CN115967839A - Live broadcast gift recommendation method and device - Google Patents
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Abstract
The invention discloses a live broadcast gift recommendation method and a device thereof, comprising the steps of obtaining gift data and user behavior data; establishing a gift information table, and respectively storing the two acquired data into different gift information tables, wherein the gift information tables comprise a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table; processing user login information, classifying the processed user login information, respectively matching the classified user login information with user behavior data in a user personal appreciation gift list and a user appreciation gift summary list, respectively associating the user personal appreciation gift list and the user appreciation gift summary list with a platform gift summary list, and obtaining gift related data to be recommended; and sending the gift related data to be recommended to the client, and displaying the live gift to the user matched with the user personal appreciation gift table or the user appreciation gift summary table by the client. The invention improves the appreciation experience of the user and the success rate of the live broadcast platform for obtaining appreciation.
Description
Technical Field
The invention relates to the technical field of live gift recommendation, in particular to a live gift recommendation method and a live gift recommendation device.
Background
With the development of network technology, a variety of live broadcast platforms are developed, live broadcast watching becomes a new entertainment and relaxation mode for people, generally, interaction between a user and a main broadcast has interactive behaviors such as comments, appreciation and the like, and many recommendation methods are available for recommending live broadcast gifts in the live broadcast platforms to the user.
Prior document 1 (CN 112578957 a) discloses a method and apparatus for recommending a virtual gift in live broadcasting, a computer-readable storage medium, and an electronic device, including: acquiring live comment information input at a spectator end; determining a virtual gift corresponding to the live comment information; determining recommendation information corresponding to the virtual gift so as to display the recommendation information at a spectator end; the audience can respond to the presenting operation aiming at the recommended information and trigger the presenting process of the virtual gift. According to the scheme, the gift which is recommended to be given needs to be matched according to live comment information sent by the audience in the live broadcast room, whether the audience inputs the comment information at a user side is limited, and the accuracy of the recommendation method is general.
Prior document 2 (CN 114710709 a) discloses a live broadcast room virtual gift recommendation method and apparatus, a computer storage medium, and an electronic device, including: acquiring the live broadcast room information of a live broadcast room where a main broadcast is located, and generating a gift recommendation instruction according to the live broadcast room information; and displaying a virtual gift control at the live broadcast user side based on the gift recommending instruction. According to the scheme, gifts to be given need to be matched and recommended according to the live broadcast room information of the live broadcast room of the anchor, the matching is limited by the contents of the live broadcast rooms of the anchors in different fields, and the recommendation method cannot cover all live broadcast gifts on the same live broadcast platform and is not comprehensive.
Therefore, it is desirable to provide a live gift recommendation method and device thereof, which are not limited by other behaviors except for enjoying of users, and can perform personalized recommendation of live gifts for different users without considering the field of the anchor.
Disclosure of Invention
In view of this, the present invention provides a live gift recommendation method, including:
the method comprises the steps of obtaining gift data and user behavior data, wherein the gift data comprises a gift identification and a gift price, and the user behavior data comprises a user unique identification, a gift identification enjoyed by a user, a gift price enjoyed by the user and a time for enjoying the gift by the user;
establishing a gift information table, and respectively storing the obtained gift data and the user behavior data into different gift information tables, wherein the gift information tables comprise a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table;
processing user login information, classifying the processed user login information, respectively matching the classified user login information with user behavior data in a user personal appreciation gift list and a user appreciation gift summary list, respectively associating the user personal appreciation gift list and the user appreciation gift summary list with a platform gift summary list, and obtaining gift related data to be recommended;
and sending the gift related data to be recommended to the client, and displaying the live gift to the user matched with the user personal appreciation gift table or the user appreciation gift summary table by the client.
Optionally, the storing the acquired gift data and the user behavior data into different gift information storage tables respectively comprises:
storing the gift data to a platform gift summary table, storing the user behavior data with the same user unique identification to a user personal appreciation gift table or storing all the user behavior data to the user appreciation gift summary table.
