CN110889733A - Resource and commodity recommendation method, device and equipment - Google Patents

Resource and commodity recommendation method, device and equipment Download PDF

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Publication number
CN110889733A
CN110889733A CN201811051554.9A CN201811051554A CN110889733A CN 110889733 A CN110889733 A CN 110889733A CN 201811051554 A CN201811051554 A CN 201811051554A CN 110889733 A CN110889733 A CN 110889733A
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resource
information
type
commodity
heat
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CN201811051554.9A
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CN110889733B (en
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梁剑锋
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Alibaba Group Holding Ltd
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Alibaba Group Holding Ltd
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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 application discloses a resource and commodity recommendation method, device and equipment. The method comprises the following steps: the method comprises the steps of firstly determining a resource type concerned by a resource transfer-out party, then obtaining resource heat information of the resource transfer-in party on the resource type, and recommending hot resources of the resource type to the resource transfer-out party based on the resource heat information.

Description

Resource and commodity recommendation method, device and equipment
Technical Field
The present application relates to the field of computer technologies, and in particular, to a resource and commodity recommendation method, device, and apparatus.
Background
With the rapid development of internet technology, more and more users are used to perform online resource transfer in the internet.
Common resource transfer patterns include: the user is used as a resource transferring party to transfer the resource from the resource producing party, and then used as a resource transferring party to provide the transferred resource for other users. Thus, the resources that a user carries in need to match the needs of other users.
Therefore, a more efficient resource recommendation method is needed.
Disclosure of Invention
The embodiment of the specification provides a resource and commodity recommendation method, device and equipment, which are used for helping a resource transfer party to make an effective resource selection strategy and improving resource selection efficiency.
An embodiment of the present specification further provides a resource recommendation method, including:
determining the type of the resource concerned by the resource roll-out party;
acquiring resource heat information of the resource transferring party on the resource type;
and recommending hot spot resources to the resource transfer party based on the resource heat information of the resource type.
An embodiment of the present specification further provides a commodity recommendation method, including:
determining the type of goods concerned by the seller;
acquiring commodity popularity information of the consumer to the commodity type;
and recommending hot commodities to the seller based on the commodity popularity information of the commodity type.
An embodiment of the present specification further provides a resource recommendation device, including:
the determining module is used for determining the type of the resource concerned by the resource transferring party;
the acquisition module is used for acquiring the resource heat information of the resource transfer party on the resource type;
and the recommending module is used for recommending the hot resource to the resource transfer party based on the resource heat information of the resource type.
An embodiment of the present specification further provides a commodity recommendation device, including:
the first determining module is used for determining the types of commodities concerned by sellers;
the second determining module is used for acquiring commodity popularity information of the consumer to the commodity type;
and the recommending module is used for recommending hot commodities to the seller based on the commodity heat information of the commodity type.
An embodiment of the present specification further provides an electronic device, including:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the steps of:
determining the type of the resource concerned by the resource roll-out party;
acquiring resource heat information of the resource transferring party on the resource type;
and recommending hot spot resources to the resource transfer party based on the resource heat information of the resource type.
Embodiments of the present specification further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the following steps:
determining the type of the resource concerned by the resource roll-out party;
acquiring resource heat information of the resource transferring party on the resource type;
and recommending hot spot resources to the resource transfer party based on the resource heat information of the resource type.
An embodiment of the present specification further provides an electronic device, including:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the steps of:
determining the type of goods concerned by the seller;
acquiring commodity popularity information of the consumer to the commodity type;
and recommending hot commodities to the seller based on the commodity popularity information of the commodity type.
The embodiment of the specification adopts the following technical scheme:
embodiments of the present specification further provide a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the following steps:
determining the type of goods concerned by the seller;
acquiring commodity popularity information of the consumer to the commodity type;
and recommending hot commodities to the seller based on the commodity popularity information of the commodity type.
The embodiment of the specification adopts at least one technical scheme which can achieve the following beneficial effects:
when the resource transfer-out party selects the resource, recommending the hot resource of the resource type to the resource transfer-out party from the angle of the resource heat information of the resource type concerned by the resource transfer-in party to the resource transfer-out party. Compared with the prior art, the resource selection method can effectively improve the resource selection efficiency of the resource transfer party and help the resource transfer party to make an effective resource selection strategy.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1a is a schematic diagram of an application scenario provided herein;
FIG. 1b is a schematic diagram of another application scenario provided herein;
FIG. 1c is a schematic diagram of yet another application scenario provided herein;
FIG. 2 is a flowchart illustrating a resource recommendation method according to an embodiment of the present disclosure;
FIG. 3 is a flowchart illustrating an implementation manner of determining a resource heat according to an embodiment of the present disclosure;
fig. 4 is a schematic flowchart of a product recommendation method according to another embodiment of the present disclosure;
5 a-5 c are schematic diagrams illustrating the effect of displaying commodity information by scrolling according to another embodiment of the present disclosure;
fig. 6 is a schematic structural diagram of a resource recommendation device according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of a merchandise recommendation device according to another embodiment of the present disclosure;
fig. 8 is a schematic structural diagram of an electronic device provided in an embodiment of the present specification;
fig. 9 is a schematic structural diagram of an electronic device according to another embodiment of the present disclosure.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the technical solutions of the present application will be described in detail and completely with reference to the following specific embodiments of the present application and the accompanying drawings. It should be apparent that the described embodiments are only some of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
As stated in the background section, when a resource transfer-out party selects a resource, the resource is generally recommended to the resource transfer-out party based on information such as the ranking, preference, etc. of the resource types transferred by the whole resource transfer-out party, but the resource types transferred by other resource transfer-out parties are not necessarily the resource types concerned by the resource transfer-out party. Therefore, the actual selection strategy for the resource forwarder is not much helpful.
