CN105095431A - Method and device for pushing videos based on behavior information of user - Google Patents
Method and device for pushing videos based on behavior information of user Download PDFInfo
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Abstract
The application discloses a method and device for pushing videos based on behavior information of a user. The method comprises following steps: acquiring behavior information of the user to videos; generating parameters of interest of the user based on behavior information of the user; acquiring the pre-set number of videos satisfying parameters of interest; and pushing acquired videos to the user. According to the technical scheme of the embodiment, the method and device for pushing videos based on behavior information of the user have following beneficial effects: parameters of interest of the user can be generated from a great number of behavior information of the user and videos are recommended according to interests of the user; and according to the method for pushing videos based on behavior information of the user, behavior information of the user is generated while much behavior information is used so that accuracy for recommendation of videos based on parameters of interest is improved.
Description
Technical field
The application relates to technical field of the computer network, is specifically related to video push technical field, particularly relates to the method and apparatus of the behavioural information pushing video according to user.
Background technology
Along with the development of internet, applications, various Internet video is that the study of user and amusement provide a great convenience, and user can obtain the video that oneself needs at any time from network.
At present, for the recommendation of video in conventional internet application, mostly recommend based on the video of current popular video, user's collection or video scoring.
But only analyze user preferences according to the video of current popular video, user's collection or video scoring thus carry out video recommendations in conventional internet application, the data utilized during analysis are less, thus cause the precision of video recommended for user poor.
Summary of the invention
In view of above-mentioned defect of the prior art or deficiency, expect that can provide a kind of utilizes the scheme that data are many, recommendation precision is high.In order to realize above-mentioned one or more object, this application provides the method and apparatus of the behavioural information pushing video according to user.
First aspect, this application provides the method for the behavioural information pushing video according to user, the method comprises:
Obtain the behavioural information of user for video, wherein, described behavioural information obtains according to following one or more information: search information, click information, viewing information, score information and Information on Collection;
According to the behavioural information of user, generate the interest parameter of user, wherein, described interest parameter comprises following one or more parameter: the preference information of the scoring of video temperature, video, video classification, actor information, product area, produce time and user's owning user group;
Video that obtain predetermined number, that meet described interest parameter;
The video obtained is pushed to user.
Second aspect, this application provides the device of the behavioural information pushing video according to user, this device comprises:
Behavioural information acquiring unit, for obtaining the behavioural information of user for video, wherein, described behavioural information obtains according to following one or more information: search information, click information, viewing information, score information and Information on Collection;
Interest parameter generation unit, for the behavioural information according to user, generate the interest parameter of user, wherein, described interest parameter comprises following one or more parameter: the preference information of the scoring of video temperature, video, video classification, actor information, product area, produce time and user's owning user group;
Video acquisition unit, for obtain predetermined number, the video that meets described interest parameter;
Video push unit, for pushing the video obtained to user.
The method and apparatus of the behavioural information pushing video according to user that the application provides, can generate the interest parameter of user from a large amount of user behavior information, then recommends video according to the interest parameter of user.The method and apparatus of the behavioural information pushing video according to user of the application's embodiment, when the behavioural information of analysis user is to generate interest parameter, employs more behavioural information, improves the precision recommending video according to interest parameter.
Accompanying drawing explanation
By reading the detailed description to non-limiting example done with reference to the following drawings, the other features, objects and advantages of the application will become more obvious:
Fig. 1 shows the exemplary system architecture can applying the embodiment of the present application;
Fig. 2 shows an exemplary process diagram of the method for the behavioural information pushing video according to user according to the embodiment of the present application;
Fig. 3 shows the exemplary process diagram of an embody rule scene of the method for the behavioural information pushing video according to user according to the embodiment of the present application;
Fig. 4 shows an exemplary process diagram of the method for the video obtained that pushes to user according to the embodiment of the present application;
Fig. 5 shows the exemplary block diagram of the weights according to the interest parameter preset in an embody rule scene of the embodiment of the present application;
Fig. 6 shows an exemplary process diagram of the device of the behavioural information pushing video according to user according to the embodiment of the present application.
