CN113327147A - Method and device for displaying article information - Google Patents
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- CN113327147A CN113327147A CN202010131360.0A CN202010131360A CN113327147A CN 113327147 A CN113327147 A CN 113327147A CN 202010131360 A CN202010131360 A CN 202010131360A CN 113327147 A CN113327147 A CN 113327147A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0641—Shopping interfaces
- G06Q30/0643—Graphical representation of items or shoppers
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/953—Querying, e.g. by the use of web search engines
- G06F16/9535—Search customisation based on user profiles and personalisation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
Abstract
The invention discloses a method and a device for displaying article information, and relates to the technical field of computers. One embodiment of the method comprises: acquiring user information, and determining a user portrait corresponding to the user information; wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user; determining an article to be displayed according to the user portrait; and displaying the article information of the article to be displayed on a page currently viewed by a user. The embodiment can provide corresponding personalized recommendations for different users, thereby being beneficial to improving the viscosity of the users.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for displaying article information.
Background
With the development of big data and internet, more and more users select an online shopping mode, and when online shopping is performed, the users generally browse multiple pages of an e-commerce platform to select items, such as a home page of the e-commerce platform, an item search result page, and the like.
At present, the e-commerce platform displays each page in a preset page display mode, so that when different users respectively view the same page, the viewed contents are the same. For example, when different users log in the home pages of the same e-commerce platform respectively, the contents viewed by the users are the same, and it is difficult to provide personalized recommendations for the users in this way.
Disclosure of Invention
In view of this, the method and the device for displaying item information provided in the embodiments of the present invention can display the item information corresponding to the user portrait on the page currently viewed by the user, so as to provide personalized recommendations corresponding to different users, thereby facilitating improvement of user viscosity.
To achieve the above object, according to an aspect of an embodiment of the present invention, there is provided a method of displaying information of an article.
The method for displaying the article information comprises the following steps:
acquiring user information, and determining a user portrait corresponding to the user information; wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user;
determining an article to be displayed according to the user portrait;
and displaying the article information of the article to be displayed on the current page.
Optionally, the determining an article to be displayed according to the user representation includes:
taking the user portrait as an input of an article prediction model, and determining the article to be displayed according to the output of the article prediction model; the item prediction model is obtained based on the user attributes, the historical behavior data of the user and the items corresponding to the historical behavior data of the user.
Optionally, the output of the item prediction model comprises: the output of the item prediction model comprises: item information of a plurality of items and item information of the plurality of items respectively correspond to matching degrees of the user images; the determining the item to be displayed according to the output of the item prediction model comprises:
and determining the article corresponding to the article information with the matching degree larger than the threshold value as the article to be displayed.
Optionally, the method further comprises:
and receiving user behavior data aiming at the current page with the article information, and optimizing the article prediction model according to the user behavior data.
Alternatively,
the item prediction model is generated based on a GBDT-CNN-DNN model.
Optionally, the user information is user login information, and displaying the article information of the article to be displayed on a current page includes:
and displaying the article information on a home page where the user logs in.
Optionally, the method further comprises:
and displaying the evaluation data of the to-be-displayed article.
Optionally, the method further comprises:
and generating an interaction area corresponding to the item information so as to display an interaction interface related to the item information and/or interaction information related to the item information by a plurality of users by utilizing the interaction area.
To achieve the above object, according to still another aspect of the embodiments of the present invention, there is provided an apparatus for displaying information on an article.
The device for displaying the article information in the embodiment of the invention comprises: the system comprises an image determining module, an information determining module and a display module; wherein the content of the first and second substances,
the portrait determining module is used for acquiring user information and determining a user portrait corresponding to the user information; wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user;
the information determining module is used for determining an article to be displayed according to the user portrait;
and the display module is used for displaying the article information of the article to be displayed on a page currently viewed by a user.
Optionally, the information determining module is configured to use the user representation as an input of an item prediction model, and determine the item to be displayed according to an output of the item prediction model; the item prediction model is obtained based on user attributes, historical behavior data of the user and item information corresponding to the historical behavior data of the user.