Based on the above, the invention provides a resource recommendation method, which comprises the steps of determining the resource type concerned by the resource transfer-out party when the resource transfer-out party selects the resource, and then recommending the hot resource of the resource type to the resource transfer-out party from the perspective of the resource heat information of the resource transfer-in party on the resource type. Therefore, the hot resources preferred by the resource transfer-in party can be recommended for the resource transfer-out party, so that the resource selection efficiency of the resource transfer-out party is effectively improved, and the resource transfer-out party is helped to make an effective resource selection strategy.
The following exemplifies an application scenario of the present invention.
Referring to fig. 1a, an application scenario includes: a plurality of resource transferors 101, resource transferors 102, and resource transfer platforms 103, wherein:
a resource transferring-in party 101 for transferring in the resource provided by the resource transferring-out party 102 through the resource transferring platform 103;
the resource transfer platform 103 is used for recording resource transfer-in data of the resource transfer-in party 101 and performing summary statistics to determine the resource preferred by the resource transfer-in party 101 and the heat information of the resource type concerned by the resource transfer-out party 102, and further recommending a hot resource for the resource transfer-out party 102;
and the resource transferring-out party 102 is used for transferring the hot resource recommended by the resource transferring platform 103 from the resource transferring platform 103 or other platforms for supplying the hot resource, and providing the hot resource to the resource transferring-in party 101 through the resource transferring platform 103.
Referring to fig. 1b, another application scenario includes: a plurality of resource transferors 111, resource transferors 112, a first resource transferor 113, and a second resource transferor 114, wherein:
a resource transferring-out part 112 for transferring in the resource from the first resource transferring platform 113 and providing to the resource transferring-in part 111 through the second resource transferring platform 114;
a resource transferor 111 for transferring the resource provided by the resource transferor 112 through the second resource transfer platform 114;
the second resource transfer platform 114 is configured to record resource transfer-in data of the resource transfer-in party 111 and perform summary statistics to determine the resource preferred by the resource transfer-in party 111 and the heat information of the resource type concerned by the resource transfer-out party 112;
the first resource transfer platform 113 is configured to obtain heat information of a resource type concerned by the resource transferring party 111 to the resource transferring party 112 from the second resource transfer platform 114, and recommend a hot resource to the resource transferring party 112 based on the heat information when the resource transferring party 112 transfers the resource from the local platform to the resource.
It should be noted that the resources in the two application scenarios include, but are not limited to: private products (i.e., commodities) produced for consumption by exchange into society, products that can be used without exchange (e.g., cloud disk shared resources, documents shared online in a library, etc.). However, for convenience of understanding and description, the following takes "commodity" as an example, and further provides an application scenario of "commodity".
Referring to fig. 1c, an application scenario of "commodity" includes: a plurality of consumer terminals 121, seller terminals 122, wholesale platform 123 and retail platform 124 for goods, wherein:
a seller terminal 122 for wholesale of the goods through the goods wholesale platform 123 and retail through the goods retail platform 124;
a consumer terminal for purchasing goods retail by a seller through the goods retail platform 124;
the commodity retail platform 124 is used for recording commodity transaction data of the consumer and performing summary statistics to determine commodity popularity information of commodity types concerned by the consumer to the seller;
the commodity wholesale platform 123 is configured to obtain commodity popularity information of commodity types of interest to the seller by the consumer from the commodity retail platform 124, so as to recommend hot commodities to the seller based on the commodity popularity information when the seller wholesales the commodities.
In the three application scenes, the resource transfer-in party and the resource transfer-out party, and the consumer terminal and the seller terminal can be a computer terminal, a mobile terminal and the like; the mobile terminal or the mobile communication terminal refers to a computer device which can be used in moving, and broadly includes a mobile phone, a notebook, a tablet computer, a POS machine, and even a vehicle-mounted computer. But most often refer to cell phones or smart phones and tablets with multiple application functions. The resource transfer platform, the first resource transfer platform, the second resource transfer platform, the commodity wholesale platform and the commodity retail platform can be server sides.
The technical solutions provided by the embodiments of the present application are described in detail below with reference to the accompanying drawings.