Optionally, the processing the user login information, and classifying the processed user login information includes:
processing user login information to obtain a user unique identifier of a user;
and classifying the user login information according to the unique user identifier.
Optionally, classifying the user login information according to the unique user identifier includes:
and judging whether the user unique identification of the user is empty, classifying the user to a new user if the user unique identification of the user is empty, and classifying the user to an old user if the user unique identification of the user is empty.
Optionally, the matching the classified user login information with the user behavior data in the user personal appreciation gift list and the user appreciation gift summary list respectively comprises:
and matching the new user with the user appreciation gift summary table to obtain the matching data of the new user, or matching the old user with the user personal appreciation gift table to obtain the matching data of the old user.
Alternatively, the first and second liquid crystal display panels may be,
when the user is a new user, associating the platform gift summary table with the user appreciation gift summary table;
and when the user is an old user, associating the platform gift summary table with the user personal appreciation gift table.
Optionally, obtaining the gift data comprises obtaining all gift data in the background of the live platform.
Optionally, the obtaining the user behavior data includes:
data embedding is carried out on the behavior of the user for enjoying the gift;
and acquiring user behavior data when the data is buried according to the data buried point.
Optionally, the time interval for the user to enjoy the gift in all the user behavior data does not exceed 30 days.
Based on the same conception, the invention also discloses a live gift recommendation device which comprises a data acquisition module, wherein the data acquisition module is used for acquiring gift data and user behavior data, the gift data comprises a gift identifier and a gift price, and the user behavior data comprises a user unique identifier, a gift identifier enjoyed by a user, a gift price enjoyed by the user and a time for the user to enjoy the gift;
the storage module is coupled with the data acquisition module and used for establishing a gift information table and respectively storing the acquired gift data and the user behavior data into different gift information tables, and each gift information table comprises a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table;
the judging module is coupled with the storage module and used for processing the user login information, classifying the processed user login information, respectively matching the classified user login information with the user behavior data in the user personal appreciation gift list and the user appreciation gift summary table, and respectively associating the user personal appreciation gift list and the user appreciation gift summary table with the platform gift summary table to obtain the gift related data to be recommended;
and the recommending module is coupled with the judging module and used for sending the gift related data to be recommended to the client, and the client displays the live gift to the user matched with the user personal appreciation gift table or the user appreciation gift summary table.
Compared with the prior art, the live broadcast gift recommendation method and the device thereof provided by the invention at least realize the following beneficial effects:
the live gift recommendation method and the device thereof comprehensively and accurately acquire gift data of the whole live broadcast platform and user behavior data of a user, and perform personalized recommendation of live gifts for different users by depending on recent reward behaviors of the user and gift data of the live broadcast platform under the condition that the field of a main broadcast is not considered, so that the recommended live gifts seen by new users and old users on the live broadcast platform are different, the problem of realizing intelligent recommendation of the live gifts under the condition of no manual intervention is solved, the reward experience of the users is improved, the success rate of the live broadcast platform for gaining rewards is improved, and the work burden of operation and maintenance personnel is reduced.
Of course, it is not necessary for any product in which the present invention is practiced to achieve all of the above-described technical effects simultaneously.
Other features of the present invention and advantages thereof will become apparent from the following detailed description of exemplary embodiments thereof, which proceeds with reference to the accompanying drawings.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.
Fig. 1 is a schematic flow chart of a live gift recommendation method provided by the present invention;
FIG. 2 is a schematic diagram of a gift information table provided by the present invention;
FIG. 3 is a schematic flow chart of classifying user login information according to the present invention;
FIG. 4 is a schematic flow chart of matching a user with a gift information table according to the present invention;
FIG. 5 is a schematic flow chart of acquiring user behavior data according to the present invention;
fig. 6 is a schematic structural diagram of a live gift recommendation device provided by the present invention;
fig. 7 is a schematic structural diagram of the data acquisition module in fig. 6.
