the target user, it can be determined whether there is different or extreme operation information of the target user within a preset time period, such as a large occasional change in the consumption range or a large consumption expenditure. It can be understood that the different or extreme operation information of the target user only appears occasionally, so such information needs to be excluded to avoid interfering with the analysis of the operation information of the target user. After information extraction is performed on the collected operation information, the public information corresponding to the target user (that is, the target public characteristic attributes) and the characteristic information (that is, the target category subgroup) can be determined. According to the target public characteristic attributes corresponding to the target user, at least one waiting-to-be-matched user group corresponding to the target user can be determined, and then the users in the waiting-to-be-matched user group are classified based on the preset category, and the preset category corresponding to the target user is determined according to the category identifier carried in the user information of the target user. Further, according to the corresponding relationship between the preset category and each waiting-to-be-matched category subgroup, the target category subgroup corresponding to the target user can be determined. In order to be able to better recommend information to the target user, the difference information of the target user, that is, the category identifier information carried in the user basic information of the target user, needs to be used as an extended factor and put into each waiting-to-be-matched user group to iteratively update the group portrait, that is, to update each waiting-to-be-matched user group and recommend more matching information to the users in this user group.

[0078] In the technical solution of this embodiment, according to the category identifier carried in the target user basic information, the preset category corresponding to the category identifier in the at least one waiting-to-be-matched user group is determined; wherein, the category identifier matches the preset category. By establishing the corresponding relationship between the category identifier and the preset category, the preset category corresponding to the category identifier in the user basic information can be determined, and further, at least one waiting-to-be-matched category subgroup corresponding to the target user can be determined based on the corresponding preset category. According to the corresponding relationship between the preset category and the waiting-to-be-matched category subgroup set in advance, the target category subgroup corresponding to the target user is determined. Based on the corresponding relationship between the category identifier in the user basic information of the target user and the preset category, and the corresponding relationship between the preset category and each waiting-to-be-matched category subgroup, the target category subgroup corresponding to the target user can be determined. This solves the problem that the information recommended based on the user basic information is inaccurate, and realizes the effect of recommending more matching information to individual users based on the characteristic information of the user group.

[0079] Embodiment III

[0080] Figure 4An information recommendation device provided in Embodiment 3 of the present invention, the device includes: a target public feature attribute determination module 310, a user group to be matched determination module 320, a target category subgroup determination module 430, and a to-be-displayed information display module 340.

[0081] Among them, the target public feature attribute determination module 310 is configured to collect operation information of a target user on a target display interface within a preset duration, and determine a target public feature attribute that matches the target user from multiple to-be-matched public feature attributes according to the operation information;

[0082] The user group to be matched determination module 320 is configured to determine at least one user group to be matched according to the target public feature attribute; wherein, the user group to be matched includes at least one user to be matched, and the public feature attributes corresponding to the user group to be matched are the same;

[0083] The target category subgroup determination module 330 is configured to determine a target category subgroup corresponding to the target user in the at least one user group to be matched according to the user basic information of the target user; wherein, the user group to be matched includes multiple subgroups divided according to preset category information;

[0084] The to-be-displayed information display module 340 is configured to determine to-be-displayed information corresponding to the target user according to the historical operation information of each user to be matched in the target category subgroup, and display the to-be-displayed information on the target display interface.

[0085] In the technical solution of this embodiment, the operation information of the target user on the target display interface within a preset time period is collected, and the target public feature attribute that matches the target user is determined from multiple to-be-matched public feature attributes. By analyzing the collected operation information of the target user and the corresponding relationship between each operation information and the to-be-matched public feature, the target public attribute corresponding to the target user can be determined. According to the target public feature attribute, at least one to-be-matched user group is determined. That is to say, the to-be-matched user group corresponding to the target user can be one or more. Through the target public feature attribute corresponding to the target user and the target attribute label corresponding to the target public attribute, at least one to-be-matched user group corresponding to the target user can be determined. According to the user basic information of the target user, the target category subgroup corresponding to the target user in the at least one to-be-matched user group is determined. Based on the user basic information, the user group to which the target user belongs can be further determined, and then a user group that is more suitable for the target user can be determined. Based on the information of interest of each to-be-matched user in the same target category subgroup, information to be recommended is determined. According to the historical operation information of each to-be-matched user in the target category subgroup, the information to be displayed corresponding to the target user is determined, and the information to be displayed is displayed on the target display interface. According to the historical operation information of each to-be-matched user, the satisfaction of each to-be-matched user with the information to be recommended is determined, and then the information to be displayed is determined based on the satisfaction, so as to display it to the target user on the target display interface. This solves the problem of inaccurate recommended information when making information recommendations based on a single user, realizes the analysis of user groups with the same attribute information, and achieves the effect of making information recommendations to users belonging to the same user group according to the analysis results.