Fig. 2 is a flowchart of a resource recommendation method provided in an embodiment of this specification, and referring to fig. 1, the method may be executed by the resource transfer platform 103 in fig. 1a or the first resource transfer platform 113 in fig. 1b, and specifically may include the following steps:
step 220, determining the type of the resource concerned by the resource transfer party;
the resource type concerned by the resource transfer-out party may be a resource type input or selected by the resource transfer-out party, or may be a resource type available by the resource transfer-out party. Accordingly, one implementation of step 220 may be:
acquiring one or more resource types determined by the resource roll-out party;
that is, one resource type selected or input by the resource roll-out party is taken as the resource type of interest.
Another implementation of step 220 may be:
determining one or more resource types associated with the identification information of the resource roll-out party; the method specifically comprises the following steps:
determining a resource transfer-out history record of the resource transfer-out party based on the identification information of the resource transfer-out party; and determining one or more resource types transferred by the resource transfer party based on the resource transfer history.
That is, based on the resource roll-out history of the resource roll-out party, one or more resource types that it can provide are determined and taken as the resource type of interest.
Step 240, acquiring resource hot degree information of the resource transferring party on the resource type;
it should be noted that, when the method is executed by the resource transfer platform 103 in fig. 1a, one implementation manner of the method may be:
step S1, acquiring the history behavior record of the resource transfer party;
the historical behavior record can be a resource search record of a resource transfer party, and can also be a resource transfer record.
Step S2, determining the resource heat information of the resource transfer party to each resource type based on the historical behavior record;
the resource heat information can be determined by searching or transferring frequency, frequency increase and decrease amplitude in the latest preset time period and the like.
And step S3, determining the resource heat information of the resource type concerned by the resource transfer party to the resource transfer party. For example:
if the resource type concerned by the resource transfer party is a computer-class document, the resource heat information corresponding to the computer-class document is extracted from step S2, where the resource heat information may include a heat sequence under multiple dimensions, for example: under the dimension of download quantity, the heat sequence is as follows: the document A-heat is a, the document C-heat is C, and the document B-heat is B, wherein a is more than C and more than B; under the browsing volume dimension, the popularity sequence is as follows: the document B-heat is B, the document C-heat is C, and the document A-heat is a, wherein B > C > a.
When the method is executed by the first resource transfer platform 113 in fig. 1b, another implementation manner may be:
step S1, sending a read access request to the second resource transfer platform 114, where the read access request carries a resource type concerned by the resource transfer party;
step S2, receiving the historical behavior record corresponding to the resource type returned by the second resource transfer platform 114 in response to the read access request
And step S3, determining the resource heat information of the resource transferring party to the resource type based on the historical behavior record corresponding to the resource type.
When the method is executed by the first resource transfer platform 113 in fig. 1b, another implementation manner may be:
step S1, sending a read access request to the second resource transfer platform 114, where the read access request carries a resource type concerned by the resource transfer party;
step S2, receiving the resource hot degree information of the resource transferring party to the resource type, which is returned by the second resource transferring platform 114 in response to the read access request.
It is understood that, in this implementation manner, the second resource transfer platform 114 determines the resource heat information of each resource type by recording the historical behavior of the resource transferring party on each resource type and performing statistical analysis, and then returns the resource heat information of the resource type concerned by the resource transferring party when receiving the read access request of the first resource transfer platform 113.
And step 260, recommending hot spot resources to the resource roll-out party based on the resource heat information of the resource types.
Wherein the resource hot degree information includes: resource retrieval heat information and/or resource transfer heat information, wherein the resource retrieval heat information is a heat sequence in a retrieval (search) dimension, and the resource transfer heat information is a heat sequence in a transfer dimension (for example, a download dimension in step S3 of step 240);
accordingly, one implementation of step 260 may be:
step S1, determining the corresponding heat degree of the resource belonging to the resource type based on the resource heat degree information of the resource type; with reference to fig. 3, it may specifically be:
step 320, determining the retrieval heat corresponding to the resource belonging to the resource type based on the resource retrieval heat information of the resource type;
step 340, determining the transfer heat corresponding to the resource of the resource type based on the resource transfer heat information of the resource type;
and 360, determining the heat degree of the resource belonging to the resource type based on the retrieval heat degree and/or the transfer heat degree.
For steps 320-360, assuming that the resource type of interest to the resource roll-out is a computer-like document, the resource retrieval heat information may be exemplified by: the document A-retrieval heat is a, the document B-retrieval heat is B, and the document C-retrieval heat is C, wherein a is more than B is more than C; the resource transfer heat information may be exemplified by: d is the download heat of the document D, W is the download heat of the document W, and a is the download heat of the document A, wherein D is more than W and more than a. Further, the degree of popularity of each document may be determined based on the degree of popularity of retrieval and/or the degree of popularity of download of each document of the computer class.
The implementation manner of calculating the document popularity based on the document retrieval popularity and/or the download popularity is not limited herein.
And step S2, recommending the characteristic information of the resource (namely, the hot resource) with the heat degree meeting the preset condition to the resource transfer party.