Detailed Description
Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless it is specifically stated otherwise.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.
In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.
Referring to fig. 1-4, fig. 1 is a flow chart illustrating a live gift recommendation method provided by the present invention; FIG. 2 is a schematic diagram of a gift information table provided by the present invention; FIG. 3 is a schematic flow chart of classifying user login information according to the present invention; fig. 4 is a schematic flow chart of matching a user with a gift information table according to the present invention. The embodiment provides a live gift recommendation method, which comprises the following steps:
s1: the method comprises the steps of obtaining gift data and user behavior data, wherein the gift data comprises a gift identifier and a gift price, and the user behavior data comprises a unique user identifier, a gift identifier enjoyed by a user, a gift price enjoyed by the user and a time for enjoying the gift by the user;
specifically, the gift refers to a virtual gift for enjoying a main broadcast in a live broadcast platform in a live broadcast process, and the gift data comprises two data of a gift identification and a gift price; the user behavior refers to the behavior that the user watches the gift after entering the live broadcast platform, and the user behavior data comprises the unique user identifier, the gift identifier watched by the user, the gift price watched by the user and the time for the user to watch the gift.
S2: establishing a gift information table, and respectively storing the obtained gift data and the user behavior data into different gift information tables, wherein the gift information tables comprise a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table;
specifically, the gift information table comprises a platform gift summary table, a user personal enjoyment gift table and a user enjoyment gift summary table; storing the acquired gift data into a platform gift summary table, wherein the platform gift summary table is only related to the gift data and is unrelated to the user behavior data; storing the acquired user behavior data with the same user unique identifier into a user personal appreciation gift table, wherein the user behavior data stored in the user personal appreciation gift table are all user behavior data generated by the same user, and the user behavior data of other users do not exist; storing all the acquired user behavior data to a user enjoyment gift summary table; it is to be understood that the user behavior data in the user personal enjoyment gift list is a part of the user behavior data in the user enjoyment gift summary list.
S3: processing user login information, classifying the processed user login information, respectively matching the classified user login information with user behavior data in a user personal appreciation gift list and a user appreciation gift summary list, and respectively associating the user personal appreciation gift list and the user appreciation gift summary list with a platform gift summary list to obtain gift related data to be recommended;
specifically, the user login information comprises an obtained user unique identifier after a user logs in a live platform, firstly, when the user logs in a webpage of the live platform or an app page of the live platform, a login account of the user on the live platform becomes the user unique identifier, data query is carried out aiming at the user unique identifier of the current user, if the user unique identifier does not exist, the user logs in for the first time, the user unique identifier under the condition is defined to be empty, if the user unique identifier exists, the user is not logged in the live platform for the first time, the user unique identifier under the condition is defined to be non-empty, and it needs to be described that the reward behavior relates to money transaction, in order to ensure financial safety of the user and facilitate live platform management, the user can only perform reward behavior after logging in the live platform. Therefore, whether the user unique identification of the user is empty or not is judged by judging whether the user unique identification of the user exists before the user logs in, and if the user does not log in the live broadcast platform, the user unique identification does not exist, and meanwhile, the reward behavior cannot be carried out; classifying the user login information according to the unique user identifier, matching the new user with the user appreciation gift summary table, associating the user personal appreciation gift summary table with the platform gift summary table to obtain matching data of the new user, wherein the matching data is gift related data to be recommended for the new user, or matching the old user with the user personal appreciation gift summary table, associating the user appreciation gift summary table with the platform gift summary table to obtain matching data of the old user, and the matching data is gift related data to be recommended for the old user.
S4: sending the gift related data to be recommended to a client, and displaying live gifts to users matched with a user personal appreciation gift table or a user appreciation gift summary table by the client;
specifically, the matched gift related data to be recommended for the new user is sent to the client of the new user, the client displays a live gift for the new user, or the matched gift related data to be recommended for the old user is sent to the client of the old user, the client displays the live gift for the old user, and the displayed live gift comprises a gift identification and a gift price.
