CN110941766B

CN110941766B - Information pushing method, device, computer equipment and storage medium

Info

Publication number: CN110941766B
Application number: CN201911262108.7A
Authority: CN
Inventors: 祝硕宏; 王晓露
Original assignee: Beijing ByteDance Network Technology Co Ltd
Current assignee: Douyin Vision Co Ltd; Douyin Vision Beijing Co Ltd
Priority date: 2019-12-10
Filing date: 2019-12-10
Publication date: 2023-10-20
Anticipated expiration: 2039-12-10
Also published as: CN110941766A

Abstract

The disclosure provides a method, a device, a computer device and a storage medium for pushing information, wherein the method comprises the following steps: determining a target recommended word; n candidate media materials corresponding to the target recommended word are obtained, and M candidate recommended pictures are extracted from the N candidate media materials; wherein M is greater than or equal to N; determining a target recommended picture from the candidate recommended pictures based on the similarity between the candidate recommended pictures; and correlating the target recommended words with the target recommended pictures and sending the target recommended words and the target recommended pictures to the terminal. By adopting the scheme, information pushing is realized through a combined display mode of the text and the picture, so that the display effect is improved, the display effect is more visual, and the user can select conveniently.

Description

Information pushing method, device, computer equipment and storage medium

Technical Field

The disclosure relates to the technical field of computer processing, and in particular relates to a method, a device, computer equipment and a storage medium for pushing information.

Background

Currently, in order to improve the searching efficiency of a user, before the user inputs a keyword into a search box, the user may automatically recommend a search term to the user in a search area, and if the recommended search term can arouse the interest of the user, the user may obtain a corresponding search result by directly clicking the search term.

It can be known that the existing search word pushing method only pushes the search word, and the display effect is single.

Disclosure of Invention

The embodiment of the disclosure provides at least one scheme for pushing information, and the information pushing is realized through a combined display mode of texts and pictures, so that the display effect is improved, the display effect is more visual, and the user can select the information conveniently.

Mainly comprises the following aspects:

in a first aspect, an embodiment of the present disclosure provides a method for pushing information, where the method includes:

determining a target recommended word; acquiring N candidate media materials corresponding to the target recommended word, and extracting M candidate recommended pictures from the N candidate media materials; wherein M is greater than or equal to N;

determining a target recommended picture from the candidate recommended pictures based on the similarity between the candidate recommended pictures;

and correlating the target recommended word with the target recommended picture and sending the target recommended word and the target recommended picture to a terminal.

In an optional embodiment, the determining, based on the similarity between the candidate recommended pictures, the target recommended picture from the candidate recommended pictures includes:

grouping M candidate recommended pictures based on the similarity among the candidate recommended pictures to obtain at least one candidate recommended picture set;

Sorting the at least one candidate recommended picture set according to the number of candidate recommended pictures included in the candidate recommended picture set;

determining the first candidate recommended picture set with the highest ranking as a target recommended picture set;

and selecting the target recommended picture from the target recommended picture set.

In an optional embodiment, if the number of the first candidate recommended picture sets with the highest ranking is greater than or equal to 2, the determining the first candidate recommended picture set with the highest ranking as the target recommended picture set includes:

respectively acquiring candidate media materials from which each candidate recommended picture in the first candidate recommended picture set comes, and determining at least one candidate media material corresponding to each first candidate recommended picture set;

and determining the target recommended picture set from the first candidate recommended picture sets based on the relevance of at least one candidate media material corresponding to each first candidate recommended picture set and the target recommended word.

In an optional implementation manner, the determining the target recommended picture set from the first candidate recommended picture sets based on the relevance between at least one candidate media material corresponding to each first candidate recommended picture set and the target recommended word includes:

Determining the number of the candidate recommended pictures in the first candidate recommended set corresponding to each first candidate recommended picture set, and respectively generating the weight of each at least one candidate media material;

the target recommended picture set is determined from the first candidate recommended picture set based on the relevance of at least one candidate media material corresponding to each first candidate recommended picture set and the target recommended word, and the weight of each at least one candidate media material.

In an optional embodiment, the grouping the M candidate recommended pictures based on the similarity between the candidate recommended pictures to obtain at least one candidate recommended picture set includes:

aiming at any candidate recommended picture in the M candidate recommended pictures, forming a candidate recommended picture set by the candidate recommended picture and other candidate recommended pictures with similarity meeting a preset condition with the candidate recommended picture;

wherein the preset conditions include at least one of the following conditions:

the similarity is greater than a first threshold;

and the similarity between the candidate recommended pictures and the different candidate recommended pictures except the candidate recommended picture in the composed candidate recommended picture set is the same.

In an alternative embodiment, the selecting the target recommended picture from the target recommended picture set includes:

determining the similarity between any candidate recommended picture and other candidate recommended pictures in the target recommended picture set to obtain a similarity set corresponding to the target recommended picture set;

if the number of the similarities in the similarity set is 1, or the number of the similarities in the similarity set is more than or equal to 2, and the absolute value of the difference value between the similarities is less than or equal to a second threshold, determining any candidate recommended picture in the target recommended picture set as the target recommended picture;

if the number of the similarities in the similarity set is greater than or equal to 2 and the absolute value of the difference between the similarities is greater than the second threshold, attributing candidate recommended pictures with the same similarity in the target recommended picture set to the same group to obtain at least one target recommended picture subset; sorting the at least one target recommended picture subset according to the number of candidate recommended pictures included in the target recommended picture subset; and determining any candidate recommended picture in the highest-ranking target recommended picture subset as the target recommended picture.