The predetermined condition may be a predetermined number of resources with the maximum heat degree, or may be a resource with the heat degree satisfying a predetermined threshold; the characteristic information of the resource includes: one or more of the resource identification, the resource heat and the heat fluctuation range may further include: search (or go) volume, comments, profiles, etc. Taking the assumption in step 320-step 360 as an example:
assume that the calculated popularity of a computer-like document is: the degree of heat of the document W > the degree of heat of the document A > the degree of heat of the document D, and the like, one or more resources can be selected from the documents based on a preset condition, and characteristic information such as retrieval (or transfer-in) amount, score, name, abstract, source and the like can be recommended to a resource transfer party.
In addition, it is understood that the resource type concerned by the resource transfer party may not be unique, and based on the above steps, a resource whose heat degree satisfies the predetermined condition may be selected from the resources of each resource type, and the characteristic information thereof may be recommended to the resource transfer party.
Optionally, in order to improve the resource recommendation effect, this embodiment further discloses a recommendation method of feature information of a resource:
and associating the characteristic information of the hot spot resources belonging to the same resource type and sending the characteristic information to the client so that the client can display the characteristic information of the associated hot spot resources in a scroll mode. Assuming that the resource types concerned by the resource roll-out party include computer-class documents and science fiction-class movies, the recommendation method can be exemplified as follows:
binding the characteristic information of the hot documents belonging to the computer documents so that the client can show the characteristic information of the hot documents of the bound computer documents as a first frame;
binding the characteristic information of the hot movies belonging to the science fiction movies, so that the client can show the bound characteristic information of the hot movies of the science fiction movies as a second frame;
the loop shows the feature information in the first frame and the second frame.
In addition, it is understood that when the feature information of the hot spot resource of the same resource type is more, the feature information can be separately bound and displayed by using multiple frames.
Optionally, to further improve recommendation efficiency, this embodiment further discloses an association manner of feature information of hot resources of the same resource type:
determining a heat sequence corresponding to hot spot resources belonging to the same resource type; and associating the characteristic information of the hot spot resources belonging to the same resource type based on the heat sequence. Suppose that the hot resource sequence of the computer-class document concerned by the resource roll-out party is: the degree of heat of document W > the degree of heat of document A > the degree of heat of document D, the association may be as follows:
and setting the characteristic information of the document W at the first position, the characteristic information of the document A at the second position and the characteristic information of the document D at the last position.
Therefore, the characteristic information of the hot resources of the unified resource types can be displayed to the user according to the heat sequence, so that the heat resources and the characteristic information thereof can be found by the resource transfer party at the first time, and an effective resource selection strategy can be made efficiently.
It can be seen that, in this embodiment, when a resource transfer-out party selects a resource, a resource type concerned by the resource transfer-out party is determined first, and then resource heat information of the resource transfer-in party on the resource type is determined, so that a hot resource of the concerned resource type can be recommended to the resource transfer-out party from the perspective of resource demand heat of the resource transfer-in party. Compared with the prior art, the resource selection method can help the resource transfer party to make an effective resource selection strategy and improve the resource selection efficiency of the resource transfer party.
Fig. 4 is a schematic flow chart of a product recommendation method according to another embodiment of the present disclosure, referring to fig. 4, where the method may be executed by the product wholesale platform in fig. 1c, and specifically may include the following steps:
step 420, determining the type of goods concerned by the seller;
the type of the goods concerned by the seller may be a type of goods input or selected by the seller, or a type of goods sold by the seller. Accordingly, one implementation of step 420 may be:
acquiring one or more commodity types determined by the seller;
that is, one article type selected or input by the seller is taken as the article type of interest.
Another implementation of step 220 may be:
determining one or more commodity types associated with the seller's identification information; the method specifically comprises the following steps:
determining a commodity selling history of the seller based on the identification information of the seller; determining one or more types of goods sold by the seller based on the goods sale history.
That is, based on the seller's product sale history, one or more product types that it can provide are determined and taken as the product type of interest.
Step 440, obtaining commodity popularity information of the consumer for the commodity type;
for step 440, since it corresponds to 240 in the corresponding embodiment of fig. 2, the implementation thereof is similar, so that step 440 is briefly described as follows:
if the method is applied to a commodity wholesale platform, step 440 may be exemplified as:
acquiring commodity popularity information of the consumer on the commodity type from a commodity retail platform; alternatively, the first and second electrodes may be,
sending a reading access request to a commodity sales platform so as to obtain a historical transaction record corresponding to the commodity type concerned by a seller from the commodity sales platform; and determining commodity popularity information of the consumer for the commodity type based on the historical transaction records.
Step 460, recommending hot goods to the seller based on the goods popularity information of the goods type.
For step 460, since it corresponds to 260 in the corresponding embodiment of fig. 2, and its implementation is similar, the step 460 is briefly described as follows, and one implementation may be:
step S1, determining the corresponding popularity of the commodity belonging to the commodity type based on the commodity popularity information of the commodity type;
wherein, commodity heat degree information includes: commodity searching popularity information and/or commodity transaction popularity information; step S1 may specifically be:
determining the corresponding search heat of the commodity belonging to the commodity type based on the commodity search heat information of the commodity type;
determining the transaction popularity corresponding to the commodity of the commodity type based on the commodity transaction popularity information of the commodity type;
and determining the popularity of the commodity belonging to the commodity type based on the search popularity and/or the transaction popularity.
