CN111143662B - Content recommendation method, device and computer storage medium - Google Patents
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Abstract
Embodiments of the present disclosure relate to methods, apparatuses, and computer storage media for content recommendation. In one embodiment, a method of content recommendation is provided. The method comprises the following steps: in response to receiving a request for a predetermined number of content, determining identity information of a user associated with the request; determining, based on the identity information, a first set of content associated with the user, the first set of content comprising at least one item of content not pushed to the user; determining whether a first number of content in the first set of content reaches a predetermined number; determining a second set of content unread by the user from among the pushed sets of content that have been pushed to the user in response to the first number not reaching the predetermined number; and pushing the first set of content and the second set of content to the user.
Description
Technical Field
Embodiments of the present disclosure relate to the field of the internet, and more particularly, to a method, apparatus, and computer storage medium for content recommendation.
Background
With the development of internet technology, the internet is capable of providing more and more network services to users. For example, a user may browse videos, listen to music, read, shop, etc. through the internet. On the internet platform, a user can search for own desired contents through a search function. Meanwhile, in order to facilitate the user to acquire information, the Internet platform can also actively recommend content to the user. With the explosive growth of information on the internet, how to recommend content more in line with the needs of users to users has become a current focus of attention.
Disclosure of Invention
Embodiments of the present disclosure provide a scheme for content recommendation to a user.
According to a first aspect of the present disclosure, a method of content recommendation is presented. The method comprises the following steps: in response to receiving a request for a predetermined number of content, determining identity information of a user associated with the request; determining, based on the identity information, a first set of content associated with the user, the first set of content comprising at least one item of content not pushed to the user; determining whether a first number of content in the first set of content reaches a predetermined number; determining a second set of content unread by the user from among the pushed sets of content that have been pushed to the user in response to the first number not reaching the predetermined number; and pushing the first set of content and the second set of content to the user.
According to a second aspect of the present disclosure, an apparatus for content recommendation is presented. The apparatus includes: at least one processing unit; at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions when executed by the at least one processing unit cause the apparatus to perform actions comprising: in response to receiving a request for a predetermined number of content, determining identity information of a user associated with the request; determining, based on the identity information, a first set of content associated with the user, the first set of content comprising at least one item of content not pushed to the user; determining whether a first number of content in the first set of content reaches a predetermined number; determining a second set of content unread by the user from among the pushed sets of content that have been pushed to the user in response to the first number not reaching the predetermined number; and pushing the first set of content and the second set of content to the user.
In a third aspect of the present disclosure, a computer storage medium is provided. The computer storage medium has computer readable program instructions stored thereon for performing the method according to the first aspect.
The summary is provided to introduce a selection of concepts in a simplified form that are further described below in the detailed description. This summary is not intended to identify key features or essential features of the disclosure, nor is it intended to be used to limit the scope of the disclosure.
Drawings
The foregoing and other objects, features and advantages of the disclosure will be apparent from the following more particular descriptions of exemplary embodiments of the disclosure as illustrated in the accompanying drawings wherein like reference numbers generally represent like parts throughout the exemplary embodiments of the disclosure.
FIG. 1 illustrates a block diagram of a computing environment in which implementations of the present disclosure can be implemented;
FIG. 2 illustrates a flow chart of a method of content recommendation according to an embodiment of the present disclosure;
FIG. 3 illustrates a flowchart of a method of determining a first set of content associated with a user, according to an embodiment of the present disclosure;
FIG. 4 illustrates a flowchart of a method of determining a second set of content that is unread by a user from a pushed set of content that has been pushed to the user, according to an embodiment of the present disclosure;
FIG. 5 illustrates a flowchart of a method of determining a second set of content that is not read by a user from a pushed set of content that has been pushed to the user, according to another embodiment of the present disclosure;
FIG. 6 illustrates a flowchart of a method of determining a third set of content from a first set of content, according to an embodiment of the present disclosure;
FIG. 7 illustrates a flowchart of a method of determining a third set of content from a first set of content according to another embodiment of the present disclosure; and
fig. 8 illustrates a schematic block diagram of an example device that may be used to implement embodiments of the present disclosure.