In an alternative embodiment, if the target recommended picture subset is a plurality of target recommended pictures; determining any candidate recommended picture in the highest-ranking target recommended picture subset as the target recommended picture, including:

determining ranking results of candidate media materials to which any candidate recommended picture included in each target recommended picture subset belongs in N candidate media materials according to any target recommended picture subset in each target recommended picture subset; determining the ranking result of the target recommended picture subset in each target recommended picture subset according to the ranking result of the candidate media material to which each candidate recommended picture belongs in the N candidate media materials;

and determining any target recommended picture in the target recommended picture subset with the highest ranking as the target recommended picture.

In an alternative embodiment, the similarity between candidate recommended pictures is determined according to the following steps:

extracting picture fingerprint features from one candidate recommended picture in the two candidate recommended pictures;

and determining the similarity between the two candidate recommended pictures based on the similarity between the extracted picture fingerprint features.

In an optional implementation manner, the acquiring N candidate media materials corresponding to the target recommended word includes:

acquiring corresponding media materials according to the target recommended words;

ranking the media materials according to the sequence of the relevance from high to low;

and determining the media materials with the top N ranks as N candidate media materials corresponding to the target recommended word.

In an alternative embodiment, the candidate media materials include candidate videos, and the extracting M candidate recommended pictures from the N candidate media materials includes:

determining all candidate pictures included in the N candidate videos as M candidate recommended pictures; or alternatively, the process may be performed,

intercepting any one of the N candidate videos according to a preset intercepting duration and/or a preset intercepting position to obtain intercepted candidate videos, and determining all candidate pictures included in the intercepted N candidate videos as M candidate recommended pictures; or alternatively, the process may be performed,

and extracting key frame candidate pictures from all candidate pictures included in any one of the N candidate videos, and determining the extracted key frame candidate pictures in the N candidate videos as M candidate recommended pictures.

In an alternative embodiment, the candidate media material includes web page content; n candidate media materials corresponding to the target recommended word are determined according to the following steps:

capturing N webpage contents corresponding to the target recommended word; m candidate recommended pictures are carried in the N webpage contents;

extracting M candidate recommended pictures from the N candidate media materials according to the following steps:

and extracting M candidate recommended pictures from the N webpage contents.

In a second aspect, the present disclosure further provides a method for pushing information, where the method includes:

receiving a target recommended word and a target recommended picture; the target recommended pictures are determined from the candidate recommended pictures based on the similarity among M candidate recommended pictures, wherein the M candidate recommended pictures are extracted from N candidate media materials, and M is greater than or equal to N;

and carrying out association display on the target recommended word and the target recommended picture.

In a third aspect, the present disclosure further provides an apparatus for pushing information, where the apparatus includes:

the acquisition module is used for determining target recommended words; acquiring N candidate media materials corresponding to the target recommended word, and extracting M candidate recommended pictures from the N candidate media materials; wherein M is greater than or equal to N;

The determining module is used for determining a target recommended picture from the candidate recommended pictures based on the similarity between the candidate recommended pictures;

and the pushing module is used for associating the target recommended word with the target recommended picture and sending the target recommended word and the target recommended picture to the terminal.

In a fourth aspect, the present disclosure further provides an apparatus for pushing information, where the apparatus includes:

the receiving module is used for receiving the target recommended words and the target recommended pictures; the target recommended pictures are determined from the candidate recommended pictures based on the similarity among M candidate recommended pictures, wherein the M candidate recommended pictures are extracted from N candidate media materials, and M is greater than or equal to N;

and the display module is used for carrying out association display on the target recommended word and the target recommended picture.

In a fifth aspect, the present disclosure also provides a computer device comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating over the bus when the computer device is running, the machine-readable instructions when executed by the processor performing the steps of the method of information pushing according to the first aspect and any of its various embodiments.

In a sixth aspect, the present disclosure also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the method of information pushing of the first aspect and any of its various embodiments.

By adopting the scheme, the server firstly determines the target recommended word, then acquires N candidate media materials corresponding to the target recommended word, can determine the target recommended picture from M candidate recommended pictures based on the similarity between the candidate recommended pictures, and finally can correlate the target recommended word with the target recommended picture and then send the target recommended picture to the terminal for displaying.

The foregoing objects, features and advantages of the disclosure will be more readily apparent from the following detailed description of the preferred embodiments taken in conjunction with the accompanying drawings.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings required for the embodiments are briefly described below, which are incorporated in and constitute a part of the specification, these drawings showing embodiments consistent with the present disclosure and together with the description serve to illustrate the technical solutions of the present disclosure. It is to be understood that the following drawings illustrate only certain embodiments of the present disclosure and are therefore not to be considered limiting of its scope, for the person of ordinary skill in the art may admit to other equally relevant drawings without inventive effort.

FIG. 1 is a flow chart of a method for pushing information according to an embodiment of the present disclosure;

FIGS. 2 (a) -2 (b) are schematic diagrams showing specific applications of the method for pushing information according to the first embodiment of the present disclosure;

fig. 3 is a flowchart illustrating a specific method for selecting a target recommended picture in the method for pushing information according to the first embodiment of the present disclosure;

Fig. 4 is a flowchart of a specific method for determining a target recommended picture set in a method for pushing information according to an embodiment of the disclosure;

fig. 5 is a flowchart of a specific method for determining a target recommended picture in the method for pushing information according to the first embodiment of the present disclosure;

FIG. 6 is a flowchart of a specific method for determining candidate media materials in a method for pushing information according to an embodiment of the present disclosure;

fig. 7 is a flowchart of a method for pushing information according to a second embodiment of the disclosure;

fig. 8 is a schematic diagram of an apparatus for pushing information according to a third embodiment of the disclosure;

fig. 9 is a schematic diagram of another information pushing apparatus according to the third embodiment of the disclosure;

FIG. 10 shows a schematic diagram of a computer device provided by a fourth embodiment of the present disclosure;

fig. 11 shows a schematic diagram of another computer device provided by the fourth embodiment of the disclosure.