Fig. 7 shows the structural representation of the computer system be suitable for for the terminal device or server realizing the embodiment of the present application.
Embodiment
Below in conjunction with drawings and Examples, the application is described in further detail.Be understandable that, specific embodiment described herein is only for explaining related invention, but not the restriction to this invention.It also should be noted that, for convenience of description, in accompanying drawing, illustrate only the part relevant to Invention.
It should be noted that, when not conflicting, the embodiment in the application and the feature in embodiment can combine mutually.Below with reference to the accompanying drawings and describe the application in detail in conjunction with the embodiments.
Please refer to Fig. 1, Fig. 1 shows the exemplary system architecture 100 can applying the embodiment of the present application.
As shown in Figure 1, system architecture 100 can comprise terminal device 101,102, network 103 and server 104.Network 103 in order to provide the medium of communication link between terminal device 101,102 and server 104.Network 103 can comprise various connection type, such as wired, wireless communication link or fiber optic cables etc.
User 110 can use terminal device 101,102 mutual by network 103 and server 104, with the response message etc. initiating solicited message or receive solicited message.Terminal device 101,102 can be provided with various video player, such as Android version video player, IOS version video player, webpage version video player etc.
Terminal device 101,102 can be various electronic equipment, includes but not limited to PC, smart mobile phone, intelligent watch, panel computer, personal digital assistant etc.
Server 104 can be to provide the server of various service.The process such as server can store the information received, analysis, and result is fed back to terminal device.
It should be noted that, the method of the behavioural information pushing video according to user that the embodiment of the present application provides can be performed by terminal device 101,102, also can be performed by server 104, can be arranged in terminal device 101,102 according to the device of the behavioural information pushing video of user, also can be arranged in server 104.In certain embodiments, user behavior information can obtain in terminal 101,102, according to the behavioural information of user generate user interest parameter, obtain predetermined number, the video that meets described interest parameter can carry out in server 104, can push the video obtained by terminal device 101,102 to user.Such as, when the behavioural information pushing video according to user, if network 103 is unobstructed, can by server 104 according to the behavioural information of user generate user interest parameter, obtain predetermined number, the high in the clouds video that meets described interest parameter, if do not have network or network 103 not smooth, can directly by terminal device 101,102 carry out according to the behavioural information of user generate user interest parameter, obtain predetermined number, the local video that meets described interest parameter.
Should be appreciated that, the number of the terminal device in Fig. 1, network and server is only schematic.According to realizing needs, the terminal device of arbitrary number, network and server can be had.
Please refer to Fig. 2, Fig. 2 shows an exemplary process diagram of the method for the behavioural information pushing video according to user according to the embodiment of the present application.
As shown in Figure 2, comprise according to the method 200 of the behavioural information pushing video of user:
First, in step 201, the behavioural information of user for video is obtained.
In the present embodiment, user obtains according to following one or more information for the behavioural information of video: search information, click information, viewing information, score information and Information on Collection.
Wherein, search information refers to the information of user search video, and the searching request information of such as user's input, can comprise the keyword such as video name and actor information in solicited message, can also comprise time, position etc. that request occurs.Search information can include but not limited to following one or more: text search information, phonetic search information and picture searching information.Click information refers to that user clicks the information of video, the time that the title, scoring, classification etc. of the video that such as user clicks and click occur, the position etc. of generation.Viewing information refers to that user watches the information of video, the time (comprising initial time and/or duration) that the classification, actor information, product area etc. of the video of such as user's viewing and viewing occur, the position etc. occurred.Score information refers to the scoring information of user to video, the position etc. that the number of times that the title of video of such as user's marking, classification, product time and marking occur, marking occur.Information on Collection refers to the information of the video that user collects, title, classification, the product address of the video of such as user's collection, the produce time of time and collection generation and the position etc. of generation.