[0086] Based on any optional technical solution in the embodiment of the present invention, optionally, the target public feature attribute determination module includes:

[0087] A corresponding relationship establishment sub-module, configured to establish a corresponding relationship between each to-be-matched public feature attribute and the operation information;

[0088] A to-be-matched public feature attribute determination sub-module, configured to, within a preset time period, when detecting the operation information of the target display interface, determine the to-be-matched public feature attribute corresponding to the operation information based on the corresponding relationship;

[0089] A target public feature attribute determination sub-module, configured to determine the target public feature attribute that matches the target user according to the trigger frequency information of the to-be-matched public feature attribute.

[0090] Based on any optional technical solution in the embodiment of the present invention, optionally, the to-be-matched user group determination module includes:

[0091] A to-be-matched user group sub-module, configured to determine at least one to-be-matched user group that matches the target public feature attribute according to a pre-established corresponding relationship and an attribute label corresponding to the target public feature attribute;

[0092] Wherein, the corresponding relationship includes the corresponding relationship between each to-be-matched public feature attribute and the attribute label, and the corresponding relationship between the attribute label and each to-be-matched user group.

[0093] Based on any optional technical solution in the embodiments of the present invention, optionally, the to-be-matched user group sub-module includes:

[0094] A preset category determination unit, configured to determine a preset category corresponding to the category identifier in the at least one to-be-matched user group according to the category identifier carried in the target user basic information; wherein, the category identifier matches the preset category;

[0095] A target category sub-group determination unit, configured to determine a target category sub-group corresponding to the target user according to a pre-set corresponding relationship between the preset category and the to-be-matched category group.

[0096] Based on any optional technical solution in the embodiments of the present invention, optionally, the preset category determination unit includes:

[0097] A new category identifier determination sub-unit, configured to use the category identifier that appears for the first time as a new category identifier;

[0098] A new preset category determination unit, configured to update the preset category according to the new category identifier to obtain a new preset category, and determine a new preset category corresponding to the new category identifier, so as to update each to-be-matched category sub-group based on the new preset category.

[0099] Based on any optional technical solution in the embodiments of the present invention, optionally, the to-be-displayed information display module includes:

[0100] A to-be-recommended information determination sub-module, configured to determine to-be-recommended information for each to-be-matched user according to the historical operation information of each to-be-matched user; wherein, the historical operation information includes at least one of browsing information, clicking information, and accessing information;

[0101] A to-be-displayed information determination sub-module, configured to determine to-be-displayed information that matches the target user according to the operation information of the target user in the display interface and the to-be-recommended information of each to-be-matched user in the corresponding target category sub-group.

[0102] The to-be-displayed information display sub-module is used to display the to-be-displayed information on the target display interface to present the to-be-displayed information to the target user.

[0103] Optionally, based on any optional technical solution in the embodiments of the present invention, the information recommendation device further includes:

[0104] The correspondence relationship establishment module is configured to collect the operation information of the target user on the target display interface within a preset time period, and before determining the target public feature attribute that matches the target user from multiple to-be-matched public feature attributes, preset the attribute tags corresponding to the to-be-matched public feature attributes, and establish the correspondence relationship between the attribute tags and the to-be-matched user groups;

[0105] The to-be-matched category sub-group classification module is configured to classify the to-be-matched user groups in advance based on a preset category, and determine the to-be-matched category sub-groups corresponding to the preset category.

[0106] The information recommendation device provided by the embodiments of the present invention can execute the information recommendation method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0107] It should be noted that the various units and modules included in the above device are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the embodiments of the present invention.

[0108] Embodiment 4

[0109] Figure 5 FIG. is a schematic structural diagram of an electronic device provided for Embodiment 4 of the present invention. Figure 5 FIG. shows a block diagram of an exemplary electronic device 40 suitable for implementing the embodiments of the present invention. Figure 5 The illustrated electronic device 40 is only an example and should not impose any limitation on the functions and usage scope of the embodiments of the present invention.

[0110] As Figure 5 shown, the electronic device 40 is presented in the form of a general-purpose computing device. The components of the electronic device 40 may include, but are not limited to: one or more processors or processing units 401, a system memory 402, and a bus 403 connecting different system components (including the system memory 402 and the processing unit 401).