Detailed Description
Preferred embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While the preferred embodiments of the present disclosure are illustrated in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
The term "comprising" and variations thereof as used herein means open ended, i.e., "including but not limited to. The term "or" means "and/or" unless specifically stated otherwise. The term "based on" means "based at least in part on". The terms "one example embodiment" and "one embodiment" mean "at least one example embodiment. The term "another embodiment" means "at least one additional embodiment". The terms "first," "second," and the like, may refer to different or the same object. Other explicit and implicit definitions are also possible below.
As discussed above, in order to prevent repeated recommendation of the same content to users during content pushing to users, existing content recommendation generally requires maintaining a buffer pool of a moderate size for each user to store data to be recommended, then cleaning up and adding data to the buffer pool for a certain period of time, and separately maintaining a data table for users that has been browsed for recommended data, thereby performing a deduplication operation for the recommended content.
In addition, the existing content recommendation often does not determine the actual operation of the user, and even if the user does not actually read the content, the content recommended to the user is not recommended to the user again, and the content may be desired to be acquired by the user. Therefore, the recommendation mode leads to omission of related content by the user, and accordingly usage experience of information recommendation by the user is reduced.
According to embodiments of the present disclosure, a scheme is provided for effectively deduplicating user content recommendations and reducing the omission of unread content. In this scheme: first, receiving a request for a predetermined number of contents, determining identity information of a user associated with the request; subsequently, determining a first set of content associated with the user based on the identity information, the first set of content comprising at least one item of content not pushed to the user; and determining whether a first number of content in the first set of content reaches a predetermined number; if the first number does not reach the predetermined number, determining a second set of content unread by the user from the pushed set of content that has been pushed to the user; and finally, pushing the first content set and the second content set to the user.
By adopting the scheme disclosed by the invention, the latest content which is not pushed before can be recommended to the user preferentially, and when the number of the latest content is smaller, the content which is pushed before but not read by the user is pushed to the user. By the method, the latest content can be pushed to the user in time, and missing of unread content by the user can be reduced.
The basic principles and several example implementations of the present disclosure are described below with reference to the accompanying drawings.
FIG. 1 illustrates a block diagram of a computing environment 100 in which implementations of the present disclosure can be implemented. It should be understood that the computing environment 100 illustrated in fig. 1 is only exemplary and should not be taken as limiting the functionality and scope of the implementations described in this disclosure. As shown in fig. 1, computing environment 100 includes user device 120, server 130, and storage 140, where user device 120 may interact with user 110.
In some embodiments, user 110 may request content from server 130 via user device 120. For example, user device 120 may be provided with an application associated with content in server 130, and user 110 may initiate a request for content to server 130 based on a particular operation on the application (e.g., newly opening the application, refreshing application content, switching application columns, etc.). In some embodiments, the request may specify the number of content that needs to be requested. For example, this number may depend on the number of bars in the first screen of the user device 120 that can present content. In some embodiments, the server 130 may also actively push content to the user device 120. For example, the server 130 may push a predetermined number of content to the user device 120 on a regular basis.
In some embodiments, in response to the server 130 receiving a request for content from the user 110, or when the server 130 determines that active pushing of content to the user device 120 is required, the server 130 may obtain a set of content to be pushed to the user 110 from the storage 140 and send the set of content to the user device 120. Examples of such content include, but are not limited to: news, advertising, music, video, merchandise, and applications, among others. In some embodiments, the storage device 140 may be independent of the server 130 or may be inherited in the server 130.
In some embodiments, the user device 120 may receive the set of content sent by the server 130 and present the set of content to the user 110. In some embodiments, the user device 120 is, for example, any type of mobile terminal, fixed terminal, or portable terminal, including a mobile handset, multimedia computer, multimedia tablet, internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal Communication System (PCS) device, personal navigation device, personal Digital Assistants (PDAs), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof. It is also contemplated that the user device 120 can support any type of interface to the user (such as "wearable" circuitry, etc.).
In some embodiments, the user 110 may operate on the set of content that may be pushed through the user device 120, and the user device 120 may record the operation performed by the user 110 and send the operation information to the server 130. The server 130 may store the operational information in association with the user 110. For example, using news as an example, the user device 120 may record whether the user 110 clicked on a particular news, forwarded a particular news, collected a particular news, and so on.
A method for content recommendation according to an embodiment of the present disclosure will be described below in connection with fig. 2-7. Fig. 2 illustrates a flow chart of a method 200 of content recommendation according to an embodiment of the present disclosure. The method 200 may be implemented by the server 130 in fig. 1 to push content required by the user 110 to the user device 120.