When obtaining the behavioural information of user for video, only can obtain the real time data of active user for the behavioural information of video to improve data counting yield, alternatively or additionally, the historical data of user for the behavioural information of video can also be obtained to improve the quantity for the data analyzed, thus obtain analysis result more accurately.
In some alternatively implementation, behavioural information can comprise object of action information, object of action information take video as the information that object of action obtains, such as, can include but not limited to following one or more: the scoring of video name, video temperature, video, video classification, actor information, product area and product time etc.
Alternatively or additionally, behavioural information can also comprise behavior characteristic information, behavior characteristic information is the information that subordinate act itself is extracted, and such as, can include but not limited to following one or more: position etc. occurs for behavior title, behavior quantity, behavior time of origin and behavior.Wherein, behavior title refers to the title of user for the behavior of video, can include but not limited to following one or more: search, click, viewing, scoring and collection etc.
Then, in step 202., according to the behavioural information of user, the interest parameter of user can be generated.
In the present embodiment, the interest parameter of user indicates user to the preference profiles of video, can include but not limited to following one or more parameter: the preference information etc. of the scoring of video temperature, video, video classification, actor information, product area, produce time and user's owning user group.
Wherein, video temperature refers to the number of times that video is viewed and pouplarity; Video scoring refers to the score value that video is chosen by customer group; Video classification refers to the classification that video is divided according to interior perhaps form etc.; Actor information refers to the information etc. of protagonist and other performers comprised in video; Product area refers to the area of manufacturing video; The product time refers to video capture or disclosed time; The preference information of user's owning user group refers to according to user the preference information to video of the preference of video to the customer group formed after user clustering.
Parameters in above-mentioned interest parameter, can classify according to the sort key word of artificial setting, also can classify based on the sort key word in historical experience.
For video classification, based on the sort key word classification in historical experience, usually can comprise following one or more: TV play, film, variety, animation, legal system, physical culture, make laughs, play, live and network is acute.
Wherein, movies category can comprise following one or more subclass: love, comedy, action, terror, science fiction, war, terrible sheet, crime, the story of a play or opera, ancient costume, swordsman and animation etc.; Television category can comprise following one or more subclass: war, ancient costume, anti-Japanese, spy war, policemen and bandits, swordsman, rural area, comedy, idol, describing love affairs, family, mythology, city etc.; Variety classification can comprise following one or more subclass: select-elite, interview, reality TV show, make laughs, play, talk show, job market, Eight Diagrams, life etc.; Animation classification can comprise following one or more subclass: juvenile, magic, machine war, children's stories, make laughs, beauty, take a risk, pursue a goal with determination, warm blood, sports, terror, intelligence development, classics etc.
Then, in step 203, video that obtain predetermined number, that meet interest parameter.
In the present embodiment, the video meeting interest parameter of acquisition refers to and analyzes user to after the preference of video according to the behavioral data of user, and what obtain from video library meets the video of user to the preference of video.
When acquisition meets the video of interest parameter, the video meeting single interest parameter can be obtained, such as, in interest parameter, select the video of the predetermined number that rank is the highest everyhow; Also the video of satisfied many-sided interest parameter can be obtained.Such as, consider many-sided interest parameter of demand fulfillment thus choose the video of predetermined number.Wherein, for different interest parameter, the quantity of the video chosen for identical predetermined number, also can choose different quantity according to the weights of each interest parameter preset.Above-mentioned predetermined number can be the quantity manually pre-entered, also can be obtain quantity according to the behavioural information statistics of user, such as, user is within a period of time, first three literature and art class videos have been searched for, have viewed the class video of making laughs produced in somewhere afterwards, thus the quantity of the video obtained can be: what produced in literature and art class video and somewhere make laughs class video, both ratios can be 3:1.