To achieve the above object, according to still another aspect of the embodiments of the present invention, there is provided an electronic device for displaying information of an article.
An electronic device for displaying article information according to an embodiment of the present invention includes: one or more processors; the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors realize the method for displaying the article information.
To achieve the above object, according to still another aspect of embodiments of the present invention, there is provided a computer-readable storage medium.
A computer-readable storage medium of an embodiment of the present invention stores thereon a computer program, which when executed by a processor implements a method of item information presentation of an embodiment of the present invention.
One embodiment of the above invention has the following advantages or benefits: the method comprises the steps of determining a corresponding user portrait according to user information, then determining an article to be displayed corresponding to the user portrait, and displaying the article information of the article to be displayed on a current page, so that personalized recommendation is provided for a user through the page displaying the article information corresponding to the user portrait, and the method is beneficial to improving the viscosity of the user.
Further effects of the above-mentioned non-conventional alternatives will be described below in connection with the embodiments.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a schematic diagram of the main steps of a method for displaying information on an item according to an embodiment of the present invention;
FIG. 2 is a block diagram of an item prediction model according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of the main steps of another method for displaying information on an item according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of the main steps of yet another method for item information display according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of the main modules of an article information display apparatus according to an embodiment of the present invention;
FIG. 6 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 7 is a schematic block diagram of a computer system suitable for use in implementing a terminal device or server of an embodiment of the invention.
Detailed Description
Exemplary embodiments of the present invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding, and which are to be considered as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
It should be noted that the embodiments of the present invention and the technical features of the embodiments may be combined with each other without conflict.
Fig. 1 is a schematic diagram of main steps of a method for displaying article information according to an embodiment of the invention.
As shown in fig. 1, a method for displaying article information according to an embodiment of the present invention mainly includes the following steps:
step S101: acquiring user information, and determining a user portrait corresponding to the user information; wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user.
The user information can be registration information or login information of the user, and before the user information is acquired, a user portrait can be constructed in advance according to user attributes and historical behavior data of the user. The user attributes can include population attributes, social attributes, family information, property information, user preference information, whether the user is a member or not and the like, the population attributes include gender, age, geographical position where the user is located and the like, the social attributes include marital status, occupation and the like, the family information includes the number of children and the age and the like, and the property information includes whether the vehicle exists or not and the like. The historical behavior data of the user comprises historical behaviors of clicking, browsing, paying attention, collecting, shopping cart adding, ordering and the like of the user history.
In order to improve the accuracy of constructing the user portrait, the user portrait may be constructed according to multi-dimensional user behavior data, for example, the user portrait may be constructed by using user behavior data of the user in different time periods, such as constructing the user portrait by combining real-time behavior data (behavior data of the user within 5min from the current time), short-term historical behavior data (behavior data of the user within 15 days from the current time), medium-term historical behavior data (behavior data of the user within 3 months from the current time), and long-term historical behavior data (behavior data of the user within 1 year from the current time), so that the constructed user portrait is more accurate.
Step S102: and determining an article to be displayed according to the user portrait.
When an article to be displayed corresponding to the user portrait is determined, the user portrait can be used as the input of an article prediction model, and the article to be displayed is determined according to the output of the article prediction model; the item prediction model is obtained based on the user attributes, the historical behavior data of the user and the items corresponding to the historical behavior data of the user.
Wherein the goods prediction model is generated based on the GBDT-CNN-DNN model, and the main architecture of the GBDT-CNN-DNN model can be as shown in FIG. 2. When training the article prediction model, the input features may be user attributes, historical behavior data of the user, and article information corresponding to the historical behavior data of the user. During model training, user attributes, historical behavior data of a user and sample data related to the historical behavior data of the user can be input into a model, low-order features are extracted through a Linear Part of a GBDT-CNN-DNN model, high-order features are extracted through a CNN Part and a DNN Part, the low-order features and the high-order features are spliced before entering an input layer, the spliced features are input into the input layer of the GBDT-CNN-DNN model, and then the features can be converted into mathematical vectors by the input layer so as to facilitate model training. In the model training process, the exponential weighting moving average is carried out on the sample data on the basis of the random gradient so as to carry out deviation correction on the momentum in a time step, and the learning rate of each element in the model parameters is readjusted through operation according to the elements, so that each element in the objective function independent variable has the learning rate of the element, the model is converged stably and quickly, and the model training efficiency is improved.
