CN114880560A - Content recommendation method and device, storage medium and electronic device - Google Patents
Content recommendation method and device, storage medium and electronic device Download PDFInfo
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Abstract
The application discloses a content recommendation method and device, a storage medium and an electronic device, and relates to the technical field of smart families, wherein the content recommendation method comprises the following steps: under the condition of receiving a display content request of a target object, determining equipment information corresponding to target equipment which has a binding relationship with the target object, and acquiring a historical content display record recorded in the target equipment; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device; determining preference information of the target object for the content according to the equipment information and the historical content display record; and determining target recommendation values of different types of contents accepted by the target object based on the preference information, and recommending the target contents to the target object according to the target recommendation values. The method and the device can solve the problems that in the prior art, content recommendation adjustment cannot be performed according to the dynamically changed preference of the target object and the like.
Description
Technical Field
The application relates to the field of smart homes, in particular to a content recommendation method and device, a storage medium and an electronic device.
Background
Common recommendation algorithms include collaborative filtering recommendation methods, content-based recommendation methods, association rule-based recommendation, utility-based recommendation, knowledge-based recommendation, combined recommendation, and the like. The intelligent recommendation algorithm is a key technology in the field of content push application, and is a mainstream scheme for predicting the purchase intention and preference of consumers at present. The intelligent recommendation technology of the shopping website is relatively well developed at the present stage, but the pushing of the content preferred by the user and the intelligent recommendation of the shopping website are greatly different and are not completely applicable. For example, when recommending popular science articles to a user, a single intention and preference static recommendation method cannot timely grasp dynamic changes of the user, so that the recommended popular science articles are low in application efficiency, the requirements of the user cannot be met, and the recommendation is too rigid.
Aiming at the problems that the content recommendation adjustment cannot be carried out according to the dynamically changed preference of the target object and the like in the related technology, an effective technical scheme is not provided yet.
Disclosure of Invention
The embodiment of the invention provides a content recommendation method and device, a storage medium and an electronic device, which are used for at least solving the problems that in the related art, content recommendation adjustment cannot be carried out according to dynamically-changed preference of a target object and the like.
According to an embodiment of the present invention, there is provided a content recommendation method including: under the condition of receiving a content display request of a target object, determining equipment information corresponding to target equipment which has a binding relationship with the target object, and acquiring a historical content display record recorded in the target equipment; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device; determining preference information of the target object for the content according to the equipment information and the historical content display record; and determining a target recommendation value of the target object for receiving different types of contents based on the preference information, and recommending the target content to the target object according to the target recommendation value.
In an exemplary embodiment, in a case that a display content request of a target object is received, before determining device information corresponding to a target device having a binding relationship with the target object and acquiring a history content display record recorded in the target device, the method further includes: under the condition that a target object to be subjected to content recommendation exists in a target area, acquiring identification information corresponding to the target object; and screening out target equipment which has a binding relationship with the target object from the plurality of equipment in the target area according to the identification information.
In one exemplary embodiment, determining the preference information of the target object for the content according to the device information and the historical content display record comprises: determining a first recommended value according to the equipment information; wherein the device information includes at least one of: the device type of the target device, the device number of the same type of target device, the binding time of the target device and the target object, and the content displayed by the target device correspondingly; determining a second recommendation value according to the historical content display record; and summarizing the first recommended value and the second recommended value to determine preference information of the target object for content.
In one exemplary embodiment, determining a first recommendation value from the device information includes: carrying out statistical processing on the equipment information according to preset equipment classification; determining the type of the equipment currently used by the target object and the quantity of the equipment corresponding to each type of the equipment; and determining a first recommendation value for recommending the content corresponding to each equipment type according to the number of the equipment.
In an exemplary embodiment, after determining the first recommendation value for recommending the content by the number of devices, the method further includes: sorting the first recommended value from at least a plurality of values based on the number of the devices; under the condition that the number of devices of two device types is the same, acquiring first binding time of a first device type and the target object, and acquiring second binding time of a second device type and the target object; and comparing the first binding time with the second binding time to determine the type of the equipment for preferentially recommending the content.
In one exemplary embodiment, determining a second recommendation value based on the historical content display record comprises: analyzing the historical content display record to obtain a plurality of operation behaviors of the target object on the content displayed on the target equipment, determining weight values corresponding to the operation behaviors from a preset behavior weight list, and counting the behavior times of each operation behavior; and comprehensively calculating the weight value and the behavior times to obtain a second recommended value corresponding to each operation behavior.