Detailed Description

For the purposes of making the objects, technical solutions and advantages of the embodiments of the present disclosure more apparent, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the drawings in the embodiments of the present disclosure, and it is apparent that the described embodiments are only some embodiments of the present disclosure, but not all embodiments. The components of the embodiments of the present disclosure, which are generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present disclosure provided in the accompanying drawings is not intended to limit the scope of the disclosure, as claimed, but is merely representative of selected embodiments of the disclosure. All other embodiments, which can be made by those skilled in the art based on the embodiments of this disclosure without making any inventive effort, are intended to be within the scope of this disclosure.

According to research, in the related art, before a user inputs a keyword into a search box, the user can automatically recommend the search word to the user in a search area, so that the user can obtain a corresponding search result by directly clicking the search word, however, only the pushing method for recommending the search word has a single display effect and cannot meet the increasingly promoted search requirement of the user.

Based on the above research, the present disclosure provides a scheme of information pushing, which realizes information pushing through a combined display mode of text and pictures, thereby improving the display effect, enabling the display effect to be more visual, facilitating the selection of users, and meeting the search requirements of users.

The present invention is directed to a method for manufacturing a semiconductor device, and a semiconductor device manufactured by the method.

The following description of the embodiments of the present disclosure will be made clearly and fully with reference to the accompanying drawings in which it is evident that the embodiments described are only some, but not all, of the embodiments of the present disclosure. The components of the present disclosure, as generally described and illustrated in the figures herein, may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present disclosure provided in the accompanying drawings is not intended to limit the scope of the disclosure, as claimed, but is merely representative of selected embodiments of the disclosure. All other embodiments, which can be made by those skilled in the art based on the embodiments of this disclosure without making any inventive effort, are intended to be within the scope of this disclosure.

It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further definition or explanation thereof is necessary in the following figures.

For the sake of understanding the present embodiment, first, a detailed description will be given of a method for pushing information disclosed in the present embodiment, where an execution subject of the method for pushing information provided in the present embodiment is generally a computer device with a certain computing capability, where the computer device includes, for example: a server or other processing device. In some possible implementations, the method of information pushing may be implemented by a processor invoking computer readable instructions stored in a storage medium.

The method for pushing information provided by the embodiment of the present disclosure will be described below by taking an execution body as a server as an example.

Example 1

Referring to fig. 1, a flowchart of a method for pushing information according to a first embodiment of the present disclosure is shown, where the method includes steps S101 to S103, where:

s101, determining a target recommended word; n candidate media materials corresponding to the target recommended word are obtained, and M candidate recommended pictures are extracted from the N candidate media materials; wherein M is greater than or equal to N;

S102, determining a target recommended picture from candidate recommended pictures based on the similarity between the candidate recommended pictures;

and S103, correlating the target recommended words with the target recommended pictures and sending the target recommended words and the target recommended pictures to the terminal.

In the information providing method provided by the embodiment of the present disclosure, after determining the target recommended word, the server may determine a candidate media material corresponding to the target recommended word, extract a candidate recommended picture from the candidate media material, then determine a target recommended picture based on a similarity between candidate recommended pictures, and finally send the target recommended word and the associated target recommended picture to the terminal, so that the terminal may display the target recommended word and the target recommended picture at the same time, and improve an overall display effect by using a visual response effect of the target recommended picture.

In order to facilitate different search requirements of different users, the target recommended words can be generated based on the search popularity information so that the user can know the information with higher popularity, and can also be generated based on the historical search record information of the terminal so as to meet the personalized requirements of different users.

In the embodiment of the present disclosure, only the target recommended word related to the search heat information may be determined for the terminal, only the target recommended word for the search record may be determined for the terminal, and the terminal may be determined to include the two types of target recommended words, which is not particularly limited in the embodiment of the present disclosure. In a specific application, a determination mode of which target recommended word is adopted can be determined by acquiring a preset search mode of the terminal.

The target recommended words may be one or more. In a specific Application, the server in the embodiment of the present disclosure may be an automatically determined target recommended word after determining that a search Application (APP) set on the terminal is opened, or may be a target recommended word determined after receiving a target recommended word display instruction sent by the terminal.

The target recommended word display instruction may be initiated to the server after the terminal responds to the target trigger operation, where the target trigger operation may be performed by using a search button set on a search display interface presented by the terminal by the user, that is, after the search button is triggered by the user, the target recommended word display instruction may be sent to the server by using a communication channel between the terminal and the server. The triggering operation may be a single click, a double click, a long press, etc., which is not particularly limited by the embodiments of the present disclosure.

In order to improve timeliness of information searching, the target recommended word may be updated along with the lapse of searching time. For example, it is determined that the user's history search record information is related to the driving of the car during the history time, and the target recommended word thereof may be a text including the driving of the car. If the automobile beauty with higher heat appears along with the forward movement of the search time, the interest of the user can be possibly caused after the server pushes the automobile beauty to the terminal, so that the search of the user for the automobile beauty is promoted, and at the moment, after the user triggers the target recommended word display instruction again, the text of the automobile beauty can be determined as the target recommended word of the user.

In the embodiment of the disclosure, while determining the target recommended word for the terminal, a target recommended picture associated with the target recommended word may also be determined for the terminal, where the target recommended picture may be determined from each candidate recommended picture based on a similarity between M candidate recommended pictures.

The M candidate recommended pictures may be extracted from N candidate media materials, where M is greater than or equal to N, that is, at least one candidate recommended picture may be extracted from any one candidate media material in the embodiment of the disclosure. The candidate media materials may be video materials, web page materials, or other multimedia materials including pictures, which is not particularly limited in the embodiments of the present disclosure. In addition, because the candidate media materials are corresponding to the target recommended words, the target recommended pictures extracted from the candidate media materials have a larger relevance with the target recommended words, so that the display effect is further improved.