In step S2, the commodity information of the commodity whose popularity satisfies the predetermined condition is recommended to the seller.
The preset condition can be one or more commodities with the maximum heat degree, or the commodities with the heat degree larger than a preset threshold value; the commodity information includes: one or more of a picture of the commodity, a heat of the commodity, and a rise and fall amplitude of the heat. Accordingly, step S2 may be specifically exemplified by:
and correlating the commodity information of the hot commodities belonging to the same commodity type and sending the commodity information to the client so that the client can display the commodity information of the correlated hot commodities in a scroll screen mode.
In connection with fig. 5 a-5 c, it is assumed that the types of goods of interest to the seller include: women's wear, children's wear, and department store; wherein hot spot commodities of women's dress are down jackets, pure cotton coats and leggings, hot spot commodities of children's dress are one-piece dress, pullover and leggings, hot spot commodities of general merchandise are electric cooker, thermos cup and storage box; binding commodity information of hot commodities belonging to the women's dress for the client to display in the first frame; binding commodity information of hot commodities belonging to children's garments for display of the client side in a second frame; and binding the commodity information of the hot commodities belonging to the general merchandise for the client to display in the third frame.
Further, this embodiment also further discloses a commodity information binding mode:
determining a heat sequence corresponding to hot commodities belonging to the same commodity type; and associating the commodity information of the hot commodities belonging to the same commodity type based on the heat sequence.
Namely, the commodity information of each hot commodity is bound from the dimension of the heat degree according to the sequence of the heat degrees from big to small.
Therefore, in the embodiment, when a seller wholesales goods, the type of the goods concerned by the seller is determined, and then the goods popularity information of the consumer for the type of the goods is determined, so that hot goods of the type of the goods sold can be recommended to the seller from the perspective of the goods demand popularity of the consumer. Compared with the prior art, the method can help the seller to make an effective commodity wholesale strategy and improve the commodity wholesale efficiency of the seller.
In another possible embodiment, a commodity recommendation method provided in fig. 4 may also be performed by the server or the client or both interactively; the client refers to a program that can be installed on the seller terminal or the consumer terminal in fig. 1c, and is used for providing local services for the user; the server is used for interacting with the client to provide services such as resources and data storage for the client.
Taking the example that the server and the client interact to execute the commodity recommendation method, the specific implementation process may be as follows:
a user initiates a login request carrying a user identifier to a server through a client, so that the server responds to the login request when verifying that the user identifier is legal to complete login;
the server inquires the commodity type concerned by the user, wherein the concerned commodity type can be a commodity type corresponding to a keyword input by the user after login, can also be a commodity type corresponding to a historical search record and a historical transaction record of the user, and can also be a commodity type sold by the user;
the server inquires hot sold commodities of the commodity type concerned by the user and takes one or more commodities with the highest heat degree in the hot sold commodities as hot commodities; alternatively, the first and second electrodes may be,
the server inquires hot search keywords of the commodity type concerned by the user, such as: and if the types of the goods concerned by the user are inquired to be women's clothes and children's clothes, inquiring hot search keywords corresponding to the women's clothes, down coats, pure cotton coats, leggings and the like, and selecting one or more keywords with the highest hot search degree from the keywords, such as: the down jacket and the leggings are used as hot spot commodities;
the server further recommends the commodity information such as the hot degree/hot search degree, the hot degree expansion/hot search degree expansion, the commodity picture and the like of the hot commodity to the user.
The user can be a seller, and the recommended hot commodities are used for prompting hot commodities searched and purchased by consumer groups, so that convenience is provided for wholesale and goods-feeding of the seller; the user can also be a consumer, and the recommended hot commodity is used for prompting other consumers to search and purchase the hot commodity, so that the commodity required by the consumer can be recommended to the consumer with high probability.
Therefore, in the embodiment, when the user shops, the commodity type concerned by the user is determined firstly, and then the commodity popularity information of the consumer group for the commodity type is determined, so that the hot commodity for purchasing can be recommended for the user from the commodity demand popularity of the consumer group. Compared with the prior art, the method and the system can help the user to make an effective commodity purchasing strategy and improve the commodity purchasing efficiency of the user.
In addition, for simplicity of explanation, the above-described method embodiments are described as a series of acts or combinations, but it should be understood by those skilled in the art that the present invention is not limited by the order of acts or steps described, as some steps may be performed in other orders or simultaneously according to the present invention. Furthermore, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no particular act is required to implement the invention.
Fig. 6 is a schematic structural diagram of a resource recommendation device according to an embodiment of the present disclosure, and referring to fig. 6, the device may specifically include: a determination module 61, an acquisition module 62 and a recommendation module 63, wherein:
a determining module 61, configured to determine a resource type concerned by the resource transfer party;
an obtaining module 62, configured to obtain resource heat information of the resource type for the resource transferring party;
and the recommending module 64 is configured to recommend the hot resource to the resource forwarding party based on the resource hot degree information of the resource type.