In addition, focal-loss is added into the loss function of the GBDT-CNN-DNN model, and the loss function of the goods prediction model is improved into a function shown in formula (1):
Lossfocal＝-αy2(1-y)γlogy………………(1)
wherein y represents the predicted probability value of the model, namely the result output by softmax of the GBDT-CNN-DNN model, and alpha and gamma are the modulation coefficients of focoal-loss. The modulation coefficient makes the GBDT-CNN-DNN model more focused on samples which are difficult to classify during training by reducing the weight of samples which are easy to classify. Alpha is used to balance the number of samples, and gamma is used to control the mining of samples that are difficult to classify, corresponding to a penalty term. When γ is 1, the cross entropy loss is obtained, and when γ is increased, the loss of samples which are easy to classify is reduced, and the loss of samples which are difficult to classify is relatively large.
In the prior art, during model training, activating functions such as Relu and Sigmoid are usually selected, and the division points of the activating functions are all 0, so that the model prediction accuracy is limited by adopting a fixed division point mode. In the embodiment of the invention, the activation function is improved, so that the segmentation point is determined by the data per se, and the model prediction accuracy is improved. Specifically, the improved activation function is shown in equation (2):
wherein m isiCharacterizing the predictive data, piCharacterizing the prediction probability, aiAnd characterizing preset parameters. Therefore, through the improved multi-classification self-adaptive nonlinear mapping, the segmentation points are adjusted according to the expectation and the variance of the data in MiniBatch, and compared with the method that Relu, sigmoid and the like adopt fixed segmentation points 0, the characteristics of the data set can be learned, so that the recall rate of the model in the verification set is improved, and the prediction accuracy rate of the model is further improved.
After the article prediction model is trained and before the article prediction model is brought online, the article prediction model needs to be tested, for example, when an article to be displayed corresponding to a user portrait is determined through a server and article information of the article to be displayed is displayed through a user terminal, joint debugging can be performed on the terminal and the server, and multi-angle testing can be performed on the effect of the model through a regression centralized example, so that the stable performance and the reliable effect of the article prediction model in the application process are ensured.
In addition, similar to the construction of the user image, the article prediction model may be trained according to multidimensional user behavior data, for example, the article prediction model may be trained by using user behavior data of the user in different time periods, for example, the article prediction model may be trained by combining real-time behavior data (behavior data of the user within 5min from the current time), short-term historical behavior data (behavior data of the user within 15 days from the current time), medium-term historical behavior data (behavior data of the user within 3 months from the current time), and long-term historical behavior data (behavior data of the user within 1 year from the current time), so that the trained article prediction model is more accurate.
Further, the output of the item prediction model includes: item information of a plurality of items and item information of the plurality of items respectively correspond to matching degrees of the user images; the determining the item to be displayed according to the output of the item prediction model comprises: and determining the article corresponding to the article information with the matching degree larger than the threshold value as the article to be displayed. Thus, the item information that matches the user figure best can be selected based on the score (matching degree) of each item information output by the item prediction model, thereby providing more accurate item recommendation to the user.
That is, the trained item prediction model may be used to determine the item information corresponding to the user image, and as shown in fig. 3, the item information display method according to the embodiment of the present invention may include the following steps S301 to S303:
step S301: user information is obtained and a user representation corresponding to the user information is determined.
Wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user.
Step S302: and taking the user image as an input of an article prediction model to obtain article information of a plurality of articles output by the article prediction model and matching degrees of the article information of the plurality of articles corresponding to the user image respectively.