When the system is used specifically, the process that the gift data and the user behavior data are obtained, the gift information table is established, the obtained gift data and the user behavior data are stored in different gift information tables respectively, background data of a live broadcast platform are generated, when a user logs in an interface of the live broadcast platform, user login information is generated, and the live broadcast platform carries out intelligent live broadcast gift recommendation on the user according to the user login information.
Compared with the prior art, the live broadcast gift recommendation method provided by the embodiment at least achieves the following beneficial effects:
the live gift recommendation method provided by the embodiment can comprehensively and accurately acquire gift data of the whole live broadcast platform and user behavior data of a user, and personalized recommendation of live gifts is performed for different users by depending on recent watching behaviors of the user and the gift data of the live broadcast platform under the condition that the field of a main broadcast is not considered, so that the recommended live gifts seen by new users and old users on the live broadcast platform are different, intelligent recommendation of the live gifts under the condition that manual work is not interfered is achieved, the watching experience of the users is improved, the watching success rate of the live broadcast platform is improved, and the work burden of operation and maintenance personnel is reduced.
It should be noted that: the steps of the embodiment are mutually related, so that the division cannot be performed, the order of the steps cannot be adjusted, and the technical effect achieved by the embodiment cannot be achieved if the order of the steps is reversed; firstly, acquiring gift data and user behavior data; then, establishing a gift information table, and respectively storing the obtained gift data and the user behavior data into different gift information tables, wherein the gift information tables comprise a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table; secondly, processing user login information, classifying the processed user login information, respectively matching the classified user login information with user behavior data in a user personal appreciation gift list and a user appreciation gift summary table, respectively associating the user personal appreciation gift list and the user appreciation gift summary table with a platform gift summary table, and obtaining gift related data to be recommended; and finally, sending the data related to the gifts to be recommended to the client, and displaying the live gifts to the user matched with the user personal appreciation gift list or the user appreciation gift summary list by the client.
In one embodiment, with continued reference to FIG. 2, storing the obtained gift data and user behavior data into different gift information storage tables respectively comprises storing the gift data into a platform gift summary table, storing the user behavior data with the same user unique identifier into a user personal appreciation gift table, or storing all the user behavior data into the user enjoyment gift summary table.
Specifically, the gift information table comprises a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table; the platform gift summary table comprises data such as gift identification, gift price and the like; the user personal appreciation gift list comprises data such as a user unique identifier, a gift identifier enjoyed by the user, a gift price enjoyed by the user, time for enjoying the gift by the user and the like, wherein the user unique identifiers in the user personal appreciation gift list are the same; the user enjoyment gift summary table comprises data such as a user unique identifier, a gift identifier enjoyed by the user, a gift price enjoyed by the user, time for enjoying the gift by the user and the like, wherein the user unique identifiers in the user enjoyment gift summary table are multiple; the user behavior data with the same user unique identification are stored in the user personal appreciation gift table, the user behavior data specific to a certain user can be obtained, live gift recommendation can be conveniently carried out on old users, all the user behavior data with different user unique identifications are stored in the user appreciation gift summary table, the user behavior data of all the users can be obtained, live gift recommendation can be conveniently carried out on new users, and the success rate of appreciation obtained by a live broadcast platform can be improved.
It should be noted that the user behavior data in the user personal enjoyment gift list and the user enjoyment gift summary list are arranged according to the rule from high to low according to the occurrence frequency of the gift identifiers enjoyed by the user.
In one embodiment, as shown with continued reference to fig. 3, processing the user login information, and classifying the processed user login information includes: processing user login information to obtain a user unique identifier of a user; and classifying the user login information according to the unique user identifier.
Specifically, when a user logs in a webpage of a live platform or an app page of the live platform, user login information is generated, wherein the user login information comprises a user unique identifier obtained by the user; the user login information is classified according to the unique user identification, the user person and other people except the user person can be separated, different gift information tables can be matched, the recommended live gifts seen by the new user and the old user on the live broadcast platform are different, the problem of achieving intelligent recommendation of the live broadcast gifts under the condition that manual work is not intervened is solved, the appreciation experience of the user is improved, and the workload of operation and maintenance personnel is reduced.