Optionally, the determining module 61 is specifically configured to:
acquiring one or more resource types determined by the resource roll-out party; or determining one or more resource types associated with the identification information of the resource roll-out party.
Optionally, the determining module 61 is further configured to:
determining a resource transfer-out history record of the resource transfer-out party based on the identification information of the resource transfer-out party; and determining one or more resource types transferred by the resource transfer party based on the resource transfer history.
Optionally, the apparatus further comprises:
the recording module is used for acquiring the historical behavior record of the resource transfer party; and determining the resource heat information of the resource transfer party to each resource type based on the historical behavior record.
Optionally, the recommending module 64 is specifically configured to:
determining the corresponding heat degree of the resource belonging to the resource type based on the resource heat degree information of the resource type; and recommending the characteristic information of the resource with the heat degree meeting the preset condition to the resource transfer party.
Optionally, the resource hot degree information includes: resource retrieval heat information and/or resource transfer heat information;
wherein, the recommending module 64 is further configured to:
determining the retrieval heat corresponding to the resource belonging to the resource type based on the resource retrieval heat information of the resource type; determining the transfer heat corresponding to the resource of the resource type based on the resource transfer heat information of the resource type; and determining the heat degree of the resource belonging to the resource type based on the retrieval heat degree and/or the transfer heat degree.
Optionally, the recommending module 64 is further configured to:
and associating the characteristic information of the hot spot resources belonging to the same resource type and sending the characteristic information to the client so that the client can display the characteristic information of the associated hot spot resources in a scroll mode.
Optionally, the recommending module 64 is further configured to:
determining a heat sequence corresponding to hot spot resources belonging to the same resource type; and associating the characteristic information of the hot spot resources belonging to the same resource type based on the heat sequence.
Optionally, the feature information includes one or more of a resource identifier, a resource heat and a heat fluctuation range.
Optionally, the apparatus is adapted to a first resource transfer platform, where the first resource transfer platform is configured to provide a resource transfer service for a resource transfer-out party, and the second resource transfer platform is configured to provide a resource transfer service for a resource transfer-in party;
the obtaining module 62 is specifically configured to:
acquiring resource heat information of the resource transferring party on the resource type from the second resource transferring platform; or acquiring a historical behavior record corresponding to the resource type from the second resource transfer platform, and determining the resource heat information of the resource transfer party on the resource type based on the historical behavior record.
Therefore, in the embodiment, when a seller wholesales goods, the type of the goods concerned by the seller is determined, and then the goods popularity information of the consumer for the type of the goods is determined, so that hot goods of the type of the goods sold can be recommended to the seller from the perspective of the goods demand popularity of the consumer. Compared with the prior art, the method can help the seller to make an effective commodity wholesale strategy and improve the commodity wholesale efficiency of the seller.
Fig. 7 is a schematic structural diagram of a product recommendation device according to another embodiment of the present disclosure, and referring to fig. 7, the device may specifically include: a determination module 71, an acquisition module 72 and a recommendation module 73, wherein:
a determination module 71 for determining the type of goods of interest to the seller;
the acquisition module 72 is used for acquiring the commodity popularity information of the consumer to the commodity type;
and the recommending module 73 is configured to recommend hot commodities to the seller based on the commodity popularity information of the commodity type.
Optionally, the determining module 71 is specifically configured to:
acquiring one or more commodity types determined by the seller; alternatively, the first and second electrodes may be,
determining one or more commodity types associated with the seller's identification information;
optionally, the determining module 71 is specifically configured to:
determining a commodity selling history of the seller based on the identification information of the seller; determining one or more types of goods sold by the seller based on the goods sale history.
Optionally, the obtaining module 72 is specifically configured to:
and acquiring commodity popularity information of the consumer to the commodity type from a commodity retail platform. Alternatively, the first and second electrodes may be,
sending a reading access request to a commodity sales platform so as to obtain a historical transaction record corresponding to the commodity type concerned by a seller from the commodity sales platform; and determining commodity popularity information of the consumer for the commodity type based on the historical transaction records.
Optionally, the recommending module 73 is specifically configured to:
determining the corresponding popularity of the commodity belonging to the commodity type based on the commodity popularity information of the commodity type; and recommending the commodity information of the commodity with the heat degree meeting the preset condition to the seller.
Optionally, the predetermined condition may be one or more commodities with the highest heat degree, or may be commodities with a heat degree greater than a predetermined threshold value; the commodity information includes: one or more of a picture of the commodity, a heat of the commodity, and a rise and fall amplitude of the heat.
Optionally, the commodity popularity information includes: commodity searching popularity information and/or commodity transaction popularity information;
wherein, the recommending module 73 is further configured to:
determining the corresponding search heat of the commodity belonging to the commodity type based on the commodity search heat information of the commodity type; determining the transaction popularity corresponding to the commodity of the commodity type based on the commodity transaction popularity information of the commodity type; and determining the popularity of the commodity belonging to the commodity type based on the search popularity and/or the transaction popularity.