In block 210, in response to receiving the request for the predetermined number of content, the server 130 determines identity information of the user 110 associated with the request. In some embodiments, the server 130 receives the request from the user device 120, which may include identity information of the user 110 to which the user device 120 is logged. In some embodiments, the request may be generated in response to the server 130 desiring to push content to the user device 120 on a timed basis, at which time the server 130 may determine identity information of the user 110 logged in the user device 120 to which the content is to be pushed. In some embodiments, the identity information of the user 110 may be any item or items of information capable of uniquely identifying the user's identity, examples of which include, but are not limited to, a user name, a cell phone number, an identification card number, an IMEI number of the user device 120 associated with the user 110, and the like.
Based on the identity information, the server device 130 determines a set of content associated with the user 110 (hereinafter referred to as a first set of content for ease of description) that includes at least one item of content that is not pushed to the user 110, at block 220. In some embodiments, the content stored in storage 140 has an associated content identifier. In some embodiments, the content identifier may be associated with a publication time such that the more recently published content has a larger content identifier. In some embodiments, the server 130 may maintain a first set of content for each user 110 that is made up of content that is not pushed to the user 110 and store it in the storage 140.
The operation of how the first set of content associated with the user is determined based on the identity information will be described below in connection with fig. 3. Fig. 3 illustrates a flowchart of a method 300 of determining a first set of content associated with a user, according to an embodiment of the present disclosure.
At block 310, the server 130 obtains a set of content that was not pushed to the user 110 in the previous push (hereinafter referred to as a fourth set of content for convenience of description). In some embodiments, a single push may not be able to push all of the un-pushed content to the user 110 because of the limited number of content that can be pushed to the user 110 at a time. In some embodiments, the server 130 may record content that has not been pushed to the user 110 in a previous push. In some embodiments, server 130 may mark content that has been pushed to user 110 as pushed.
In some embodiments, the server 130 may record content that is not pushed to the users 110 by maintaining at least one content identifier interval for each user 110. In some embodiments, the content identifier interval may be represented as: [ Start content identifier, end content identifier ]. As previously described, the content identifier is associated with the release time of the content, and thus the interval may identify one or more items of content that are not pushed to the user 110. In this manner, the server 130 need not maintain a push state for each user for each content, rather, the server 130 can identify content that is not pushed to the user 110 based on multiple content identifier intervals, thereby saving the required storage overhead.
At block 320, the server 130 determines the maximum content identifier that has been pushed to the user 110 in the previous push. In some embodiments, the server 130 may store for each user 110 the maximum content identifier last_max_id that has been pushed to that user 110 in the previous push. Based on the maximum content identifier, server 130 may determine the most recent content that has been pushed to user 110.
Based on the maximum content identifier and the latest content identifier, the server 130 determines a content set (hereinafter referred to as a fifth content set for convenience of description) at block 330. In some embodiments, since new content is generated after the previous push, the server 130 may determine the content of the update publication relative to the previous push based on the maximum content identifier last_max_id previously pushed to the user 110 and the content identifier last_max_id of the current latest content. In some embodiments, a fifth set of content, which is made up of content that is newly published relative to the previous push, may be identified by a content identifier interval [ last_max_id+1, last_max_id ].
At block 340, the server 130 combines the fourth set of content and the fifth set of content to obtain the first set of content. As described above, the fourth content set includes content that was not pushed to the user in the previous push, and the fifth content set includes content that was updated for distribution relative to the previous push, so that the first content set combined from the fourth content set and the fifth content set includes all content that was not pushed to the user 110 in the present push.
In some embodiments, the content identifiers may be discontinuous, i.e., some content identifiers may be invalid. In determining the first content set, the server 130 may determine the validity of each content identifier in the content identifier section. For example, the server 130 may traverse each content identifier in the content identifier section and determine whether there is content corresponding to the content identifier.
With continued reference to fig. 2, at block 230, the server 130 determines whether the first number of content in the first set of content reaches a predetermined number. If not, the method 200 proceeds to block 240, i.e., in response to the first number not reaching the predetermined number, the server 130 determines a set of content not read by the user 110 (hereinafter referred to as a second set of content for convenience of description) from the set of pushed content that has been pushed to the user 110. As described above, the server 130 may receive operations performed by the user 110 from the user device 120 and store the operation information in association with the user 110. In some embodiments, server 130 may tag each content according to the operational information of user 110, e.g., as "user read" or "user not read". In some embodiments, server 130 may similarly maintain for user 110 a content identifier interval that has been pushed to the user but not read by the user. Taking news as an example, when user 110 does not click on a particular news, server 130 may mark the news as "user unread". In contrast, when the user 110 performs operations such as click-to-open, forwarding, or commenting on the content, the server 130 may mark the news as "user read".