In some alternatively implementation, video that obtain predetermined number, that meet interest parameter can include but not limited to following arbitrary: according to video temperature, choose the video that predetermined number meets interest parameter; According to video scoring, choose the video that predetermined number meets interest parameter; And random selecting predetermined number meets the video of interest parameter.
Afterwards, in step 204, the video obtained is pushed to user.
In the present embodiment, obtain above-mentioned predetermined number, after the video that meets interest parameter, push the video obtained to user.
When pushing, can push according to after appraisal result sequence after the scoring of obtained video synthesis; Also obtained video can be classified according to each side interest parameter and the pusher that sorts send; The video of acquisition can also be pushed at random.
In one of the present embodiment concrete application scenarios, can according to the search information pushing video of user, video name " brave mother cat father " can be obtained according to the keyword of user search " brave mother cat father ", and according to the continuous viewing behavioural analysis of user's nearest fortnight, can judge that the interest parameter of this user is as there being the TV play chasing after acute behavior, no matter whether collection of drama finishes, and all will the TV play entity chasing after acute behavior be had to recommend user.
In another concrete application scenarios of the present embodiment, user is had to the variety show of viewing continuously, judge that the interest parameter of user is the up-to-date variety show that can watch continuously, then by judging whether variety finishes the update time of video library, for user recommend to upgrade and have the variety show of continuous viewing behavior, priority is improved to the variety show emphasis upgraded in the near future.
Fig. 3 shows the exemplary process diagram of an embody rule scene of the method for the behavioural information pushing video according to user according to the embodiment of the present application.
As shown in Figure 3, in the 3rd the concrete application scenarios of the present embodiment, user searched for respectively within a period of time in the morning on Sunday scoring be more than 9.0 video, have viewed first three popular video of rank that webpage version player recommends, and collected the class video of making laughs that performer A performs.After getting the above-mentioned behavioural information of user, namely can generate the interest parameter of user, also the preference of user to video comprises: video scoring more than 9.0, video temperature rank first three, performer A, class of making laughs video, with user have other people in same customer group of liking the class video of making laughs of performer B also liked; The quantitative proportion of the video obtained can be determined afterwards according to the time spent in user behavior information: the first five video, five videos of scoring more than 9.0, three videos of performer A, two videos of performer B and other class three videos of making laughs of video temperature rank, and the video of acquisition is recommended to user.
The method of the behavioural information pushing video of the user provided according to the above embodiments of the present application, when the behavioural information analyzing user is to generate interest parameter, can uses more behavioural information, improve the precision according to interest parameter recommendation video.
An exemplary process diagram of the method for the video obtained that pushes to user according to the embodiment of the present application is shown with further reference to Fig. 4, Fig. 4.
As shown in Figure 4, the method 400 pushing the video obtained to user can include but not limited to:
In step 401, according to the weights of interest parameter and default interest parameter, calculate the recommendation score value of the video obtained.
Wherein, the weights of interest parameter preset, can for the weights of the interest parameter of artificial input received, and also can be the weights set based on the statistics of the behavioural information to history.
In some alternatively implementation, the weights of above-mentioned interest parameter can be obtained by following either type: the weights obtaining the interest parameter of input; Obtain the weights of the interest parameter determined based on the behavioural information of user; And obtain the weights adding up the interest parameter obtained based on the behavioural information of user's owning user group.
Wherein, when obtaining the weights of interest parameter of input, the weights inputted after manually discriminatory analysis being carried out to behavioral parameters and interest parameter can be obtained.Such as, in above-mentioned application scenarios, user watches first three time of popular video of rank that webpage version player recommends and is far longer than the video that search score is more than 9.0, search score is be greater than the class video of making laughs collected performer A and performed the time of the video of more than 9.0, the weights of interest parameter that then artificial judgment generates close and are: first three the weights > performer A> performer B> of weights > video scoring more than 9.0 of video temperature rank makes laughs class video, and according to the weights assignment of artificial experience to interest parameter.