Based on the determined target recommended word and target recommended picture, the information pushing method provided by the embodiment of the disclosure can correlate the target recommended word and target recommended picture and then send the target recommended word and target recommended picture to the terminal. In this way, the terminal can display each target recommended word and the corresponding target recommended picture at the same time, if the user is determined to execute the target selection operation for one target recommended word in each target recommended word, a search request can be initiated to the server, then the media material fed back by the server based on the search request can be received, and the media material can be displayed. The media materials are similar to the candidate media materials, and will not be described herein.

In order to facilitate understanding of the information pushing method provided by the embodiment of the present disclosure, an example is described below with reference to fig. 2 (a) to 2 (b).

As shown in fig. 2 (a), after determining and sending target recommended pictures corresponding to the 3 target recommended words to the terminal, the server presents a first search display interface for the terminal. On the first search display interface, the large scout skin dune is a target recommended word, and the picture arranged on the left side of the large scout skin dune is the target recommended picture. After the user selects the target recommended word, i.e. the large spy picric, the server can feed back the media material based on the search request of the terminal and can display the media material, as shown in fig. 2 (b).

It should be noted that the setting position of the search button and the relative position of the target recommended picture to the target recommended word are just a specific example, and in practical applications, the setting may be performed based on different application requirements, which is not limited herein.

Considering that the determination of the target recommended picture based on the similarity between candidate recommended pictures is a key step for implementing information push in the embodiment of the present disclosure, a specific description will be made below with reference to fig. 3.

As shown in fig. 3, the step of determining the target recommended picture specifically includes:

s301, grouping M candidate recommended pictures based on the similarity among the candidate recommended pictures to obtain at least one candidate recommended picture set;

s302, sorting at least one candidate recommended picture set according to the number of candidate recommended pictures included in the candidate recommended picture set;

s303, determining the first candidate recommended picture set with the highest ranking as a target recommended picture set;

s304, selecting a target recommended picture from the target recommended picture set.

Here, in the embodiment of the present disclosure, first, M candidate recommended pictures may be grouped based on a similarity between candidate recommended pictures to obtain a plurality of candidate recommended picture sets, and then, a first candidate recommended picture set with the largest number of candidate recommended pictures is selected from each candidate recommended picture set as a target recommended picture set to achieve selection of a target recommended picture. The number of the same or similar images can be maximized due to the selected target recommended picture set, so that the association degree between the selected target recommended picture and the target recommended word can be further ensured, and the display effect is improved.

In the embodiment of the present disclosure, the M candidate recommended pictures may be grouped based on the similarity between the candidate recommended pictures, that is, for each candidate recommended picture, the candidate recommended picture may be determined as a candidate recommended picture set, and other candidate recommended pictures whose similarity with the candidate recommended picture satisfies a preset condition.

The preset condition may be that the similarity is greater than a first threshold, that is, other candidate recommended pictures with greater similarity to the candidate recommended pictures to be grouped and the candidate recommended pictures to be grouped may be divided into a group; the above preset condition may also be that the similarity between the candidate recommended pictures other than the candidate recommended picture and the candidate recommended picture in the composed candidate recommended picture set is the same, that is, the candidate recommended pictures other than the candidate recommended picture to be grouped and the candidate recommended picture to be grouped may be divided into a group.

After grouping the candidate recommended pictures and obtaining at least one candidate recommended picture set, the at least one candidate recommended picture set may be ranked based on the number of candidate recommended pictures included in each candidate recommended picture set, and the first candidate recommended picture set having the highest ranking may be determined as the target recommended picture set.

The first candidate recommended picture set with the highest ranking can be one or a plurality of first candidate recommended pictures. When the plurality of first candidate recommended picture sets are provided, the target recommended picture set can be determined from the plurality of first candidate recommended picture sets based on the relevance of at least one candidate media material corresponding to the first candidate recommended picture sets and the target recommended word.

In the embodiment of the disclosure, regarding the relevance between each candidate media material corresponding to the first candidate recommended picture set and the target recommended word, the relevance between each candidate media material and the target recommended word may be determined based on the feature information corresponding to the candidate media material.

For example, when candidate videos are used as candidate media materials, the correlation between each candidate video and a target recommended word can be determined based on the correlation between feature information such as the summary information and the video content of the candidate videos and the target recommended word, and when the summary information of one candidate video contains the target recommended word, the correlation between the candidate video and the target recommended word can be determined to be larger, and conversely, the correlation between the candidate video and the target recommended word can be determined to be smaller. For another example, when the web page contents are used as the candidate media materials, the relevance between each web page content and the target recommended word can be determined by looking up the inverted index established by the web page contents and the like.

In order to facilitate understanding the above-described process related to determining a target recommended picture set from a plurality of first candidate recommended picture sets based on the relevance of the candidate media material to the target recommended word, a specific example will be described below with reference to candidate videos as candidate media materials.

For example, there are 10 candidate videos and two first candidate recommended picture sets with highest ranking, wherein each candidate recommended picture in one first candidate recommended picture set is from candidate video a, candidate video B and candidate video C, the ranking results corresponding to each candidate recommended picture in the first candidate recommended picture set are 1, 2 and 3, and each candidate recommended picture in the other first candidate recommended picture set is from candidate video C, candidate video D and candidate video F, and the ranking results corresponding to each candidate video in the first candidate recommended picture set are 3, 4 and 5.

Considering that different first candidate recommended picture sets may be derived from different candidate videos or may be derived from the same candidate video, when different first candidate recommended picture sets are derived from the same candidate video, the target recommended picture set may be determined in combination with the weight of at least one candidate media material corresponding to each first candidate recommended picture set (the number of corresponding occurrence candidate recommended pictures).

As shown in fig. 4, the target recommended picture set may be determined as follows.