Optionally, the recommending module 73 is further configured to:
and correlating the commodity information of the hot commodities belonging to the same commodity type and sending the commodity information to the client so that the client can display the commodity information of the correlated hot commodities in a scroll screen mode.
Optionally, the recommending module 73 is further configured to:
determining a heat sequence corresponding to hot commodities belonging to the same commodity type; and associating the commodity information of the hot commodities belonging to the same commodity type based on the heat sequence.
Optionally, the device is suitable for a commodity wholesale platform;
wherein, the acquisition module is specifically configured to:
and acquiring commodity popularity information of the consumer to the commodity type from a commodity retail platform.
Therefore, in the embodiment, when a seller wholesales goods, the type of the goods concerned by the seller is determined, and then the goods popularity information of the consumer for the type of the goods is determined, so that hot goods of the type of the goods sold can be recommended to the seller from the perspective of the goods demand popularity of the consumer. Compared with the prior art, the method can help the seller to make an effective commodity wholesale strategy and improve the commodity wholesale efficiency of the seller.
In addition, as for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to part of the description of the method embodiment.
It should be noted that, in the respective components of the apparatus of the present invention, the components therein are logically divided according to the functions to be implemented thereof, but the present invention is not limited thereto, and the respective components may be newly divided or combined as necessary.
Fig. 8 is a schematic structural diagram of an electronic device provided in an embodiment of the present specification, and referring to fig. 8, the electronic device includes: a processor, an internal bus, a network interface, a memory, and a non-volatile memory, although it may also include hardware required for other services. The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the resource recommendation device on the logic level. Of course, besides the software implementation, the present application does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or logic devices.
The network interface, the processor and the memory may be interconnected by a bus system. The bus may be an ISA (Industry Standard Architecture) bus, a PCI (peripheral component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 8, but that does not indicate only one bus or one type of bus.
The memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both read-only memory and random access memory, and provides instructions and data to the processor. The Memory may include a Random-Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least 1 disk Memory.
The processor is used for executing the program stored in the memory and specifically executing:
determining the type of the resource concerned by the resource roll-out party;
acquiring resource heat information of the resource transferring party on the resource type;
and recommending hot spot resources to the resource transfer party based on the resource heat information of the resource type.
The method performed by the resource recommendation device or manager (Master) node according to the embodiment shown in fig. 6 of the present application may be applied to or implemented by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The resource recommendation device may also perform the methods of fig. 2-3 and implement the methods performed by the manager node.
Based on the same invention creation, the embodiment of the present application further provides a computer readable storage medium, which stores one or more programs that, when executed by an electronic device including a plurality of application programs, cause the electronic device to execute the resource recommendation method provided by the corresponding embodiment of fig. 2 to 3.
Fig. 9 is a schematic structural diagram of an electronic device according to another embodiment of the present disclosure, and referring to fig. 9, the electronic device includes: a processor, an internal bus, a network interface, a memory, and a non-volatile memory, although it may also include hardware required for other services. The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form the commodity recommending device on a logic level. Of course, besides the software implementation, the present application does not exclude other implementations, such as logic devices or a combination of software and hardware, and the like, that is, the execution subject of the following processing flow is not limited to each logic unit, and may also be hardware or logic devices.
The network interface, the processor and the memory may be interconnected by a bus system. The bus may be an ISA (Industry Standard Architecture) bus, a PCI (peripheral component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of illustration, only one double-headed arrow is shown in FIG. 9, but this does not indicate only one bus or one type of bus.
The memory is used for storing programs. In particular, the program may include program code comprising computer operating instructions. The memory may include both read-only memory and random access memory, and provides instructions and data to the processor. The Memory may include a Random-Access Memory (RAM) and may also include a non-volatile Memory (non-volatile Memory), such as at least 1 disk Memory.
The processor is used for executing the program stored in the memory and specifically executing:
determining the type of goods concerned by the seller;
acquiring commodity popularity information of the consumer to the commodity type;
and recommending hot commodities to the seller based on the commodity popularity information of the commodity type.
The method performed by the product recommendation device or manager (Master) node according to the embodiment shown in fig. 7 of the present application may be implemented in or by a processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps, and logic blocks disclosed in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware decoding processor, or implemented by a combination of hardware and software modules in the decoding processor. The software module may be located in ram, flash memory, rom, prom, or eprom, registers, etc. storage media as is well known in the art. The storage medium is located in a memory, and a processor reads information in the memory and completes the steps of the method in combination with hardware of the processor.
The merchandise recommendation device may also perform the method of fig. 4 and implement the method performed by the manager node.
Based on the same invention creation, the embodiment of the present application further provides a computer-readable storage medium storing one or more programs, which when executed by an electronic device including a plurality of application programs, cause the electronic device to execute the product recommendation method provided by the embodiment corresponding to fig. 4.