[0111] The bus 403 represents one or more of several types of bus architectures, including a memory bus or memory controller, a peripheral bus, an Accelerated Graphics Port, a processor bus, or a local bus using any of the various bus architectures. By way of example, such architectures include, but are not limited to, Industry Standard Architecture (ISA) bus, Micro Channel Architecture (MAC) bus, Enhanced ISA bus, Video Electronics Standards Association (VESA) local bus, and Peripheral Component Interconnect (PCI) bus.

[0112] The electronic device 40 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by the electronic device 40, including both volatile and nonvolatile media, removable and non-removable media.

[0113] The system memory 402 can include computer system readable media in the form of volatile memory, such as random access memory (RAM) 404 and / or cache memory 405. The electronic device 40 may further include other removable / non-removable, volatile / nonvolatile computer system storage media. By way of example only, a storage system 406 can be used for reading from and writing to a non-removable, nonvolatile magnetic medium ( Figure 5 not shown and typically referred to as a "hard disk drive"). Although Figure 5 not shown in the figure, a disk drive for reading from and writing to a removable nonvolatile disk (such as a "floppy disk"), and an optical disk drive for reading from and writing to a removable nonvolatile optical disk (such as a CD-ROM, DVD-ROM or other optical medium) can be provided. In these cases, each drive can be connected to the bus 403 by one or more data media interfaces. The memory 402 can include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of the embodiments of the present invention.

[0114] A program / utility 408 having a set (at least one) of program modules 407 can be stored, for example, in the memory 402, and such program modules 407 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data, each of which or some combination thereof may include an implementation of a network environment. The program modules 407 generally carry out the functions and / or methods described in the embodiments of the present invention.

[0115] The electronic device 40 can also communicate with one or more external devices 409 (such as a keyboard, a pointing device, a display 410, etc.), and can also communicate with one or more devices that enable a user to interact with the electronic device 40, and / or communicate with any device that enables the electronic device 40 to communicate with one or more other computing devices (such as a network card, a modem, etc.). Such communication can be carried out through the input / output (I / O) interface 411. Moreover, the electronic device 40 can also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through the network adapter 412. As shown in the figure, the network adapter 412 communicates with other modules of the electronic device 40 through the bus 403. It should be understood that although Figure 5 not shown in the figure, other hardware and / or software modules can be used in combination with the electronic device 40, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0116] The processing unit 401 executes various functional applications and data processing by running programs stored in the system memory 402, for example, implementing the information recommendation method provided by the embodiments of the present invention.

[0117] Embodiment 5

[0118] Embodiment 5 of the present invention also provides a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute an information recommendation method when executed by a computer processor. The method includes:

[0119] Collecting operation information of a target user on a target display interface within a preset time period, and determining a target public characteristic attribute that matches the target user from a plurality of to-be-matched public characteristic attributes according to the operation information;

[0120] Determining at least one to-be-matched user group according to the target public characteristic attribute; wherein, at least one to-be-matched user is included in the to-be-matched user group, and the public characteristic attributes corresponding to the to-be-matched user group are the same;

[0121] Determining a target category subgroup corresponding to the target user in the at least one to-be-matched user group according to the user basic information of the target user; wherein, a plurality of to-be-matched category subgroups divided according to preset category information are included in the to-be-matched user group;

[0122] Determining to-be-displayed information corresponding to the target user according to the historical operation information of each to-be-matched user in the target category subgroup, and displaying the to-be-displayed information on the target display interface.

[0123] The computer storage medium of the embodiments of the present invention may adopt any combination of one or more computer-readable media. The computer-readable media may be computer-readable signal media or computer-readable storage media. The computer-readable storage media may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (a non-exhaustive list) of the computer-readable storage media include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer-readable storage media may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0124] The computer-readable signal media may include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal media may also be any computer-readable media other than the computer-readable storage media, which can send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0125] The program code contained on the computer-readable media may be transmitted by any appropriate medium, including but not limited to wireless, wire, optical fiber cable, RF, etc., or any suitable combination of the above.

[0126] The computer program code for performing the operations of the embodiments of the present invention may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0127] Note that the above is only a preferred embodiment of the present invention and the technical principles applied. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments. Without departing from the concept of the present invention, more other equivalent embodiments can be included, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. An information recommendation method, characterized in that, Including: Collecting operation information of a target user on a target display interface within a preset duration, and determining a target public characteristic attribute matching the target user from multiple to-be-matched public characteristic attributes, where the operation information at least includes operation information on accessing, collecting, viewing, deleting, downloading, placing an order for, and recommending to other users for the displayed recommendation information on the target display interface; Determining at least one to-be-matched user group according to the target public characteristic attribute; where at least one to-be-matched user is included in the to-be-matched user group, and the public characteristic attributes corresponding to the to-be-matched user group are the same; Determining a target category subgroup corresponding to the target user in the at least one to-be-matched user group according to the user basic information of the target user; where multiple to-be-matched category subgroups divided according to preset category information are included in the to-be-matched user group; Determining to-be-displayed information corresponding to the target user according to the historical operation information of each to-be-matched user in the target category subgroup, and displaying the to-be-displayed information on the target display interface, where the historical operation information is historical operation information collected based on the target display interface.