S401, determining the number of candidate recommended pictures in the first candidate recommended set included in at least one corresponding candidate media material according to each first candidate recommended picture set, and respectively generating weights of the at least one candidate media material;

s402, determining a target recommended picture set from the first candidate recommended picture sets based on the correlation between at least one candidate media material corresponding to each first candidate recommended picture set and the target recommended word and the weight of each at least one candidate media material.

Here, for each first candidate recommended picture set, the weight of each at least one candidate media material may be generated based on the number of candidate recommended pictures in the first candidate recommended set included in the at least one candidate media material corresponding to the first candidate recommended picture set, that is, the greater the number of included candidate recommended pictures, the higher the weight of the at least one candidate media material corresponding to the first candidate recommended picture set.

In this way, the relevance of at least one candidate media material corresponding to each first candidate recommended picture set and the target recommended word, and the weight of each at least one candidate media material are combined, so that the target recommended picture set with the best relevance and the largest weight can be selected from the first candidate recommended picture sets.

After the target recommended picture set is determined, a target recommended picture may be selected from the target recommended picture set. In the embodiment of the disclosure, a similarity set corresponding to the target recommended picture set may be obtained based on the similarity between each candidate recommended picture in the target recommended picture set and each other candidate recommended picture, and then the target recommended picture may be selected based on the number and the size of at least one similarity included in the similarity set. The following two aspects are specifically described.

First aspect: in the embodiment of the disclosure, when determining that at least one similarity is the same similarity (i.e., the number of similarities in the corresponding similarity set is 1), any one candidate recommended picture in the target recommended picture set may be determined as the target recommended picture. In addition, when it is determined that at least one of the similarities is a plurality of the similarities and the absolute value of the difference between the different similarities is less than or equal to the second threshold (i.e., the number of the similarities in the corresponding similarity set is greater than or equal to 2 and the respective similarities are relatively close), any one of the candidate recommended pictures in the target recommended picture set may be determined as the target recommended picture.

In a second aspect, in the embodiment of the present disclosure, when it is determined that at least one similarity is a plurality of similarities, and an absolute value of a difference between different similarities is greater than a second threshold (that is, a number of similarities in a corresponding similarity set is greater than or equal to 2, and a difference between the similarities is greater), the target recommended picture sets may be grouped again to obtain a plurality of target recommended picture subsets, and then a target recommended picture subset with the largest number of candidate recommended pictures is selected from the target recommended picture subsets as the target recommended picture subset to implement selection of the target recommended pictures. As shown in fig. 5, the process of selecting the target recommended picture may be implemented as follows:

s501, attributing candidate recommended pictures with the same similarity in a target recommended picture set to the same group to obtain at least one target recommended picture subset;

s502, sorting at least one target recommended picture subset according to the number of candidate recommended pictures included in the target recommended picture subset;

s503, determining any candidate recommended picture in the highest-ranking target recommended picture subset as a target recommended picture.

Here, the candidate recommended pictures with the same corresponding similarity may be assigned to the same target recommended picture subset based on the similarity between any two candidate recommended pictures in the target recommended picture set, and then any one candidate recommended picture in the target recommended picture subset including the largest number of candidate recommended pictures may be determined as the target recommended picture.

In the information pushing method provided by the embodiment of the present disclosure, the similarity between any two candidate recommended pictures may be determined based on the similarity between the picture fingerprint features extracted from the two candidate recommended pictures, that is, the more similar the picture fingerprint features, the higher the corresponding similarity.

The fingerprint feature of the picture in the embodiment of the disclosure can be used as the identification feature of the picture, and can be realized by using a picture hash (hash) principle, that is, a candidate recommended picture can be used as input, after a hash function is applied, the hash value of the picture can be calculated based on the picture vision, and the hash values of similar pictures are similar. In this way, the embodiment of the disclosure can determine the similarity between two candidate recommended pictures based on the hash value similarity between any two candidate recommended pictures.

In the embodiment of the disclosure, there may be one or more target recommended picture subsets with highest ranks. When the target recommended picture subsets are multiple, firstly, determining ranking results of candidate media materials of any candidate recommended picture included in the target recommended picture subset in N candidate media materials according to any target recommended picture subset, then determining ranking results of the target recommended picture subset in each target recommended picture subset according to ranking results of candidate videos of each candidate recommended picture in N candidate media materials, and finally determining any target recommended picture in the target recommended picture subset with highest ranking as the target recommended picture.

In the embodiment of the disclosure, the N candidate media materials may be arranged in order, so that once the ranking result of the candidate media materials to which any candidate recommended picture included in one target recommended picture subset belongs in the N candidate media materials is determined, the ranking result of the target recommended picture subset in each target recommended picture subset may be determined.

For example, there are 10 candidate media materials and two target recommended picture subsets, the ranking result of the candidate media materials of each candidate recommended picture included in one target recommended picture subset in the 10 candidate media materials is distributed from 1 st to 5 th, the ranking result of the candidate media materials of each candidate recommended picture included in the other target recommended picture subset in the 10 candidate media materials is distributed from 6 th to 10 th, at this time, the target recommended picture subset with the ranking result distributed from 1 st to 5 th may be determined as the final target recommended picture subset, and the target recommended picture may be selected from the final target recommended picture subset.

Considering that the N candidate media materials determined in the information pushing method provided by the embodiment of the present disclosure may be sequentially arranged, here, as shown in fig. 6, the N candidate media materials may be determined as follows:

S601, acquiring corresponding media materials according to target recommended words;

s602, ranking the media materials according to the sequence of the relevance from high to low;

s603, determining the media materials of the first N famous grades as N candidate media materials corresponding to the target recommended word.

Here, the corresponding media materials may be obtained according to the target recommended word first, then the media materials may be ranked in order from large to small based on the relevance, and finally the media materials of the top N ranks may be determined as N candidate media materials corresponding to the target recommended word.