In an exemplary embodiment, determining, based on the preference information, a recommendation value that the target object accepts different types of content, and recommending the target content to the target object according to the target recommendation value includes: matching the equipment type corresponding to the first recommended value in the preference information with the operation behavior corresponding to the second recommended value; adding the first recommended value and the second recommended value in the matching result to determine a target recommended value for indicating content information recommendation; and sequentially recommending corresponding target content to the target object based on the target recommendation value, wherein the target content is a popular science article for guiding the use of the target device.
According to another embodiment of the present invention, there is provided a content recommendation method apparatus, including: the device comprises a first determining module, a second determining module and a display module, wherein the first determining module is used for determining device information corresponding to target equipment which has a binding relation with a target object and acquiring a historical content display record recorded in the target equipment under the condition of receiving a display content request of the target object; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device; the second determination module is used for determining preference information of the target object for the content according to the equipment information and the historical content display record; and the recommending module is used for determining target recommending values of different types of contents accepted by the target object based on the preference information and recommending the target contents to the target object according to the target recommending values.
In an exemplary embodiment, the apparatus further includes: the screening module is used for acquiring identification information corresponding to a target object under the condition that the target object to be subjected to content recommendation exists in a target area; and screening out target equipment which has a binding relationship with the target object from the plurality of equipment in the target area according to the identification information.
In an exemplary embodiment, the second determining module is further configured to determine a first recommended value according to the device information; wherein the device information includes at least one of: the device type of the target device, the device number of the same type of target device, the binding time of the target device and the target object, and the content displayed by the target device correspondingly; determining a second recommendation value according to the historical content display record; and summarizing the first recommended value and the second recommended value to determine preference information of the target object for content.
In an exemplary embodiment, the second determining module is further configured to perform statistical processing on the device information according to a preset device classification; determining the type of the equipment currently used by the target object and the quantity of the equipment corresponding to each type of the equipment; and determining a first recommendation value for recommending the content corresponding to each equipment type according to the number of the equipment.
In an exemplary embodiment, the second determining module further includes: the comparison unit is used for sorting the first recommended value from at least a plurality of values based on the number of the devices; under the condition that the number of devices of two device types is the same, acquiring first binding time of a first device type and the target object, and acquiring second binding time of a second device type and the target object; and comparing the first binding time with the second binding time to determine the type of the equipment for preferentially recommending the content.
In an exemplary embodiment, the second determining module is further configured to analyze the historical content display record, to obtain a plurality of operation behaviors of the target object on the content displayed on the target device, determine weight values corresponding to the plurality of operation behaviors from a preset behavior weight list, and count the behavior times of each operation behavior; and comprehensively calculating the weight value and the behavior times to obtain a second recommended value corresponding to each operation behavior.
In an exemplary embodiment, the recommending module is further configured to match a device type corresponding to the first recommended value in the preference information with an operation behavior corresponding to the second recommended value; adding the first recommended value and the second recommended value in the matching result to determine a target recommended value for indicating content information recommendation; and sequentially recommending corresponding target content to the target object based on the target recommendation value, wherein the target content is a popular science article for guiding the use of the target device.
According to a further embodiment of the present invention, there is also provided a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
According to yet another embodiment of the present invention, there is also provided an electronic device, including a memory in which a computer program is stored and a processor configured to execute the computer program to perform the steps in any of the above method embodiments.
According to the method and the device, under the condition that a display content request of the target object is received, the device information corresponding to the target device which is in binding relation with the target object is determined, and the historical content display record recorded in the target device is obtained; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device; determining preference information of the target object for the content according to the equipment information and the historical content display record; and determining target recommendation values of different types of contents accepted by the target object based on the preference information, and recommending the target contents to the target object according to the target recommendation values. That is to say, the device information and the historical content display record of the target object are determined, the dynamic preference information of the target object is tracked, different types of content are displayed on the target terminal corresponding to the target device according to different recommendation values, and accordingly, the content is recommended to the target object, so that the problems that in the prior art, content recommendation adjustment cannot be performed according to the dynamically-changed preference of the target object, and the like can be solved, furthermore, the recommendable content corresponding to the target device is flexibly recommended by determining the dynamic recommendation value of the target object, rapid processing can be performed on variable target objects, and the use experience of users is improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a hardware environment diagram of a content recommendation method according to an embodiment of the present application;
fig. 2 is a flowchart of a recommendation method of content according to an embodiment of the present invention;
FIG. 3 is a flowchart of an algorithm for popular article recommendation based on home devices in accordance with an alternative embodiment of the present invention;
fig. 4 is a block diagram of a method and apparatus for recommending contents according to an embodiment of the present invention;
fig. 5 is a block diagram of another content recommendation method apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an aspect of an embodiment of the present application, there is provided a method of recommending content. The content recommendation method is widely applied to full-House intelligent digital control application scenes such as intelligent homes (Smart Home), intelligent homes, intelligent Home equipment ecology, intelligent House (Intelligent House) ecology and the like. Alternatively, in the present embodiment, the content recommendation method described above may be applied to a hardware environment formed by the terminal device 102 and the server 104 as shown in fig. 1. As shown in fig. 1, the server 104 is connected to the terminal device 102 through a network, and may be configured to provide a service (e.g., an application service) for the terminal or a client installed on the terminal, set a database on the server or independent of the server, and provide a data storage service for the server 104, and configure a cloud computing and/or edge computing service on the server or independent of the server, and provide a data operation service for the server 104.