2. The method according to claim 1, characterized in that, The collecting operation information of a target user on a target display interface within a preset duration, and determining a target public characteristic attribute matching the target user from multiple to-be-matched public characteristic attributes, includes: Establishing a corresponding relationship between each to-be-matched public characteristic attribute and the operation information; Within a preset duration, when detecting operation information on the target display interface, determining the to-be-matched public characteristic attribute corresponding to the operation information based on the corresponding relationship; Determining the target public characteristic attribute matching the target user according to the trigger frequency information of the to-be-matched public characteristic attribute.

3. The method according to claim 1, wherein The determining at least one to-be-matched user group according to the target public characteristic attribute, includes: Determining at least one to-be-matched user group matching the target public characteristic attribute according to a pre-established corresponding relationship and the target attribute label corresponding to the target public characteristic attribute; Wherein, the corresponding relationship includes the corresponding relationship between each to-be-matched public characteristic attribute and each attribute label, and the corresponding relationship between each attribute label and each to-be-matched user group.

4. The method according to claim 3, wherein The determining a target category subgroup corresponding to the target user in the at least one to-be-matched user group according to the user basic information of the target user, includes: Determining a preset category corresponding to the category identifier in the at least one to-be-matched user group according to the category identifier carried in the target user basic information; where the category identifier matches the preset category; Determining the target category subgroup corresponding to the target user according to the pre-set corresponding relationship between the preset category and the to-be-matched category subgroup.

5. The method according to claim 4, wherein The determining a preset category corresponding to the category identifier according to the category identifier carried in the target user basic information, includes: Taking the first-occurring category identifier as a new category identifier; Update the preset categories according to the newly added category identifiers to obtain newly added preset categories, and determine the newly added preset categories corresponding to the newly added category identifiers, so as to update each subgroup of categories to be matched based on the newly added preset categories.

6. The method according to claim 1, wherein The step of determining the information to be displayed corresponding to the target user according to the historical operation information of each user to be matched in the target category subgroup and displaying the information to be displayed on the target display interface includes: Determine the information to be recommended for each user to be matched according to the historical operation information of each user to be matched; wherein, the historical operation information includes at least one of browsing information, clicking information, and access information; Determine the information to be displayed that matches the target user according to the operation information of the target user on the display interface and the information to be recommended for each user to be matched in the corresponding target category subgroup; Display the information to be displayed on the target display interface to display the information to be displayed to the target user.

7. The method according to claim 1, wherein It further includes: Preset the attribute tags corresponding to each common feature attribute to be matched, and establish the corresponding relationship between the attribute tags and each user group to be matched; Pre-classify each user group to be matched based on preset categories to determine the corresponding subgroup of categories to be matched for the preset categories.

8. An information recommendation device, characterized in that, It includes: A target common feature attribute determination module, configured to collect the operation information of the target user on the target display interface within a preset duration, and determine the target common feature attribute that matches the target user from multiple common feature attributes to be matched, where the operation information at least includes operation information such as access, collection, viewing, deletion, download, placing an order, and recommending to other users for the recommended information displayed on the target display interface; A user group to be matched determination module, configured to determine at least one user group to be matched according to the target common feature attribute; wherein, each user group to be matched includes at least one user to be matched, and the common feature attributes corresponding to the user groups to be matched are the same; A target category subgroup determination module, configured to determine the corresponding target category subgroup in the at least one user group to be matched according to the user basic information of the target user; wherein, each user group to be matched includes multiple subgroups divided according to preset category information; An information to be displayed display module, configured to determine the information to be displayed corresponding to the target user according to the historical operation information of each user to be matched in the target category subgroup, and display the information to be displayed on the target display interface, where the historical operation information is historical operation information collected based on the target display interface.

9. An electronic device, characterized in that, The electronic device includes: One or more processors; A storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors implement the information recommendation method as described in any one of claims 1-7.

10. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions are used to execute the information recommendation method as described in any one of claims 1-7 when executed by a computer processor.

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