The media materials obtained according to the target recommended word may be obtained from an offline database, or may be media materials displayed on a display interface of a search APP by each terminal obtained in real time after the terminal initiates a search request, which is not particularly limited in the embodiments of the present disclosure.

After the media materials are acquired, the relevance between the target recommended word and the media materials can be determined based on the characteristic information of the media materials, the higher the relevance is, the higher the ranking of the corresponding media materials is, and N candidate media materials corresponding to the target recommended word can be determined by using the ranking result.

For the concrete expression form of the media material and the process of determining the correlation degree between the media material and the target recommended word, reference may be made to the concrete expression form of the candidate media material and the related description content of determining the correlation degree between the candidate media material and the target recommended word, which are not described herein.

In the method for pushing information provided in the embodiment of the present disclosure, different candidate media materials are also different in the manner of extracting candidate recommended pictures, and then, a method for extracting candidate recommended pictures by using candidate videos as candidate media materials and a scheme for extracting candidate recommended pictures by using candidate web page contents as candidate media materials are respectively described in the following two aspects.

In the first aspect, when the candidate video is determined to be the candidate media material, frame framing processing can be directly performed on the candidate video, and all obtained candidate pictures are determined to be candidate recommended pictures; the candidate videos can be intercepted according to a preset intercepting duration and/or a preset intercepting position, so that intercepted candidate videos are obtained, all candidate pictures included in the intercepted candidate videos are determined to be candidate recommended pictures, for example, for a candidate video with the total video length of 5s, the candidate videos with the total video length of 2 seconds before interception can be extracted; the key frame candidate pictures can be extracted from all candidate pictures included in the candidate video based on a key frame extraction mode, and then the extracted key frame candidate pictures are determined to be candidate recommended pictures.

In the second aspect, when determining that the web page content is a candidate media material, N web page contents corresponding to the target recommended word may be first captured; the N webpage contents carry M candidate recommended pictures, and then the M candidate recommended pictures are extracted from the N webpage contents.

In the embodiment of the disclosure, web content corresponding to each target recommended word may be crawled based on web crawler technology, and the higher the correlation degree between key information contained in the web content and the target recommended word is, the higher the corresponding ranking is.

Example two

As shown in fig. 7, a flowchart of a method for pushing information provided in a second embodiment of the present disclosure may be a terminal, where the method for pushing information includes the following steps:

s701, receiving a target recommended word and a target recommended picture; the target recommended pictures are determined from the candidate recommended pictures based on the similarity among M candidate recommended pictures, wherein the M candidate recommended pictures are extracted from N candidate media materials, and M is greater than or equal to N;

s702, carrying out association display on the target recommended words and the target recommended pictures.

Here, the terminal may perform the association presentation after receiving the target recommended word and the target recommended picture.

For the determination process of the target recommended picture, refer to the related description in the first embodiment, and will not be described herein. The associated presentation form of the target recommended word and the target recommended picture may be as shown in fig. 2 (a).

The terminal in the embodiment of the disclosure may also display the corresponding media material based on the selection operation of the user for the target recommended word, that is, after determining the search request sent by the user for the target recommended word and the target icon recommended picture, the server may feed back the media material to the terminal, so that the terminal performs material display.

The related description of the display process of the media material in the first embodiment is omitted herein, and the display manner of the related media material may be shown in fig. 2 (b).

Example III

Based on the foregoing embodiments, the embodiments of the present disclosure further provide an information pushing device, and the implementation of the following various devices may refer to the implementation of the method, and the repetition is not repeated.

Fig. 8 is a schematic diagram of an information pushing device according to a third embodiment of the present disclosure, where the device includes:

an obtaining module 801, configured to determine a target recommended word; n candidate media materials corresponding to the target recommended word are obtained, and M candidate recommended pictures are extracted from the N candidate media materials; wherein M is greater than or equal to N;

A determining module 802, configured to determine a target recommended picture from candidate recommended pictures based on a similarity between candidate recommended pictures;

and the pushing module 803 is configured to associate the target recommended word with the target recommended picture, and send the target recommended word and the target recommended picture to the terminal.

In one embodiment, the determining module 802 is configured to determine the target recommended picture from the candidate recommended pictures according to the following steps:

sorting at least one candidate recommended picture set according to the number of candidate recommended pictures included in the candidate recommended picture set;

and selecting a target recommended picture from the target recommended picture set.

In one embodiment, if the number of the first candidate recommended picture sets with the highest ranking is greater than or equal to 2, the determining module 802 is configured to determine the first candidate recommended picture set with the highest ranking as the target recommended picture set according to the following steps:

And determining a target recommended picture set from the first candidate recommended picture sets based on the correlation between at least one candidate media material corresponding to each first candidate recommended picture set and the target recommended word.

In one embodiment, the determining module 802 is configured to determine the target recommended picture set from the first candidate recommended picture set according to the following steps:

for each first candidate recommended picture set, determining the number of candidate recommended pictures in the first candidate recommended set included in at least one corresponding candidate media material, and respectively generating the weight of each at least one candidate media material;

and determining a target recommended picture set from the first candidate recommended picture sets based on the correlation of at least one candidate media material corresponding to each first candidate recommended picture set and the target recommended word and the weight of each at least one candidate media material.