In one embodiment, with continued reference to fig. 3, classifying the user login information according to the user unique identifier includes: and judging whether the user unique identification of the user is empty, classifying the user to a new user if the user unique identification of the user is empty, and classifying the user to an old user if the user unique identification of the user is empty.
Specifically, when a user logs in a webpage of a live broadcast platform or an app page of the live broadcast platform, user login information is generated and comprises a user unique identifier obtained by the user, if the user unique identifier is empty, the user is classified to a new user, otherwise, the user is classified to an old user, the user is classified into the new user and the old user, different gift information tables can be matched, finally, the new user and the old user see different recommended live gifts on the live broadcast platform, the problem of achieving intelligent recommendation of the live broadcast gifts under the condition of no manual intervention is solved, the appreciation experience of the user is improved, and the work burden of operation and maintenance personnel is relieved.
In one embodiment, with continued reference to fig. 4, the matching the classified user login information with the user behavior data in the user personal enjoyment gift list and the user enjoyment gift summary list respectively comprises: and matching the new user with the user appreciation gift summary table to obtain the matching data of the new user, or matching the old user with the user personal appreciation gift table to obtain the matching data of the old user.
Specifically, when a user enters a webpage of a live broadcast platform or an app page of the live broadcast platform, if the user does not log in an account, a platform gift summary table is directly matched for the user, after the user logs in the account, user login information is classified according to a user unique identifier, if the user unique identifier is empty, the user is classified to a new user, otherwise, the user is classified to an old user, live gifts which are enjoyed by all users in a recent period can be displayed for the new user by matching the user appreciation gift summary table for the new user, and live gifts which are enjoyed by the user in the recent period can be displayed for the old user by matching the user personal appreciation gift table for the old user; the three matching mechanisms are all used for displaying the live broadcast gifts which are more inclined for the user individuals and other people except the user individuals, so that the success rate of enjoying the live broadcast platform can be improved, and the recommended live broadcast gifts can better meet the personalized requirements of each user.
In one embodiment, when the user is a new user, associating the platform gift summary with the user enjoyment gift summary; and when the user is an old user, associating the platform gift summary table with the user personal appreciation gift table.
Specifically, the total table of the user appreciation gifts may store 100 pieces of user behavior data at the highest, the gift identifiers of the 100 pieces of user behavior data which are enjoyed by the user are different, when a new user is matched with the total table of the user appreciation gifts, if the total table of the user appreciation gifts is not full of 100 pieces of user behavior data currently, the total table of the platform gifts needs to be associated with the total table of the user appreciation gifts, and part of the user behavior data in the total table of the platform gifts is added into the total table of the user appreciation gifts, so that the user behavior data in the total table of the user appreciation gifts reaches 100 pieces, wherein the user behavior data in the total table of the platform gifts which needs to be added into the total table of the user appreciation gifts follows the following rule: in the user behavior data meeting the condition that gift identifications in the supplemented user behavior data are not coincident with gift identifications enjoyed by the users in the existing user enjoyment gift summary table, the user behavior data are arranged from high to low according to the frequency of occurrence of the gift identifications, in order to meet the condition that the storage space of the user appreciation gift summary table reaches 100 user behavior data, N (N is a positive integer which is more than or equal to 1 and less than or equal to 100) user behavior data in the current user appreciation gift summary table can reach 100, N user behavior data are supplemented from the platform gift summary table, and the user behavior data with the high frequency of occurrence of the gift identifications are preferred; similarly, the user personal appreciation gift list can store up to 100 pieces of user behavior data, the gift