The item prediction model is obtained based on the user attributes, the historical behavior data of the user and the items corresponding to the historical behavior data of the user.
Step S303: and determining the article corresponding to the article information with the matching degree larger than the threshold value as the article to be displayed, and displaying the article information of the determined article to be displayed on the page currently viewed by the user.
The article to be displayed is the article matched with the user portrait.
Step S103: and displaying the article information of the article to be displayed on the current page.
The article information may include information such as an image, a name, and/or a price of the article to be displayed, and may further include more detailed information such as a color and a shape of the article to be displayed. It is understood that the name of the article to be displayed may also include information such as the brand, color, shape, and model of the article, that is, detailed information such as the color and shape of the article to be displayed may be displayed by the name of the article to be displayed.
After the article to be displayed corresponding to the user portrait is determined, the article information of the article to be displayed can be displayed on a current page of the user, such as a retrieval result page and an article detail page which are currently viewed by the user. In a preferred embodiment of the present invention, the displaying the item information of the item to be displayed on the current page includes: and displaying the article information on a home page where the user logs in.
In this embodiment, the item information matched with the user portrait is displayed on a home page where the user logs in, for example, when the user logs in the e-commerce platform, the item information of the item matched with the user portrait of the user is displayed on the home page of the e-commerce platform, so that personalized recommendation is provided for the user at the first time, the interest of the user in the displayed item is improved, and the viscosity of the user is improved. According to this embodiment, as shown in fig. 4, the method for displaying article information provided by the present invention may include the following steps S401 to S403:
step S401: acquiring user information, and determining a user portrait corresponding to the user information; wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user.
Step S402: and determining an article to be displayed according to the user portrait.
Step S403: and displaying the article information of the article to be displayed on a home page which is logged by a user.
Besides displaying the item information to the user, the evaluation data of the item to be displayed can be displayed to the user, and the evaluation data can be provided by other users who have selected the item, for example, the evaluation data can be emotional tendency evaluation (such as good evaluation or bad evaluation) and experience evaluation (such as service attitude of a seller, preferential information of collocation, use hearts and the like in the selection process) provided by other users aiming at the item. From this, the evaluation data through waiting to demonstrate article are shown for the user can also look over corresponding evaluation data when looking over the article information of this article, and the user of being more convenient for fully understands article, and the user of being convenient for is favorable to improving user experience to the selection of article.
In addition, an interactive area corresponding to the item information can be generated, so that an interactive interface related to the item information and/or interactive information related to the item information of a plurality of users can be displayed by utilizing the interactive area.
For example, a corresponding interactive interface may be provided according to the determined type of the article to be displayed, so that the user may perform an interactive behavior related to the article information through the interactive interface, and if the type corresponding to the article information is a game type, that is, it indicates that the user is interested in the game type article, the interactive interface at this time may be a corresponding game entry, so that the user may enter a mini game through the interactive interface, that is, perform an interactive behavior related to the article information. In addition, interactive information related to the article information can be displayed, if the determined article information is the article information related to the pet, the related information about the pet published by other users can be displayed through the interactive area, so that a plurality of users can publish and view the interactive information related to the article information through the interactive area. Furthermore, corresponding rewards can be provided for the user according to the interaction behavior of the user, such as coupons provided when the game is completed or items are purchased at preferential price, or coupons provided for the user with active published interaction information, and the like.
Furthermore, user behavior data aiming at the current page with the article information displayed can be received, and the article prediction model is optimized according to the user behavior data. That is to say, after the article information of the article to be displayed corresponding to the user portrait is displayed on the current page, the user behavior data of the user on the current page can be collected, that is, the feedback of the user on the recommended article information is obtained, and then the article prediction model is further optimized according to the user behavior data, so that the prediction accuracy of the article prediction model is further improved, and further more accurate personalized recommendation is provided for the user.