In one embodiment, the determining module 802 is configured to obtain at least one candidate recommended picture set according to the following steps:

Wherein the preset conditions include at least one of the following conditions:

the similarity is greater than a first threshold;

In one embodiment, the determining module 802 is configured to select a target recommended picture from the target recommended picture set according to the following steps:

determining the similarity between any candidate recommended picture in the target recommended picture set and other candidate recommended pictures, and obtaining a similarity set corresponding to the target recommended picture set;

if the number of the similarities in the similarity set is 1, or the number of the similarities in the similarity set is more than or equal to 2, and the absolute value of the difference value between the similarities is less than or equal to a second threshold, determining any candidate recommended picture in the target recommended picture set as a target recommended picture;

if the number of the similarities in the similarity set is greater than or equal to 2 and the absolute value of the difference between the similarities is greater than a second threshold, attributing candidate recommended pictures with the same similarity in the target recommended picture set to the same group to obtain at least one target recommended picture subset; sorting at least one target recommended picture subset according to the number of candidate recommended pictures included in the target recommended picture subset; and determining any candidate recommended picture in the highest-ranking target recommended picture subset as the target recommended picture.

In one embodiment, if the target recommended picture subset is a plurality of; a determining module 802, configured to determine a target recommended picture according to the following steps:

determining ranking results of candidate media materials to which any candidate recommended picture included in each target recommended picture subset belongs in N candidate media materials according to any target recommended picture subset in each target recommended picture subset; determining the ranking results of the target recommendation picture subset in each target recommendation picture subset according to the ranking results of the candidate media materials to which each candidate recommendation picture belongs in N candidate videos;

In one embodiment, the determining module 802 is configured to determine the similarity between candidate recommended pictures according to the following steps:

In one embodiment, the obtaining module 801 is configured to obtain N candidate media materials corresponding to the target recommended word according to the following steps:

ranking the media materials according to the sequence from the high correlation degree to the low correlation degree;

and determining the media materials of the first N ranks as N candidate media materials corresponding to the target recommended word.

In one embodiment, the candidate media materials include candidate videos, and the obtaining module 801 is configured to extract M candidate recommended pictures from the N candidate media materials according to the following steps:

and extracting key frame candidate pictures from all candidate pictures included in any one of the N candidate videos, and determining the key frame candidate pictures in the extracted N candidate videos as M candidate recommended pictures.

In one implementation, the candidate media material includes web page content; an obtaining module 801, configured to determine M candidate recommended pictures according to the following steps:

Capturing N webpage contents corresponding to the target recommended words; m candidate recommended pictures are carried in the N webpage contents;

m candidate recommended pictures are extracted from N webpage contents.

As shown in fig. 9, a schematic diagram of another information pushing device according to a third embodiment of the present disclosure is provided, where the device includes:

the receiving module 901 is used for receiving a target recommended word and a target recommended picture; the target recommended pictures are determined from the candidate recommended pictures based on the similarity among M candidate recommended pictures, wherein the M candidate recommended pictures are extracted from N candidate media materials, and M is greater than or equal to N;

and the display module 902 is used for carrying out association display on the target recommended words and the target recommended pictures.

Example IV

A fourth embodiment of the present disclosure provides a computer device, which may be a server or a terminal, where the server is used as the computer device, as shown in fig. 10, and the computer device includes: processor 1001, storage medium 1002, and bus 1003, storage medium 1002 stores machine-readable instructions executable by processor 1001 (such as execution instructions corresponding to acquisition module 801, determination module 802, and pushing module 803 in the information pushing apparatus of fig. 8), when the computer device is running, processor 1001 communicates with storage medium 1002 via bus 1003, and when the machine-readable instructions are executed by processor 1001, the following process is performed:

Determining a target recommended word; n candidate media materials corresponding to the target recommended word are obtained, and M candidate recommended pictures are extracted from the N candidate media materials; wherein M is greater than or equal to N;

and correlating the target recommended words with the target recommended pictures and sending the target recommended words and the target recommended pictures to the terminal.

In an alternative embodiment, in the instructions executed by the processor 1001, determining, based on the similarity between candidate recommended pictures, the target recommended picture from the candidate recommended pictures includes:

In an alternative embodiment, if the number of the first candidate recommended picture sets with the highest ranking is greater than or equal to 2, the determining, in the instruction executed by the processor 1001, the first candidate recommended picture set with the highest ranking as the target recommended picture set includes:

In an alternative embodiment, in the instructions executed by the processor 1001, determining the target recommended picture set from the first candidate recommended picture sets based on the correlation between at least one candidate media material corresponding to each first candidate recommended picture set and the target recommended word includes:

In an optional embodiment, in the instruction executed by the processor 1001, the grouping the M candidate recommended pictures based on the similarity between the candidate recommended pictures to obtain at least one candidate recommended picture set includes:

wherein the preset conditions include at least one of the following conditions:

the similarity is greater than a first threshold;

In an alternative embodiment, in the instructions executed by the processor 1001, selecting the target recommended picture from the target recommended picture set includes:

In an alternative embodiment, if the target recommended picture subset is a plurality of target recommended pictures; in the instructions executed by the processor 1001, determining any candidate recommended picture in the highest-ranked target recommended picture subset as the target recommended picture includes:

In an alternative embodiment, in the instructions executed by the processor 1001, the similarity between candidate recommended pictures is determined according to the following steps:

In an alternative embodiment, in the instruction executed by the processor 1001, acquiring N candidate media materials corresponding to the target recommended word includes:

In an alternative embodiment, the candidate media materials include candidate videos, and the instructions executed by the processor 1001 extract M candidate recommended pictures from the N candidate media materials, including:

In an alternative embodiment, the candidate media material includes web page content; in the instructions executed by the processor 1001, N candidate media materials corresponding to the target recommended word are determined according to the following steps:

extracting M candidate recommended pictures from N candidate media materials according to the following steps:

m candidate recommended pictures are extracted from N webpage contents.

When the terminal is used as a computer device, as shown in fig. 11, the computer device includes: the device comprises a processor 1101, a storage medium 1102 and a bus 1103, wherein the storage medium 1102 stores machine readable instructions executable by the processor 1101 (such as execution instructions corresponding to the receiving module 901 and the presenting module 902 in the information pushing device in fig. 9), when the computer device is running, the processor 1101 communicates with the storage medium 1102 through the bus 1103, and when the machine readable instructions are executed by the processor 1101, the following processing is performed:

and carrying out association display on the target recommended words and the target recommended pictures.