identifiers of the 100 pieces of user behavior data that are enjoyed by the user are different, when the old user matches with the user personal appreciation gift list, if the current user personal appreciation gift list has less than 100 pieces of user behavior data, the platform gift list needs to be associated with the user personal appreciation gift list, and part of the user behavior data in the platform gift list is added into the user personal appreciation gift list, so that the user behavior data in the user personal appreciation gift list reaches 100 pieces, wherein the user behavior data in the platform gift list that are added into the user personal appreciation gift list needs to follow the following rules: in the user behavior data which meets the condition that the gift identifications in the supplemented user behavior data are not coincident with the gift identifications enjoyed by the users in the user personal appreciation gift list, the user behavior data are arranged from high to low according to the frequency of occurrence of the gift identifications, in order to meet the condition that the storage space of the user personal appreciation gift list reaches 100 pieces of user behavior data, N (N is a positive integer which is more than or equal to 1 and less than or equal to 100) pieces of user behavior data in the current user personal appreciation gift list can reach 100 pieces, N pieces of user behavior data are supplemented from the platform gift summary list, and the user behavior data with the high frequency of occurrence of the gift identifications are prioritized; the platform gift summary table is respectively associated with the user appreciation gift summary table and the user personal appreciation gift table, the user behavior data in the platform gift summary table is supplemented to the user appreciation gift summary table with less than 100 pieces of user behavior data, the user behavior data in the platform gift summary table is supplemented to the user personal appreciation gift table with less than 100 pieces of user behavior data, the space of the user appreciation gift summary table and the user personal appreciation gift table can be better utilized, resource waste is avoided, live gifts can be recommended for users in high batches, and the recommendation success rate can be improved.
In one embodiment, and with continued reference to FIG. 1, obtaining the gift data includes obtaining all of the gift data in the background of the live platform.
Specifically, the gift data includes gift identification and gift price, the background of the live broadcast platform can preset the gift that the user can enjoy during the live broadcast usually, each gift has its gift identification and gift price, therefore, all gift data of the background of the live broadcast platform need to be obtained, follow-up contrast with user behavior data, through contrast of the two, the backstage manager can clearly and intuitively feel the situation that the gift is appreciated, according to the data after contrast, all gift data of the background of the live broadcast platform can be adjusted, make it accord with the user's liking more.
In an embodiment, fig. 5 is a schematic flowchart of acquiring user behavior data according to the present invention. Referring to fig. 5, acquiring the user behavior data includes: data embedding is carried out on the behavior of the user for enjoying the gift; and acquiring user behavior data when the data is embedded according to the data embedding points.
Specifically, corresponding data embedding is performed for the behavior of the user for enjoying the gift, when the user enjoys the gift, the data embedding is triggered, the user behavior data such as the unique user identifier, the gift identifier enjoyed by the user, the gift price enjoyed by the user, the time for the user to enjoy the gift and the like under the current condition are obtained, the user behavior data is obtained by whether the user triggers the data embedding, and the obtained user behavior data has comprehensiveness and accuracy.
In one embodiment, the time interval between all user behavior data when the user views the gift does not exceed 30 days.
Specifically, a program is preset in a background of a live broadcast platform, the program updates user behavior data at a fixed time every day, the user behavior data generated on the same day is replaced with the user behavior data before 30 days, and when the user behavior data is acquired, the user behavior data in a time period from 29 days before the same day to the same day can be acquired; the time for watching the gifts by the users in all the user behavior data is set to be no more than 30 days, so that the timeliness of the user behavior data can be guaranteed, the live gifts recommended by the live broadcast platform are closer to the recent tendency of the users, and the success rate of watching the gifts by the live broadcast platform is improved.