In some embodiments, server 130 may also consider whether such content meets the user's preferences when pushing twice from information that has been pushed to user 110 but not read by the user. The operation of determining the second set of content that the user has not read from the pushed set of content that has been pushed to the user is described in detail below in connection with fig. 4. Fig. 4 illustrates a flowchart of a method 400 of determining a second set of content not read by a user from a pushed set of content that has been pushed to the user, according to an embodiment of the present disclosure.
Based on the identity information of the user 110, the server 130 determines attribute information and/or preference information of the user 110 at block 410. In some embodiments, the attribute information of the user 110 may be personal information of the user 110, such as gender, age, hobbies, ethnicity, academic, hometown, frequent place, etc. of the user 110. In some embodiments, this attribute information may be filled in when user 110 registers an account and stored in storage 140. In some embodiments, the preference information of the user 110 may be preferences filled out by the user 110, e.g., the user 110 may select a music type, a movie type, a news type, or the like of interest when registering an account. In some embodiments, server 130 may determine preference information for user 110 based on an analysis of the operational behavior of user 110. For example, server 130 may determine that user 110 is interested in a particular type of content based on user 110 browsing that type of content beyond a predetermined threshold, or server 130 may determine that user 110 likes/dislikes a piece of content based on user 110 praying or masking the piece of content. It should be appreciated that other suitable techniques may also be employed to determine preference information for the user 110 based on the operational behavior of the user 110.
Based on the attribute information and/or the preference information, the server 130 determines a degree of association of each content in the set of pushed content with the user 110 at block 420. In some embodiments, server 130 may also add one or more content tags to each content, such as the category of the content, the region of the content, and so on. Based on the attribute information and/or preference information of the user 110 and the one or more tags of the content, the server 130 may determine a degree of association of the user 110 with the content. For example, when the tag of the content matches the preference information of the user 110, the content may be deemed to have a higher relevancy score; as another example, the content may have a higher relevancy score when the content is associated with the usual residence of the user 110. It should be appreciated that techniques known in the art (e.g., calculating inter-vector distances, etc.) may be employed to calculate the degree of association based on the attribute information/preference information of the user 110 and one or more tags of the content, and are not described in detail herein.
At block 430, the server 130 determines a second set of content from the pushed set of content such that the degree of association of the content in the second set of content with the user 110 is greater than a predetermined first degree of association threshold. In some embodiments, server 130 may filter out content having a relevance below the first relevance threshold based on the relevance of the content in the pushed content set, such that content that is more relevant to the attributes/preferences of user 110 is selected from only content that has been pushed to user 110 but is unread by the user.
In some embodiments, server 130 may also employ method 500 shown in fig. 5 to determine a second set of content that is not read by the user from the pushed set of content that has been pushed to the user.
Based on the identity information of the user 110, the server 130 determines attribute information and/or preference information of the user 110, block 510. Based on the attribute information and/or the preference information, the server 130 determines a degree of association of each content in the set of pushed content with the user 110 at block 520. It should be appreciated that the operations of blocks 510 and 520 may be performed as described with reference to the operations of blocks 410 and 420, and are not described in detail herein.
At block 530, based on the distribution time of each content, server 130 determines the freshness of each content. In some embodiments, the freshness of each content may represent the difference between the release time of the content to the time when the present push was performed. For example, when a piece of content has been released for 24 hours, the freshness of the content at the time of the present push may be represented as-24.
At block 540, the server 130 determines a recommendation level for each content based on the association level of each content with the user 110 and the freshness of each content. In some embodiments, server 130 may normalize the relevance and recommendation of each content. In some embodiments, server 130 may also assign different weights to the relevance and freshness, and calculate a weighted sum of the relevance and freshness, resulting in a recommendation for each content.
At block 550, the server 130 determines a second set of content from the pushed set of content such that the recommendation of content in the second set of content is greater than a predetermined first recommendation threshold. In this manner, server 130 may consider both the relevance of the content to the user's attributes/preferences and the time of release of the content, thereby avoiding pushing some of the overly stale content to user 110. In some embodiments, server 130 may also exclude content having one of relevance or freshness below a particular threshold first, thereby ensuring that user 110 is not pushed with content of a masked category or too old content.