The disclosed embodiments also provide a computer readable storage medium having a computer program stored thereon, which when executed by the processor 1001 performs the steps of the method for information pushing provided in the first embodiment described above, or when executed by the processor 1101 performs the steps of the method for information pushing provided in the second embodiment described above.

Specifically, the storage medium can be a general storage medium, such as a mobile disk, a hard disk, and the like, and when the computer program on the storage medium is run, the method for pushing information can be executed, so that the problem of poor display effect existing in the related art that only search words are recommended is solved, and further, information pushing is realized in a combined display mode of texts and pictures, and the effect of the display effect is improved.

It will be clearly understood by those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described system and apparatus may refer to corresponding procedures in the method embodiments, and will not be described in detail in this disclosure. In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices, and methods may be implemented in other manners. The above-described apparatus embodiments are merely illustrative, and the division of the modules is merely a logical function division, and there may be additional divisions when actually implemented, and for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some communication interface, indirect coupling or communication connection of devices or modules, electrical, mechanical, or other form.

The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in each embodiment of the present disclosure may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a non-volatile computer readable storage medium executable by a processor. Based on such understanding, the technical solution of the present disclosure may be embodied in essence or a part contributing to the prior art or a part of the technical solution, or in the form of a software product stored in a storage medium, including several instructions to cause a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in the embodiments of the present disclosure. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.

The foregoing is merely a specific embodiment of the disclosure, but the protection scope of the disclosure is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the disclosure, and it should be covered in the protection scope of the disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.

Claims

1. A method of information pushing, the method comprising:

determining a target recommended word; acquiring N candidate media materials corresponding to the target recommended word, and extracting M candidate recommended pictures from the N candidate media materials; wherein M is greater than or equal to N; the candidate media materials comprise video materials, webpage materials and multimedia materials containing pictures;

determining a target recommended picture from the candidate recommended pictures based on the similarity between the candidate recommended pictures; the target recommendation picture is used for assisting in selecting the target recommendation word so as to initiate searching based on the target recommendation word;

2. The method of claim 1, wherein the determining a target recommended picture from the candidate recommended pictures based on the similarity between the candidate recommended pictures comprises:

3. The method of claim 2, wherein determining the highest ranked first candidate recommended picture set as the target recommended picture set if the highest ranked first candidate recommended picture set is greater than or equal to 2, comprises:

4. The method of claim 3, wherein the determining the target recommended picture set from the first candidate recommended picture sets based on the relevance of at least one candidate media material corresponding to each of the first candidate recommended picture sets to the target recommended word comprises:

5. The method according to any one of claims 2-4, wherein grouping M candidate recommended pictures based on the similarity between the candidate recommended pictures to obtain at least one candidate recommended picture set includes:

Wherein the preset conditions include at least one of the following conditions:

the similarity is greater than a first threshold;

6. The method of any of claims 2-4, wherein the selecting the target recommended picture from the set of target recommended pictures comprises:

7. The method of claim 6, wherein if the target recommended picture subset is a plurality of; determining any candidate recommended picture in the highest-ranking target recommended picture subset as the target recommended picture, including:

8. The method according to any one of claims 1-4, wherein the similarity between candidate recommended pictures is determined according to the following steps:

9. The method according to any one of claims 1-4, wherein the obtaining N candidate media materials corresponding to the target recommended word includes:

10. The method of any of claims 1-4, wherein the candidate media materials comprise candidate videos, and wherein extracting M candidate recommended pictures from the N candidate media materials comprises:

11. The method of any one of claims 1-4, wherein the candidate media material comprises web page content; n candidate media materials corresponding to the target recommended word are determined according to the following steps:

and extracting M candidate recommended pictures from the N webpage contents.

12. A method of information pushing, the method comprising:

receiving a target recommended word and a target recommended picture; the target recommended pictures are determined from the candidate recommended pictures based on the similarity among M candidate recommended pictures, wherein the M candidate recommended pictures are extracted from N candidate media materials, M is greater than or equal to N, and the N candidate media materials correspond to the target recommended words; the target recommended picture is used for assisting in selecting the target recommended word so as to initiate searching based on the target recommended word; the candidate media materials comprise video materials, webpage materials and multimedia materials containing pictures;

13. An apparatus for pushing information, the apparatus comprising:

the acquisition module is used for determining target recommended words; acquiring N candidate media materials corresponding to the target recommended word, and extracting M candidate recommended pictures from the N candidate media materials; wherein M is greater than or equal to N; the candidate media materials comprise video materials, webpage materials and multimedia materials containing pictures;

the determining module is used for determining a target recommended picture from the candidate recommended pictures based on the similarity between the candidate recommended pictures; the target recommendation picture is used for assisting in selecting the target recommendation word so as to initiate searching based on the target recommendation word;

14. An apparatus for pushing information, the apparatus comprising:

the receiving module is used for receiving the target recommended words and the target recommended pictures; the target recommended pictures are determined from the candidate recommended pictures based on the similarity among M candidate recommended pictures, wherein the M candidate recommended pictures are extracted from N candidate media materials, M is greater than or equal to N, and the N candidate media materials correspond to the target recommended words; the target recommended picture is used for assisting in selecting the target recommended word so as to initiate searching based on the target recommended word; the candidate media materials comprise video materials, webpage materials and multimedia materials containing pictures;

15. A computer device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating over the bus when the computer device is running, the machine-readable instructions when executed by the processor performing the steps of the method of information pushing according to any of claims 1 to 12.

16. A computer-readable storage medium, characterized in that the computer-readable storage medium has stored thereon a computer program which, when run by a processor, performs the steps of the method of information pushing according to any of claims 1 to 12.