In one embodiment, fig. 6 is a schematic structural diagram of a live gift recommendation device provided by the present invention; fig. 7 is a schematic diagram of the data acquisition module in fig. 6. Referring to fig. 6 to 7, the live gift recommendation apparatus includes a data acquisition module, where the data acquisition module is configured to acquire gift data and user behavior data, the gift data includes a gift identifier and a gift price, and the user behavior data includes a user unique identifier, a gift identifier enjoyed by a user, a gift price enjoyed by the user, and a time when the user enjoys the gift;
the storage module is coupled with the data acquisition module and used for establishing a gift information table and respectively storing the acquired gift data and the user behavior data into different gift information tables, and each gift information table comprises a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table;
the judging module is coupled with the storage module and used for processing the user login information, classifying the processed user login information, respectively matching the classified user login information with user behavior data in the user personal appreciation gift list and the user appreciation gift total list, and respectively associating the user personal appreciation gift list and the user appreciation gift total list with the platform gift total list to obtain gift related data to be recommended;
and the recommending module is coupled with the judging module and used for sending the gift related data to be recommended to the client, and the client displays the live gift to the user matched with the user personal appreciation gift table or the user appreciation gift summary table.
Specifically, the data acquisition module is used for acquiring gift data and user behavior data, wherein the gift data comprises a gift identifier and a gift price, and the user behavior data comprises a user unique identifier, a gift identifier enjoyed by a user, a gift price enjoyed by the user and a time for the user to enjoy the gift; the data acquisition module comprises a gift data acquisition module and a user behavior data acquisition module, the gift data acquisition module is used for acquiring gift data, the user behavior data acquisition module is used for acquiring user behavior data, and the gift data acquisition module and the user behavior data acquisition module are not interfered with each other;
the storage module is coupled with the data acquisition module and used for establishing a gift information table and respectively storing the acquired gift data and the user behavior data into different gift information tables, the gift information tables comprise a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table, the gift data corresponds to the platform gift summary table, and the user behavior data corresponds to the user personal appreciation gift table and the user appreciation gift summary table;
the judging module is coupled with the storage module and used for processing the user login information, classifying the processed user login information, and respectively matching the classified user login information with the user behavior data in the user personal appreciation gift list and the user appreciation gift general list to obtain gift related data to be recommended;
the recommending module is coupled with the judging module and used for sending gift related data to be recommended to the client, the client displays live gifts to users who watch the gift table personally or watch the gift summary table matched with the users, under the common condition, the client is divided into two types, including live platform webpages or live platform app pages, and although the interfaces of different clients are different in size, 100 pieces of gift information can be recommended.
In an optional embodiment, the user a is an old user of the live broadcast platform, after the user a logs in the live broadcast platform on the same day, the reward behavior of the user a generates user behavior data, the user behavior data comprise a user identifier, a gift identifier appreciated by the user, a gift price appreciated by the user and a gift enjoying time of the user, a data acquisition module in the live broadcast gift recommendation device can acquire the user behavior data of the user a and the gift data of the live broadcast platform within the last 30 days, a storage module establishes a platform gift summary table, a user personal reward gift summary table of the user a and a gift reward gift summary table of the user, next time, if the user a does not log in a live broadcast platform webpage or a live broadcast platform webpage, the live broadcast platform recommends the relevant gift data in the platform gift summary table to the user a, although the user a can see the recommended live broadcast gift, the user a cannot perform the reward behavior, if the user a logs in the live broadcast platform webpage or the live broadcast platform webpage, the live broadcast platform can log in the gift summary table the gift data of the user a, and the user a can recommend the reward the user behavior.
By the embodiment, the live gift recommendation method and the device thereof provided by the invention at least realize the following beneficial effects:
the live broadcast gift recommendation method and device provided by the invention can comprehensively and accurately acquire the gift data of the whole live broadcast platform and the user behavior data of the user, and perform personalized recommendation of live broadcast gifts for different users by depending on recent rewarding behaviors of the user and the gift data of the live broadcast platform under the condition of not considering the field of the main broadcast, so that the recommended live broadcast gifts seen by new users and old users on the live broadcast platform are different, the problem of realizing intelligent recommendation of live broadcast gifts under the condition of no manual intervention is solved, the rewarding experience of the users is improved, the success rate of rewarding obtained by the live broadcast platform is improved, and the work burden of operation and maintenance personnel is reduced.