With continued reference to fig. 2, at block 250, the server 130 pushes the first set of content and the second set of content to the user 110. In some embodiments, the content identifier interval for each user 110 may be modified as content is pushed so that the server 130 records content that is not pushed to that user 110 in real-time. For example, after pushing all content in one content identifier space of the user 110 to the user 110, deleting the content identifier section; alternatively, if only a portion of the content is pushed to the user 110 in one content identifier section of the user 110, the content identifier section is modified to indicate only content that is not pushed to the user 110.
On the other hand, if it is determined at block 230 that the first number reaches the predetermined number, the method 200 proceeds to block 260, i.e., responsive to the first number reaching the predetermined number, the server 130 determines a third set of content from the first set of content, the third set of content having the predetermined number of content.
The operation of determining the third set of content from the first set of content will be described in detail below in connection with fig. 6. Fig. 6 illustrates a flowchart of a method 600 of determining a third set of content from a first set of content, according to an embodiment of the disclosure.
Based on the identity information of the user 110, the server 130 determines attribute information and/or preference information of the user 110, block 610. Based on the attribute information and/or the preference information, the server 130 determines a degree of association of each content in the first set of content with the user 110 at block 620. It should be appreciated that attribute information and/or preference information for the user 110 may be determined as described with respect to similar operations of blocks 410 and 420 to determine the relevance of each content in the first set of content to the user 110.
At block 630, the server 130 determines a set of content (hereinafter referred to as a third set of content for convenience of description) from the first set of content such that the degree of association of the content in the third set of content with the user 110 is greater than a predetermined second degree of association threshold. In some embodiments, server 130 may filter out content having a relevance below a second relevance threshold based on the relevance of the content in the first set of content, such that content from the first set of content is selected that is more relevant to the attributes/preferences of user 110.
In some embodiments, the server 130 may also employ the method 700 shown in fig. 7 to determine a third set of content from the first set of content.
Based on the identity information of the user, server 130 determines attribute information and/or preference information for user 110 at block 710. Based on the attribute information and/or the preference information, the server 130 determines a degree of association of each content in the first set of content with the user 110 at block 720. At block 730, the push information platform 130 determines the freshness of each content based on the time of release of each content. At block 740, the server 130 determines a recommendation level for each content based on the association level of each content with the user 110 and the freshness of each content. It should be appreciated that attribute information and/or preference information for the user 110 may be determined in accordance with similar operations as described with respect to blocks 510, 520, 530, and 540 to determine the relevance of each content in the first set of content to the user 110, and to determine the freshness of each content in the first set of content, and to determine the recommendation of each content in the first set of content.
At block 750, a third set of content is determined from the first set of content such that a recommendation level of content in the third set of content is greater than a predetermined second recommendation level threshold. In this manner, server 130 may consider both the relevance of the content in the first set of content to the user's attributes/preferences and the time of release of the content in the first set of content, so that the most up-to-date content that is more relevant to the user's attributes/preferences may be pushed to user 110.
Based on the above content recommendation manner, embodiments of the present disclosure can store at least one content identifier section for each user, so that a buffer pool of recommended content and a recommended content data table can be not required to be maintained separately for each user, thereby alleviating the storage burden of the server. In addition, the content which is pushed to the user but not actually read by the user is pushed to the user again, so that the user can be ensured to effectively acquire the related content, and the omission of the user on the unread content is reduced.
Fig. 8 illustrates a schematic block diagram of an example device 800 that may be used to implement embodiments of the present disclosure. For example, the push information platform 130 in the example environment 100 shown in fig. 1 may be implemented by the device 800. As shown, the device 800 includes a Central Processing Unit (CPU) 801 that can perform various suitable actions and processes in accordance with computer program instructions stored in a Read Only Memory (ROM) 802 or loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The CPU 801, ROM 802, and RAM 803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to the bus 804.
Various components in device 800 are connected to I/O interface 805, including: an input unit 806 such as a keyboard, mouse, etc.; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, etc.; and a communication unit 809, such as a network card, modem, wireless communication transceiver, or the like. The communication unit 809 allows the device 800 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.