The network may include, but is not limited to, at least one of: wired networks, wireless networks. The wired network may include, but is not limited to, at least one of: a wide area network, a metropolitan area network, which may include, but is not limited to, at least one of: WIFI (Wireless Fidelity), bluetooth. Terminal equipment 102 can be but not limited to be PC, the cell-phone, the panel computer, intelligent air conditioner, intelligent cigarette machine, intelligent refrigerator, intelligent oven, intelligent kitchen range, intelligent washing machine, intelligent water heater, intelligent washing equipment, intelligent dish washer, intelligent projection equipment, intelligent TV, intelligent clothes hanger, intelligent (window) curtain, intelligence audio-visual, smart jack, intelligent stereo set, intelligent audio amplifier, intelligent new trend equipment, intelligent kitchen guarding equipment, intelligent bathroom equipment, intelligence robot of sweeping the floor, intelligence robot of wiping the window, intelligence robot of mopping the ground, intelligent air purification equipment, intelligent steam ager, intelligent microwave oven, intelligent kitchen is precious, intelligent clarifier, intelligent water dispenser, intelligent lock etc..
In the present embodiment, a method for recommending content is provided, and fig. 2 is a flowchart of a method for recommending content according to an embodiment of the present invention, where the flowchart includes the following steps:
step S202, under the condition of receiving a display content request of a target object, determining equipment information corresponding to target equipment which has a binding relation with the target object, and acquiring a historical content display record recorded in the target equipment; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device;
optionally, the operation record is an operation content of the target object on a display interface of the target terminal corresponding to the target device, for example, according to statistics of behavior times of the target object on a series of behaviors (such as click-in, praise, collection, forwarding, comment and the like) of article contents including different labels, the method determines a preference degree of the target object on popular science articles of each household appliance type through comprehensive calculation, and generates an accurate popularity ranking.
Step S204, determining the preference information of the target object for the content according to the equipment information and the historical content display record;
step S206, determining target recommendation values of different types of contents accepted by the target object based on the preference information, and recommending the target contents to the target object according to the target recommendation values.
Optionally, the device information may be a home device list of a home where the target object is located, and may include: the system comprises a family room device relation table, a networker model index table, model and application classification information, a product classification and label mapping table and a user device first-time binding full snapshot table. The operation records are operation contents of the target object on a display interface of the target terminal corresponding to the target device, for example, according to statistics of behavior times of the target object on a series of behaviors (such as click-in, praise, collection, forwarding, comment and the like) of article contents containing different labels, comprehensive calculation is performed, the likeability of the target object to popular science articles of each household appliance type is determined, and an accurate popularity ranking is generated.
Through the steps, under the condition that a display content request of a target object is received, determining equipment information corresponding to target equipment which has a binding relation with the target object, and acquiring a historical content display record recorded in the target equipment; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device; determining preference information of the target object for the content according to the equipment information and the historical content display record; and determining target recommendation values of different types of contents accepted by the target object based on the preference information, and recommending the target contents to the target object according to the target recommendation values. That is to say, the device information and the historical content display record of the target object are determined, the dynamic preference information of the target object is tracked, different types of content are displayed on the target terminal corresponding to the target device according to different recommendation values, and accordingly, the content is recommended to the target object, so that the problems that in the prior art, content recommendation adjustment cannot be performed according to the dynamically-changed preference of the target object, and the like can be solved, furthermore, the recommendable content corresponding to the target device is flexibly recommended by determining the dynamic recommendation value of the target object, rapid processing can be performed on variable target objects, and the use experience of users is improved.
In an exemplary embodiment, in a case that a display content request of a target object is received, before determining device information corresponding to a target device having a binding relationship with the target object and acquiring a history content display record recorded in the target device, the method further includes: under the condition that a target object to be subjected to content recommendation exists in a target area, acquiring identification information corresponding to the target object; and screening out target equipment which has a binding relationship with the target object from the plurality of equipment in the target area according to the identification information.