Although some specific embodiments of the present invention have been described in detail by way of examples, it should be understood by those skilled in the art that the above examples are for illustrative purposes only and are not intended to limit the scope of the present invention. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the invention. The scope of the invention is defined by the appended claims.
Claims (10)
1. A live gift recommendation method is characterized by comprising the following steps:
the method comprises the steps of obtaining gift data and user behavior data, wherein the gift data comprises a gift identification and a gift price, and the user behavior data comprises a user unique identification, a gift identification enjoyed by a user, a gift price enjoyed by the user and a time for the user to enjoy the gift;
establishing a gift information table, and respectively storing the acquired gift data and the acquired user behavior data into different gift information tables, wherein the gift information tables comprise a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table;
processing user login information, classifying the processed user login information, respectively matching the classified user login information with the user behavior data in the user personal appreciation gift list and the user appreciation gift general list, respectively associating the user personal appreciation gift list and the user appreciation gift general list with the platform gift general list, and obtaining gift related data to be recommended;
and sending the gift related data to be recommended to a client, wherein the client displays a live gift to a user matched with the user personal appreciation gift list or the user appreciation gift summary list.
2. The live gift recommendation method of claim 1, wherein said storing the acquired gift data and the user behavior data into different gift information storage tables respectively comprises:
storing the gift data to the platform gift summary table, storing the user behavior data with the same user unique identifier to the user personal appreciation gift table, or storing all the user behavior data to the user appreciation gift summary table.
3. The live gift recommendation method of claim 1, wherein the processing user login information, and the classifying the processed user login information comprises:
processing user login information to obtain the user unique identification of the user;
and classifying the user login information according to the unique user identification.
4. The live gift recommendation method of claim 3 wherein said classifying said user login information according to said user unique identifier comprises:
and judging whether the user unique identification of the user is empty or not, if so, classifying the user to a new user, otherwise, classifying the user to an old user.
5. The live gift recommendation method of claim 4, wherein said matching the classified user login information with the user behavior data in the user personal appreciation gift list and the user appreciation gift summary table respectively comprises:
and matching the new user with the user appreciation gift summary table to obtain the matching data of the new user, or matching the old user with the user personal appreciation gift table to obtain the matching data of the old user.
6. The live gift recommendation method of claim 5,
when the user is a new user, associating the platform gift summary table with the user reward gift summary table;
and when the user is an old user, associating the platform gift summary table with the user personal appreciation gift table.
7. The live gift recommendation method of claim 1 wherein said obtaining gift data comprises obtaining all of said gift data in a background of a live platform.
8. The live gift recommendation method of claim 1, wherein said obtaining user behavior data comprises:
data embedding is carried out on the behavior of the user for enjoying the gift;
and acquiring the user behavior data when the data is embedded according to the data embedding point.
9. A live gift recommendation method of any one of claims 1-8 wherein a time interval between the user enjoyment of gifts in all of said user behavior data does not exceed 30 days.
10. A live gift recommending device is characterized by comprising a data obtaining module, wherein the data obtaining module is used for obtaining gift data and user behavior data, the gift data comprises a gift identifier and a gift price, and the user behavior data comprises a user unique identifier, a gift identifier enjoyed by a user, a gift price enjoyed by the user and a time for enjoying the gift by the user;
the storage module is coupled with the data acquisition module and used for establishing a gift information table and storing the acquired gift data and the user behavior data into different gift information tables respectively, wherein the gift information tables comprise a platform gift summary table, a user personal appreciation gift table and a user appreciation gift summary table;
the judging module is coupled with the storage module and used for processing user login information, classifying the processed user login information, respectively matching the classified user login information with the user behavior data in the user personal appreciation gift list and the user appreciation gift summary table, and respectively associating the user personal appreciation gift list and the user appreciation gift summary table with the platform gift summary table to obtain gift related data to be recommended;
and the recommending module is coupled with the judging module and used for sending the gift related data to be recommended to a client, and the client displays the live gifts to the user matched with the user personal appreciation gift list or the user appreciation gift summary list.
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