The various processes and treatments described above, such as method 200, method 300, method 400, method 500, method 600, and/or method 700, may be performed by processing unit 801. For example, in some embodiments, method 200, method 300, method 400, method 500, method 600, and/or method 700 may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 800 via ROM 802 and/or communication unit 809. When the computer program is loaded into RAM 803 and executed by CPU 801, one or more actions of method 200, method 300, method 400, method 500, method 600, and/or method 700 described above may be performed.
The present disclosure may be methods, apparatus, systems, and/or computer program products. The computer program product may include a computer readable storage medium having computer readable program instructions embodied thereon for performing aspects of the present disclosure.
The computer readable storage medium may be a tangible device that can hold and store instructions for use by an instruction execution device. The computer readable storage medium may be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of the computer-readable storage medium would include the following: portable computer disks, hard disks, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static Random Access Memory (SRAM), portable compact disk read-only memory (CD-ROM), digital Versatile Disks (DVD), memory sticks, floppy disks, mechanical coding devices, punch cards or in-groove structures such as punch cards or grooves having instructions stored thereon, and any suitable combination of the foregoing. Computer-readable storage media, as used herein, are not to be construed as transitory signals per se, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through waveguides or other transmission media (e.g., optical pulses through fiber optic cables), or electrical signals transmitted through wires.
The computer readable program instructions described herein may be downloaded from a computer readable storage medium to a respective computing/processing device or to an external computer or external storage device over a network, such as the internet, a local area network, a wide area network, and/or a wireless network. The network may include copper transmission cables, fiber optic transmissions, wireless transmissions, routers, firewalls, switches, gateway computers and/or edge servers. The network interface card or network interface in each computing/processing device receives computer readable program instructions from the network and forwards the computer readable program instructions for storage in a computer readable storage medium in the respective computing/processing device.
Computer program instructions for performing the operations of the present disclosure can be assembly instructions, instruction Set Architecture (ISA) instructions, machine-related instructions, microcode, firmware instructions, state setting data, or source or object code written in any combination of one or more programming languages, including an object oriented programming language such as Smalltalk, c++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The computer readable program instructions may be executed entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider). In some embodiments, aspects of the present disclosure are implemented by personalizing electronic circuitry, such as programmable logic circuitry, field Programmable Gate Arrays (FPGAs), or Programmable Logic Arrays (PLAs), with state information of computer readable program instructions, which can execute the computer readable program instructions.
Various aspects of the present disclosure are described herein with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the disclosure. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer-readable program instructions.
These computer readable program instructions may be provided to a processing unit of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processing unit of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks. These computer readable program instructions may also be stored in a computer readable storage medium that can direct a computer, programmable data processing apparatus, and/or other devices to function in a particular manner, such that the computer readable medium having the instructions stored therein includes an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer implemented process such that the instructions which execute on the computer, other programmable apparatus or other devices implement the functions/acts specified in the flowchart and/or block diagram block or blocks.
The flowcharts 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 disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of instructions, which comprises one or more executable instructions for implementing the specified logical function(s). 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 and/or flowchart illustration, and combinations of blocks in the block diagrams and/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 embodiments of the present disclosure have been described above, the foregoing description is illustrative, not exhaustive, and not limited to the embodiments disclosed. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the various embodiments described. The terminology used herein was chosen in order to best explain the principles of the embodiments, the practical application, or the improvement of technology in the marketplace, or to enable others of ordinary skill in the art to understand the embodiments disclosed herein.
Claims (9)
1. A method of content recommendation, comprising:
in response to receiving a request for a predetermined number of content, determining identity information of a user associated with the request;
determining, based on the identity information, a first set of content associated with the user, the first set of content comprising at least one item of content not pushed to the user;
determining whether a first number of content in the first set of content reaches the predetermined number;
determining a second set of content unread by the user from among the pushed sets of content that have been pushed to the user in response to the first number not reaching the predetermined number; and pushing the first set of content and the second set of content to the user; and is also provided with
Determining a third set of content from the first set of content in response to the first number reaching the predetermined number, the third set of content having the predetermined number of content; and pushing the third set of content to the user;
wherein determining the first set of content comprises: acquiring a fourth content set which is not pushed to the user in the previous pushing; determining a maximum content identifier in the previous push that has been pushed to the user; determining a fifth set of content based on the maximum content identifier and a content identifier of the latest content; and combining the fourth set of content and the fifth set of content to obtain the first set of content;
wherein determining the third set of content comprises at least: determining attribute information and/or preference information of the user based on the identity information; determining the association degree of each content in the first content set and the user based on the attribute information and/or the preference information; determining freshness of each content based on the release time of each content; determining a recommendation degree of each content based on the association degree of each content with the user and the freshness of each content; and determining the third set of content from the first set of content such that the recommendation of content in the third set of content is greater than a predetermined second recommendation threshold.