Briefly, in order to better recommend target content to a target object in a target area, the target object and a target device having a binding relationship in advance are screened through identification information, for example, the smart network device (corresponding to the target device) has a unique device identifier, and when a user (corresponding to the target object) purchases a device, the user binds the purchased device, so that the device and the user are associated. And according to the relationship between the user and the family and the binding relationship between the user and the equipment, the relationship between the family id (equivalent to the identification information) and the equipment mac is associated. Based on the association logic, data is collected on the equipment list of the family, so that accurate popular science article recommendation can be performed on the family.
In one exemplary embodiment, determining the preference information of the target object for the content according to the device information and the historical content display record comprises: determining a first recommended value according to the equipment information; wherein the device information includes at least one of: the device type of the target device, the device number of the same type of target device, the binding time of the target device and the target object, and the content displayed by the target device correspondingly; determining a second recommendation value according to the historical content display record; and summarizing the first recommended value and the second recommended value to determine preference information of the target object for content.
In one exemplary embodiment, determining a first recommendation value from the device information includes: carrying out statistical processing on the equipment information according to preset equipment classification; determining the type of the equipment currently used by the target object and the quantity of the equipment corresponding to each type of the equipment; and determining a first recommendation value for recommending the content corresponding to each equipment type according to the number of the equipment.
In an exemplary embodiment, after determining the first recommendation value for recommending the content by the number of devices, the method further includes: sorting the first recommended value from at least a plurality of values based on the number of the devices; under the condition that the number of devices of two device types is the same, acquiring first binding time of a first device type and the target object, and acquiring second binding time of a second device type and the target object; and comparing the first binding time with the second binding time to determine the type of the equipment for preferentially recommending the content.
It can be understood that when the number of devices is large, it indicates that the target object may use the device type with a high frequency, therefore, when pushing the target content to the target object, the device type may be considered preferentially, when the number of occurrences is the same, the usage history time of the device type by the target object is determined by determining the binding time with the target object, and the target content corresponding to the device type with a long usage history time is pushed preferentially to the target object, so that the target object may better use and operate the device corresponding to the device type, and the usage experience of the target object is improved.
In one exemplary embodiment, determining a second recommendation value based on the historical content display record comprises: analyzing the historical content display record to obtain a plurality of operation behaviors of the target object on the content displayed on the target equipment, determining weight values corresponding to the operation behaviors from a preset behavior weight list, and counting the behavior times of each operation behavior; and comprehensively calculating the weight value and the behavior times to obtain a second recommended value corresponding to each operation behavior.
In an exemplary embodiment, determining, based on the preference information, a recommendation value that the target object accepts different types of content, and recommending the target content to the target object according to the target recommendation value includes: matching the equipment type corresponding to the first recommended value in the preference information with the operation behavior corresponding to the second recommended value; adding the first recommended value and the second recommended value in the matching result to determine a target recommended value for indicating content information recommendation; and sequentially recommending corresponding target content to the target object based on the target recommendation value, wherein the target content is a popular science article for guiding the use of the target device.
It can be understood that the single biased recommendation cannot accurately grasp the favorite preference of the target object, and by combining the first recommendation value indicating the number of devices and the second recommendation value indicating that the target object uses the recommended target content to operate the devices, under the condition that the use requirement of the target object is met, popular science articles which are more easily accepted for use are pushed to the target object, so that the degree of interest of a user is greatly improved, and the reading effect of the target object on the target content is improved.
In order to better understand the process of the content recommendation method, the following describes a flow of the content recommendation method with reference to several alternative embodiments.
The home appliance service APP is more suitable for providing home appliance related popular science articles for the user, and the user is recommended by taking what as a main body and what theme type articles are recommended, so that the problems that the use requirements of the user can be met most and the use experience level of the user is improved are difficult to grasp are solved. Therefore, research is conducted on the recommendation problem of popular science articles of the household appliance user, and relevant articles conforming to the use condition of the household appliance of the user are pushed. The method aims to realize the effects of spreading the relevant small knowledge of the household appliances and popularizing the wonderful and exciting life, so that the articles pushed by the APP can really meet the preference of the user, correct use suggestions are provided for the user to use the household appliances, and the dependence degree of the user on the application is improved.
As an alternative implementation, the intelligent recommendation algorithm is a key technology in the content push application field, and is a mainstream scheme for predicting consumer buying intention and consumer preferences at present. The intelligent recommendation technology of the shopping website is relatively well developed at the present stage, but the pushing of the content preferred by the user and the intelligent recommendation of the shopping website are greatly different and are not completely applicable. Therefore, solving the pushing of the content of interest to the user requires algorithm design from multiple angles. For example, the recommendation algorithm includes a collaborative filtering recommendation method, a content-based recommendation method, an association rule-based recommendation, a utility-based recommendation, a knowledge-based recommendation, a combination recommendation, and the like.