Therefore, the object information corresponding to the user portrait, the related interactive interface, the interactive information and the like are displayed on the current page viewed by the user, such as the home page of the E-commerce platform, so that the corresponding page display information can be provided for the user according to the interest points of the user, for example, for the user who likes pets, the home page starting is various kitten dogs, for the user who likes learning artificial intelligence, the home page starting is rich deep learning or python tutorials, and for the user who likes eating snacks, the home page starting is various classical snacks, so that personalized recommendation is provided for the user, and the viscosity of the user is improved.
Fig. 5 is a schematic diagram of main modules of an article information display device according to an embodiment of the invention.
As shown in fig. 5, an apparatus 500 for displaying information of an article according to an embodiment of the present invention includes: a portrait determination module 501, an information determination module 502 and a presentation module 502; wherein the content of the first and second substances,
the portrait determining module 501 is configured to obtain user information and determine a user portrait corresponding to the user information; wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user;
the information determining module 502 is configured to determine an article to be displayed according to the user representation;
the display module 503 is configured to display the item information of the item to be displayed on a page currently viewed by the user.
In an embodiment of the present invention, the information determining module 502 is configured to use the user representation as an input of an item prediction model, and determine the item to be displayed according to an output of the item prediction model; the item prediction model is obtained based on the user attributes, the historical behavior data of the user and the items corresponding to the historical behavior data of the user.
In one embodiment of the invention, the output of the item prediction model comprises: item information of a plurality of items and item information of the plurality of items respectively correspond to matching degrees of the user images; the information determining module 502 is configured to determine, as the article to be displayed, an article corresponding to the article information of which the matching degree is greater than the threshold.
In an embodiment of the present invention, the information determining module 502 is further configured to receive user behavior data for the current page showing the item information, and optimize the item prediction model according to the user behavior data.
In an embodiment of the present invention, the displaying module 503 is configured to display the item information on a home page of a user login when the user information is user login information.
According to the device for displaying the article information, the corresponding user portrait is determined according to the user information, then the article to be displayed corresponding to the user portrait is determined, the article information of the article to be displayed is displayed on the current page, and personalized recommendation is provided for the user through the page displaying the article information corresponding to the user portrait, so that the viscosity of the user is improved.
Fig. 6 illustrates an exemplary system architecture 600 of a method of item information presentation or an apparatus of item information presentation to which embodiments of the present invention may be applied.
As shown in fig. 6, the system architecture 600 may include terminal devices 601, 602, 603, a network 604, and a server 605. The network 604 serves to provide a medium for communication links between the terminal devices 601, 602, 603 and the server 605. Network 604 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use the terminal devices 601, 602, 603 to interact with the server 605 via the network 604 to receive or send messages or the like. Various communication client applications, such as shopping applications, web browser applications, search applications, instant messaging tools, mailbox clients, social platform software, and the like, may be installed on the terminal devices 601, 602, and 603.
The terminal devices 601, 602, 603 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 605 may be a server that provides various services, such as a background management server that supports shopping websites browsed by users using the terminal devices 601, 602, and 603. The background management server may analyze and perform other processing on the received data such as the product information query request, and feed back a processing result (e.g., target push information and product information) to the terminal device.
It should be noted that the method for displaying the item information provided by the embodiment of the present invention is generally executed by the server 605, and accordingly, the apparatus for displaying the item information is generally disposed in the server 605.
It should be understood that the number of terminal devices, networks, and servers in fig. 6 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 7, shown is a block diagram of a computer system 700 suitable for use with a terminal device implementing an embodiment of the present invention. The terminal device shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 7, the computer system 700 includes a Central Processing Unit (CPU)701, which can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage section 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the system 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
The following components are connected to the I/O interface 705: an input portion 706 including a keyboard, a mouse, and the like; an output section 707 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 708 including a hard disk and the like; and a communication section 709 including a network interface card such as a LAN card, a modem, or the like. The communication section 709 performs communication processing via a network such as the internet. A drive 710 is also connected to the I/O interface 705 as needed. A removable medium 711 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 710 as necessary, so that a computer program read out therefrom is mounted into the storage section 708 as necessary.
In particular, according to the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication section 709, and/or installed from the removable medium 711. The computer program performs the above-described functions defined in the system of the present invention when executed by the Central Processing Unit (CPU) 701.