The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
As will be appreciated by one skilled in the art, embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In a typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
Computer-readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The above description is only an example of the present application and is not intended to limit the present application. Various modifications and changes may occur to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims (18)

1. A resource recommendation method, comprising:
determining the type of the resource concerned by the resource roll-out party;
acquiring resource heat information of the resource transferring party on the resource type;
and recommending hot spot resources to the resource transfer party based on the resource heat information of the resource type.
2. The method of claim 1, wherein determining a roll-out resource type of interest to a resource roll-out comprises:
acquiring one or more resource types determined by the resource roll-out party; alternatively, the first and second electrodes may be,
and determining one or more resource types associated with the identification information of the resource roll-out party.
3. The method of claim 2, wherein determining one or more resource types associated with the identity information of the resource transfer party comprises:
determining a resource transfer-out history record of the resource transfer-out party based on the identification information of the resource transfer-out party;
and determining one or more resource types transferred by the resource transfer party based on the resource transfer history.
4. The method according to claim 1, further comprising, before obtaining resource hot information of the resource type for the resource transferring party:
acquiring a historical behavior record of the resource transferring party;
and determining the resource heat information of the resource transfer party to each resource type based on the historical behavior record.
5. The method according to any one of claims 1-4, wherein recommending hot resources to the resource transferor based on the resource hot information of the resource type comprises:
determining the corresponding heat degree of the resource belonging to the resource type based on the resource heat degree information of the resource type;
and recommending the characteristic information of the resource with the heat degree meeting the preset condition to the resource transfer party.
6. The method of claim 5, wherein the resource heat information comprises: resource retrieval heat information and/or resource transfer heat information;
wherein, based on the resource heat information of the resource type, determining the corresponding heat of the resource belonging to the resource type comprises:
determining the retrieval heat corresponding to the resource belonging to the resource type based on the resource retrieval heat information of the resource type;
determining the transfer heat corresponding to the resource of the resource type based on the resource transfer heat information of the resource type;
and determining the heat degree of the resource belonging to the resource type based on the retrieval heat degree and/or the transfer heat degree.
7. The method of claim 5, wherein recommending the feature information of the resource with the heat degree satisfying the predetermined condition to the resource transferor comprises:
and associating the characteristic information of the hot spot resources belonging to the same resource type and sending the characteristic information to the client so that the client can display the characteristic information of the associated hot spot resources in a scroll mode.
8. The method of claim 7, wherein associating the feature information of the hot-spot resources belonging to the same resource type comprises:
determining a heat sequence corresponding to hot spot resources belonging to the same resource type;
and associating the characteristic information of the hot spot resources belonging to the same resource type based on the heat sequence.
9. The method of claim 7, wherein the characteristic information comprises one or more of resource identification, resource heat, and heat fluctuation.
10. The method according to claim 1, applied to a first resource transfer platform, wherein the first resource transfer platform is used for providing a resource transfer-in service for a resource transfer-out party;
the method for acquiring the resource heat information of the resource type by the resource transfer party comprises the following steps:
acquiring resource heat information of a resource transfer party on the resource type from a second resource transfer platform; alternatively, the first and second electrodes may be,
acquiring a historical behavior record corresponding to the resource type from the second resource transfer platform, and determining resource heat information of a resource transfer party on the resource type based on the historical behavior record;
and the resource transfer-in party transfers the resources provided by the resource transfer-out party through the second resource transfer platform.
11. A method for recommending an article, comprising:
determining the type of goods concerned by the seller;
acquiring commodity popularity information of the consumer to the commodity type;
and recommending hot commodities to the seller based on the commodity popularity information of the commodity type.
12. The method of claim 11, wherein recommending hot goods to the seller based on the goods popularity information for the goods type comprises:
determining the corresponding popularity of the commodity belonging to the commodity type based on the commodity popularity information of the commodity type;
and recommending the commodity information of the commodity with the heat degree meeting the preset condition to the seller.
13. The method according to claim 12, wherein recommending the article information of the article having the degree of heat satisfying the predetermined condition to the seller comprises:
and correlating the commodity information of the hot commodities belonging to the same commodity type and sending the commodity information to the client so that the client can display the commodity information of the correlated hot commodities in a scroll screen mode.
14. The method of claim 11, adapted for use with a merchandising platform;
the step of acquiring the commodity popularity information of the consumer to the commodity type comprises the following steps:
and acquiring commodity popularity information of the consumer to the commodity type from a commodity retail platform.
15. A resource recommendation device, comprising:
the determining module is used for determining the type of the resource concerned by the resource transferring party;
the acquisition module is used for acquiring the resource heat information of the resource transfer party on the resource type;
and the recommending module is used for recommending the hot resource to the resource transfer party based on the resource heat information of the resource type.
16. An article recommendation device, comprising:
the determining module is used for determining the types of the commodities concerned by the seller;
the acquisition module is used for acquiring the commodity popularity information of the consumer to the commodity type;
and the recommending module is used for recommending hot commodities to the seller based on the commodity heat information of the commodity type.
17. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions that, when executed, cause the processor to perform the steps of the method of any one of claims 1 to 14.
18. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method according to any one of claims 1 to 14.
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