In addition, in the conventional commodity recommendation method, a user is depicted according to the browsing record of the user on the commodity of the shopping website and the historical purchasing situation. Like recommending similar products based on the user's browsing records: when the user often has beauty products such as skin care products and cosmetics in the historical purchase record, and when the user's historical order record contains women's clothing and the unit price exceeds ten thousand yuan, or the user often purchases products of high-end brands, the user can be presumed to be 'white and rich'. Therefore, commodities of relatively high-end brands suitable for female application can be recommended for the user according to the current browsing requirement. Such as recommending complementary products based on a user review record. For example, the user may purchase a spectacle frame, and recommend a store or product of the optometric spectacle to the user according to the complementary association of the commodities.
The science popularization article recommendation is different from the recommendation method. The articles that the user wishes to see may be affected by many factors, such as the areas of interest to the user, the problems with the use of appliances that the user encounters in their lives, the types and numbers of appliances in the user's home, and so on. The popularity value of the article reflects the overall popularity of the article, and also affects the satisfaction degree of the user with the recommendation.
In addition, based on a content recommendation method, complex attributes are not well handled, and sufficient data are required to construct a classifier to establish a user portrait, which is based on a large amount of user behavior data; the collaborative filtering recommendation method has the problems of expandability, the quality depends on a historical data set, and the recommendation quality is poor when the system starts; based on the rule recommendation method, the rule extraction is difficult and time-consuming, the product name synonymity problem is solved, and the personalization degree is low; based on a utility recommendation method, a user must input a utility function, and the recommendation is static, poor in flexibility and has the problem of attribute overlapping; knowledge is difficult to obtain based on the knowledge recommendation method, and recommendations are static.
In order to overcome the disadvantages of the method, as another alternative embodiment, a method for recommending science popularization articles based on home equipment is provided, and articles in a science popularization article library are recommended to a home according to the ranking of the heat value according to the use condition of the home equipment of a user and the basis of predicting the preference of the user to the articles of the relevant equipment class. The family popular science articles are recommended by integrating the type of the equipment bound by the family of the user, the number of the bound equipment and the preference degree of the content of the general to-be-recommended article library. For example, recommendation of popular science articles is performed by integrating various factors such as the types of home appliances used in a user's home, the number of home appliances, the device binding time, and the popularity ranking of a popular science article library.
Optionally, fig. 3 is a flowchart of an algorithm for performing science popularization article recommendation based on a home device according to an alternative embodiment of the present invention. Specifically, the method comprises the following steps:
in step S302, a home device list is acquired. The intelligent network device has unique device identification, and after the user purchases the device, the user binds the purchased device, so that the device is associated with the user. And generating association to the relationship between the family id and the equipment mac according to the relationship between the user and the family and the binding relationship between the user and the equipment. Based on the association logic, data collection is carried out on the equipment list of the family, so that accurate popular science article recommendation is carried out on the family. Taking a family id as an example, the statistics of the related data are shown in table 1 below.
TABLE 1
And step S304, counting the family products, wherein the quantity of each type of equipment is an important influence factor recommended by the science popularization article related to the equipment. The greater the number of devices, the more likely the relevant articles for that type of device that the family needs to be concerned with. For example, if the home has 5 air-conditioning products, the higher the content demand of the home for the maintenance, cleaning, replacement, and the like of the air-conditioning equipment. By counting the existing devices in all families, the overall general view of the devices in the families of the user can be known, and a basis is provided for pushing related popular science articles of the user. And when the number of certain types of equipment in the family is the same, adding equipment binding time as a sequencing reference basis. Taking a family id as an example, the statistics of the related data are shown in table 2 below.
TABLE 2
It can be seen that in the home in the above example, the number of air conditioners is the largest, and other home appliances include a water heater and a water purifier. Because the water heater and the water purifier are the same and only one water heater and one water purifier are provided, the binding time is used as a sequencing basis. And recommending related popular science articles according to the types of the existing household appliances of the family.
Step S306, determining the popularity of the science popularization article library by the waiter-family to-be-recommended statistics (articles). And judging the popularity of the public to the related popular science articles according to different behaviors of the user on different content operations. The behavior of the user mainly comprises click-in, praise, collection, forwarding, comment and the like, different weights are given to different behaviors, and the popular preference degree of popular articles of each household appliance type is ordered accurately according to statistics and comprehensive calculation of behavior times of the user on a series of behaviors (such as click-in, praise, collection, forwarding, comment and the like) of the articles containing different labels. For example, taking air conditioner as an example, the article heat value ranking of air conditioner is shown in table 3 below.
TABLE 3
And S308, intelligently recommending content scores, sequencing according to the number of the categories of the equipment in the family of the user, and recommending the related types of popular science articles to the family.