It should be noted that the computer readable medium shown in the present invention can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present invention, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present invention, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams or flowchart illustration, and combinations of blocks in the block diagrams or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a representation determination module, an information determination module, and a presentation module. Where the names of these modules do not in some cases constitute a limitation on the module itself, for example, the representation-determining module may also be described as a "module that determines a user representation corresponding to user information".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium carries one or more programs which, when executed by a device, cause the device to comprise: acquiring user information, and determining a user portrait corresponding to the user information; wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user; determining an article to be displayed according to the user portrait; and displaying the article information of the article to be displayed on the current page.
According to the technical scheme of the embodiment of the invention, the corresponding user portrait is determined according to the user information, then the article to be displayed corresponding to the user portrait is determined, and the article information of the article to be displayed is displayed on the current page, so that personalized recommendation is provided for the user through the page displaying the article information corresponding to the user portrait, and the improvement of the user viscosity is facilitated.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (12)
1. A method of displaying information on an item, comprising:
acquiring user information, and determining a user portrait corresponding to the user information; wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user;
determining an article to be displayed according to the user portrait;
and displaying the article information of the article to be displayed on the current page.
2. The method of claim 1, wherein said determining an item to be displayed from said user representation comprises:
taking the user portrait as an input of an article prediction model, and determining the article to be displayed according to the output of the article prediction model; the item prediction model is obtained based on the user attributes, the historical behavior data of the user and the items corresponding to the historical behavior data of the user.
3. The method of claim 2, wherein the output of the item prediction model comprises: item information of a plurality of items and item information of the plurality of items respectively correspond to matching degrees of the user images; the determining the item to be displayed according to the output of the item prediction model comprises:
and determining the article corresponding to the article information with the matching degree larger than the threshold value as the article to be displayed.
4. The method of claim 2, further comprising:
and receiving user behavior data aiming at the current page with the article information, and optimizing the article prediction model according to the user behavior data.
5. The method according to any one of claims 2 to 4,
the item prediction model is generated based on a GBDT-CNN-DNN model.
6. The method according to claim 1, wherein the user information is user login information, and the displaying of the item information of the item to be displayed on the current page comprises:
and displaying the article information on a home page where the user logs in.
7. The method of claim 1, further comprising:
and displaying the evaluation data of the to-be-displayed article.
8. The method of claim 1, further comprising:
and generating an interaction area corresponding to the item information so as to display an interaction interface related to the item information and/or interaction information related to the item information by a plurality of users by utilizing the interaction area.
9. An article information display device, comprising: the system comprises an image determining module, an information determining module and a display module; wherein the content of the first and second substances,
the portrait determining module is used for acquiring user information and determining a user portrait corresponding to the user information; wherein the user representation is derived based on user attributes corresponding to the user information and/or historical behavior data of the user;
the information determining module is used for determining an article to be displayed according to the user portrait;
the display module is used for displaying the article information of the article to be displayed on a current page.
10. The apparatus of claim 9,
the information determining module is used for taking the user portrait as the input of an article prediction model and determining the article to be displayed according to the output of the article prediction model; the item prediction model is obtained based on the user attributes, the historical behavior data of the user and the items corresponding to the historical behavior data of the user.
11. An electronic device for displaying information on an article, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-8.
12. A computer-readable medium, on which a computer program is stored, which, when being executed by a processor, carries out the method according to any one of claims 1-8.
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010131360.0A CN113327147A (en) | 2020-02-28 | 2020-02-28 | Method and device for displaying article information |
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| CN202010131360.0A CN113327147A (en) | 2020-02-28 | 2020-02-28 | Method and device for displaying article information |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113822745A (en) * | 2021-09-28 | 2021-12-21 | 北京沃东天骏信息技术有限公司 | Article display method and device |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113822745A (en) * | 2021-09-28 | 2021-12-21 | 北京沃东天骏信息技术有限公司 | Article display method and device |
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Application publication date: 20210831 |