2. The method of claim 1, wherein determining the second set of content comprises:
determining attribute information and/or preference information of the user based on the identity information;
determining the association degree of each content in the pushed content set and the user based on the attribute information and/or the preference information; and
the second set of content is determined from the pushed set of content such that the association of content in the second set of content with the user is greater than a predetermined first association threshold.
3. The method of claim 1, wherein determining the second set of content comprises:
determining attribute information and/or preference information of the user based on the identity information;
determining the association degree of each content in the pushed content set and the user based on the attribute information and/or the preference information;
determining freshness of each content based on the release time of each content;
determining a recommendation degree of each content based on the association degree of each content with the user and the freshness of each content; and
the second set of content is determined from the pushed set of content such that the recommendation of content in the second set of content is greater than a predetermined first recommendation threshold.
4. The method of claim 1, wherein determining the third set of content further comprises:
determining attribute information and/or preference information of the user based on the identity information;
determining the association degree of each content in the first content set and the user based on the attribute information and/or the preference information; and
the third set of content is determined from the first set of content such that the association of content in the third set of content with the user is greater than a predetermined second association threshold.
5. An apparatus for content recommendation, comprising:
at least one processing unit;
at least one memory coupled to the at least one processing unit and storing instructions for execution by the at least one processing unit, the instructions when executed by the at least one processing unit cause the apparatus to perform actions comprising:
in response to receiving a request for a predetermined number of content, determining identity information of a user associated with the request;
determining, based on the identity information, a first set of content associated with the user, the first set of content comprising at least one item of content not pushed to the user;
determining whether a first number of content in the first set of content reaches the predetermined number;
determining a second set of content unread by the user from among the pushed sets of content that have been pushed to the user in response to the first number not reaching the predetermined number; and pushing the first set of content and the second set of content to the user; and is also provided with
Determining a third set of content from the first set of content in response to the first number reaching the predetermined number, the third set of content having the predetermined number of content; and pushing the third set of content to the user;
wherein determining the first set of content comprises: acquiring a fourth content set which is not pushed to the user in the previous pushing; determining a maximum content identifier in the previous push that has been pushed to the user; determining a fifth set of content based on the maximum content identifier and a content identifier of the latest content; and combining the fourth set of content and the fifth set of content to obtain the first set of content;
wherein determining the third set of content comprises at least: determining attribute information and/or preference information of the user based on the identity information; determining the association degree of each content in the first content set and the user based on the attribute information and/or the preference information; determining freshness of each content based on the release time of each content; determining a recommendation degree of each content based on the association degree of each content with the user and the freshness of each content; and determining the third set of content from the first set of content such that the recommendation of content in the third set of content is greater than a predetermined second recommendation threshold.
6. The apparatus of claim 5, wherein determining the second set of content comprises:
determining attribute information and/or preference information of the user based on the identity information;
determining the association degree of each content in the pushed content set and the user based on the attribute information and/or the preference information; and
the second set of content is determined from the pushed set of content such that the association of content in the second set of content with the user is greater than a predetermined first association threshold.
7. The apparatus of claim 5, wherein determining the second set of content comprises:
determining attribute information and/or preference information of the user based on the identity information;
determining the association degree of each content in the pushed content set and the user based on the attribute information and/or the preference information;
determining freshness of each content based on the release time of each content;
determining a recommendation degree of each content based on the association degree of each content with the user and the freshness of each content; and
the second set of content is determined from the pushed set of content such that the recommendation of content in the second set of content is greater than a predetermined first recommendation threshold.
8. The apparatus of claim 5, wherein determining the third set of content further comprises:
determining attribute information and/or preference information of the user based on the identity information;
determining the association degree of each content in the first content set and the user based on the attribute information and/or the preference information; and
the third set of content is determined from the first set of content such that the association of content in the third set of content with the user is greater than a predetermined second association threshold.
9. A computer readable storage medium having computer readable program instructions stored thereon for performing the method of any of claims 1-4.
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