It should be noted that, in the optional embodiment of the present invention, the ranking rule for the popular article recommendation includes ranking each article in the popular articles of the home appliance, selecting the first article in all the home appliance types to be preferentially recommended, and after the first article is recommended, performing the second recommendation, and so on. The household appliance science popularization type article (a household appliance science popularization article which is not a specific certain device, and the identifier of the following device type of '9999') is used as an article type to participate in the recommended ranking. The statistics of the relevant data recommended by the science popularization article are shown in table 4 below.
TABLE 4
In conclusion, by the above manner, the types and the number of the bound devices in the user family are used as the priority ordering conditions of the subjects of the popular science articles, and the relevant popular science articles are accurately recommended in a targeted manner; different requirements of the user on different devices are reflected by different devices in a family, so that the preference of the user on articles related to different device types can be more highlighted, and accurate popular science article recommendation can be performed. The method can also be used for ranking the heat values of the related articles based on the operation of the content containing the tag attribute in the user historical behaviors, marking the articles with different themes with related tags, collecting the historical behavior data of all users, finding the hot article content in the articles with different theme types, and recommending the families of the users, thereby greatly improving the degree of the user interest and enabling the users to accept the recommended articles more easily.
Further, the following technical effects are achieved through the mode:
1) the user experience is improved: the reasonable algorithm recommendation model is utilized, according to the types and the number of the devices bound by the family of the user, the content interested by the user and the possibly needed household appliance popular science knowledge can be accurately mastered, articles related to the family type positioning are recommended to the families of different users, thousands of people are achieved, the requirement of the user for solving the use problem of the household appliance is met, and the user has better use experience.
2) A more accurate algorithm pushes the result: based on the types and the number of the devices in the user family, the binding time of the devices and the preference sorting of the masses to different articles, algorithm design and calculation are carried out, and the pushing accuracy is improved.
3) More economic benefits are: the user preference is grasped to push the content interested by the user, so that the user is more willing to use the APP, the use desire of the user is improved, the trust degree of the user on the application is increased, the market acceptance is increased inevitably, and further the economic benefit can be improved.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solution of the present invention essentially or contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, or a network device) to execute the recommendation method of the content described in the embodiments of the present invention.
In this embodiment, a content recommendation apparatus is further provided, and the apparatus is used to implement the foregoing embodiments and preferred embodiments, and the description already made is omitted. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. Although the means described in the embodiments below are preferably implemented in software, an implementation in hardware, or a combination of software and hardware is also possible and contemplated.
Fig. 4 is a block diagram of a content recommendation apparatus according to an embodiment of the present invention, and as shown in fig. 4, the apparatus includes:
(1) a first determining module 42, configured to determine, when a display content request of a target object is received, device information corresponding to a target device having a binding relationship with the target object, and obtain a historical content display record recorded in the target device; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device;
(2) a second determining module 44, configured to determine, according to the device information and the historical content display record, preference information of the target object for content;
(3) and a recommending module 46, configured to determine, based on the preference information, a target recommendation value for the target object to accept different types of content, and recommend the target content to the target object according to the target recommendation value.
By the device, under the condition of receiving a display content request of a target object, determining equipment information corresponding to target equipment which has a binding relation with the target object, and acquiring a historical content display record recorded in the target equipment; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device; determining preference information of the target object for the content according to the equipment information and the historical content display record; and determining target recommendation values of different types of contents accepted by the target object based on the preference information, and recommending the target contents to the target object according to the target recommendation values. That is to say, the device information and the historical content display record of the target object are determined, the dynamic preference information of the target object is tracked, different types of content are displayed on the target terminal corresponding to the target device according to different recommendation values, and accordingly, the content is recommended to the target object, so that the problems that in the prior art, content recommendation adjustment cannot be performed according to the dynamically-changed preference of the target object, and the like can be solved, furthermore, the recommendable content corresponding to the target device is flexibly recommended by determining the dynamic recommendation value of the target object, rapid processing can be performed on variable target objects, and the use experience of users is improved.
Fig. 5 is a block diagram of another apparatus for recommending content according to an embodiment of the present invention, and as shown in fig. 5, the apparatus not only includes all the modules in fig. 4, but also includes: a screening module 40.
In an exemplary embodiment, the apparatus further includes: the screening module is used for acquiring identification information corresponding to a target object under the condition that the target object to be subjected to content recommendation exists in a target area; and screening out target equipment which has a binding relationship with the target object from the plurality of equipment in the target area according to the identification information.
In an exemplary embodiment, the second determining module is further configured to determine a first recommended value according to the device information; wherein the device information includes at least one of: the device type of the target device, the device number of the same type of target device, the binding time of the target device and the target object, and the content displayed by the target device correspondingly; determining a second recommendation value according to the historical content display record; and summarizing the first recommended value and the second recommended value to determine preference information of the target object for content.
In an exemplary embodiment, the second determining module is further configured to perform statistical processing on the device information according to a preset device classification; determining the type of the equipment currently used by the target object and the quantity of the equipment corresponding to each type of the equipment; and determining a first recommendation value for recommending the content corresponding to each equipment type according to the number of the equipment.
In an exemplary embodiment, the second determining module further includes: the comparison unit is used for sorting the first recommended value from at least a plurality of values based on the number of the devices; under the condition that the number of devices of two device types is the same, acquiring first binding time of a first device type and the target object, and acquiring second binding time of a second device type and the target object; and comparing the first binding time with the second binding time to determine the type of the equipment for preferentially recommending the content.
In an exemplary embodiment, the second determining module is further configured to analyze the historical content display record, to obtain a plurality of operation behaviors of the target object on the content displayed on the target device, determine weight values corresponding to the plurality of operation behaviors from a preset behavior weight list, and count the behavior times of each operation behavior; and comprehensively calculating the weight value and the behavior times to obtain a second recommended value corresponding to each operation behavior.
In an exemplary embodiment, the recommending module is further configured to match a device type corresponding to the first recommended value in the preference information with an operation behavior corresponding to the second recommended value; adding the first recommended value and the second recommended value in the matching result to determine a target recommended value for indicating content information recommendation; and sequentially recommending corresponding target content to the target object based on the target recommendation value, wherein the target content is a popular science article for guiding the use of the target device.
In the description of the present invention, it is to be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, and are only for convenience in describing the present invention and simplifying the description, but do not indicate or imply that the device or assembly referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus, should not be construed as limiting the present invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; the two components can be directly connected or indirectly connected through an intermediate medium, and the two components can be communicated with each other. When an element is referred to as being "secured to" or "disposed on" another element, it can be directly on the other element or intervening elements may also be present. When a component is referred to as being "connected" to another element, it can be directly connected to the other element or intervening elements may also be present. The specific meanings of the above terms in the present invention can be understood as specific cases by those skilled in the art.
It should be noted that the above modules may be implemented by software or hardware, and for the latter, the following may be implemented, but not limited to: the modules are all positioned in the same processor; alternatively, the modules are respectively located in different processors in any combination.
Embodiments of the present invention also provide a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
In an exemplary embodiment, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, under the condition of receiving a display content request of a target object, determining device information corresponding to a target device having a binding relationship with the target object, and acquiring a historical content display record recorded in the target device; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device;
s2, determining the preference information of the target object for the content according to the device information and the historical content display record;
s3, determining the target recommendation value of the target object for accepting different types of contents based on the preference information, and recommending the target contents to the target object according to the target recommendation value.
In an exemplary embodiment, in the present embodiment, the storage medium may include, but is not limited to: various media capable of storing computer programs, such as a usb disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic disk, or an optical disk.
Embodiments of the present invention also provide an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the above method embodiments.
In an exemplary embodiment, the electronic apparatus may further include a transmission device and an input/output device, wherein the transmission device is connected to the processor, and the input/output device is connected to the processor.
In an exemplary embodiment, in the present embodiment, the processor may be configured to execute the following steps by a computer program:
s1, under the condition of receiving a display content request of a target object, determining device information corresponding to a target device having a binding relationship with the target object, and acquiring a historical content display record recorded in the target device; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device;
s2, determining the preference information of the target object for the content according to the device information and the historical content display record;
s3, determining the target recommendation value of the target object for accepting different types of contents based on the preference information, and recommending the target contents to the target object according to the target recommendation value.
In an exemplary embodiment, for specific examples in this embodiment, reference may be made to the examples described in the above embodiments and optional implementation manners, and details of this embodiment are not described herein again.
It will be apparent to those skilled in the art that the various modules or steps of the invention described above may be implemented using a general purpose computing device, which may be centralized on a single computing device or distributed across a network of computing devices, and in one exemplary embodiment may be implemented using program code executable by a computing device, such that the steps shown and described may be executed by a computing device stored in a memory device and, in some cases, executed in a sequence different from that shown and described herein, or separately fabricated into individual integrated circuit modules, or multiple ones of them fabricated into a single integrated circuit module. Thus, the present invention is not limited to any specific combination of hardware and software.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (10)
1. A method for recommending a content, comprising:
under the condition of receiving a content display request of a target object, determining equipment information corresponding to target equipment which has a binding relationship with the target object, and acquiring a historical content display record recorded in the target equipment; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device;
determining preference information of the target object for the content according to the equipment information and the historical content display record;
and determining a target recommendation value of the target object for receiving different types of contents based on the preference information, and recommending the target content to the target object according to the target recommendation value.
2. The content recommendation method according to claim 1, wherein, in a case where a content display request of a target object is received, before determining device information corresponding to a target device having a binding relationship with the target object and acquiring a history content display record recorded in the target device, the method further comprises:
under the condition that a target object to be subjected to content recommendation exists in a target area, acquiring identification information corresponding to the target object;
and screening out target equipment which has a binding relationship with the target object from the plurality of equipment in the target area according to the identification information.
3. The content recommendation method according to claim 1, wherein determining preference information of the target object for content based on the device information and the historical content display record comprises:
determining a first recommended value according to the equipment information; wherein the device information includes at least one of: the device type of the target device, the device number of the same type of target device, the binding time of the target device and the target object, and the content displayed by the target device correspondingly;
determining a second recommendation value according to the historical content display record;
and summarizing the first recommended value and the second recommended value to determine preference information of the target object for content.
4. The method of recommending content according to claim 3, wherein determining a first recommendation value according to said device information comprises:
carrying out statistical processing on the equipment information according to preset equipment classification;
determining the type of the equipment currently used by the target object and the quantity of the equipment corresponding to each type of the equipment;
and determining a first recommendation value for recommending the content corresponding to each equipment type according to the number of the equipment.
5. The method of recommending content according to claim 4, wherein after determining a first recommendation value for recommending content by said number of devices, said method further comprises:
sorting the first recommended value from at least a plurality of values based on the number of the devices;
under the condition that the number of devices of two device types is the same, acquiring first binding time of a first device type and the target object, and acquiring second binding time of a second device type and the target object;
and comparing the first binding time with the second binding time to determine the type of the equipment for preferentially recommending the content.
6. The method of claim 3, wherein determining a second recommendation value based on the historical content display record comprises:
analyzing the historical content display record to obtain a plurality of operation behaviors of the target object on the content displayed on the target equipment;
determining weight values corresponding to the plurality of operation behaviors from a preset behavior weight list, and counting the behavior times of each operation behavior;
and comprehensively calculating the weight value and the behavior times to obtain a second recommended value corresponding to each operation behavior.
7. The content recommendation method according to claim 1, wherein determining recommendation values for the target object to accept different types of content based on the preference information, and recommending the target content to the target object according to the target recommendation values comprises:
matching the equipment type corresponding to the first recommended value in the preference information with the operation behavior corresponding to the second recommended value;
adding the first recommended value and the second recommended value in the matching result to determine a target recommended value for indicating content information recommendation;
and recommending corresponding target content to the target object in sequence based on the target recommendation value, wherein the target content is a popular science article for guiding the use of the target equipment.
8. A recommendation method device of content is characterized by comprising the following steps:
the device comprises a first determining module, a second determining module and a display module, wherein the first determining module is used for determining device information corresponding to target equipment which has a binding relation with a target object and acquiring a historical content display record recorded in the target equipment under the condition of receiving a display content request of the target object; the device information is information that a target object uses a plurality of target devices in a target area, and the historical content display record is an operation record of the target object on corresponding display content of the target device;
the second determination module is used for determining preference information of the target object for the content according to the equipment information and the historical content display record;
and the recommending module is used for determining target recommending values of different types of contents accepted by the target object based on the preference information and recommending the target contents to the target object according to the target recommending values.
9. A computer-readable storage medium, comprising a stored program, wherein the program when executed performs the method of any of claims 1 to 7.
10. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of claims 1 to 7 by means of the computer program.
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| CN202210462235.7A CN114880560A (en) | 2022-04-28 | 2022-04-28 | Content recommendation method and device, storage medium and electronic device |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115438270A (en) * | 2022-10-26 | 2022-12-06 | 深圳市信润富联数字科技有限公司 | Intelligent equipment information recommendation method, device, equipment and storage medium |
| CN115481315A (en) * | 2022-08-30 | 2022-12-16 | 海尔优家智能科技（北京）有限公司 | Method and device for determining recommendation information, storage medium and electronic device |
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115481315A (en) * | 2022-08-30 | 2022-12-16 | 海尔优家智能科技（北京）有限公司 | Method and device for determining recommendation information, storage medium and electronic device |
| WO2024045501A1 (en) * | 2022-08-30 | 2024-03-07 | 海尔优家智能科技（北京）有限公司 | Recommendation information determination method and apparatus, and storage medium and electronic apparatus |
| CN115481315B (en) * | 2022-08-30 | 2024-03-22 | 海尔优家智能科技（北京）有限公司 | Recommendation information determining method and device, storage medium and electronic device |
| CN115438270A (en) * | 2022-10-26 | 2022-12-06 | 深圳市信润富联数字科技有限公司 | Intelligent equipment information recommendation method, device, equipment and storage medium |
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