When obtaining the weights of the interest parameter determined based on the behavioural information of user, the behavioural information in user's a period of time can be obtained, the behavioural information obtained being added up to the distribution situation of the interest parameter drawing user, thus determining the weights of interest parameter.Such as, user continues the comedy class film of viewing Hongkong within a period of time, the weights that the comedy class film then obtaining Hongkong according to the behavioural information of user statistics takies the video of family viewing are 1.0, then the weights setting the interest parameter of user are: the weights of the comedy class film of Hongkong are 1.0.
Obtain add up the weights of the interest parameter obtained based on the behavioural information of user's owning user group time, the weights of the interest parameter obtained after can obtaining the behavioural information cluster of the customer group with user with identical hobby.Such as, user watches and explores the animation of intelligence development class within a period of time; Other users of identical behavioural information are had also to like the cartoon of humorous warm blood class with him, and add up according to the behavioural information in customer group a period of time the weights that the animation of exploration intelligence development class, the cartoon of humorous warm blood class and other cartoons that obtain account for the video of customer group viewing and be respectively 0.7,0.2 and 0.1, then using the weights of the weights of the interest parameter of customer group as the interest parameter of user, the interest weights also namely setting user are respectively: explore the animation of intelligence development class, the weights of the cartoon of humorous warm blood class and other cartoons are respectively 0.7,0.2 and 0.1.
When calculating the score value of each candidate video, the weight can considering the parameter that this video meets and the recommendation weight preset, such as a video meets this parameter of actor information, the recommendation weight of this parameter is performer A0.7, performer B0.3, there is (performer A, performer C, performer D, performer E, performer F) 5 protagonist candidate video " XXXX " the inside, assuming that the priori weight of this parameter of actor information is 0.3, then " XXXX " must be divided in this parameter of actor information: 0.7 × 1/5 × 0.3=0.042.According to the fancy grade of user to other interest parameter, the score value of the video obtained can be calculated, the video obtained from height to low recommendation according to score value afterwards.
The weights of default interest parameter are described below in conjunction with Fig. 5.
Fig. 5 shows the exemplary block diagram of the weights according to the interest parameter preset in the concrete application scenarios of the embodiment of the present application one.
Exemplary, as shown in Figure 5, in one of the present embodiment concrete application scenarios, the interest parameter of user can concentrate on video classification, and video classification can comprise: the large class of TV play classification, movies category, animation classification and variety classification four.In this four large class, the interest parameter of user concentrates on again movies category and variety classification, and wherein, movies category can comprise following subclass: classification, area and performer; Variety classification can comprise performer's subclass and type subclass.In video classification, movies category has accounted for the weight of video classification 0.7, and variety classification has accounted for the weight of video classification 0.3.Further, if the movies category of user's viewing is according to class discrimination, then comedy categories and action classification and love classification account for the weight of classification is respectively 0.2,0.4 and 0.4; If distinguish according to area, interiorly, the weight of the U.S. and occupation of land district, Hong Kong classification is respectively 0.5,0.2 and 0.3; If distinguish according to performer, then the weight that performer A and performer B accounts for performer is respectively 0.7 and 0.3; In like manner, if the variety classification of user's viewing is distinguished according to performer, then the weight of performer C is 1.0; If according to type classification, then outdoor and interview accounts for the weight of type is respectively 0.5.
Those skilled in the art are to be understood that, the weights of the interest parameter in above-mentioned Fig. 5 are only the exemplary description of the embodiment of the present application, the application is not limited to this, and the setting of interest parameter and weights thereof can also with reference to the setting of the interest parameter described in above-mentioned Fig. 2 to Fig. 4 and weights thereof.
Return Fig. 4, in step 402, can push after the sequence of obtained video to low from height according to recommendation score value.
In the present embodiment, after going out the recommendation score value of obtained video according to the weight computing of above-mentioned interest parameter and default interest parameter, can sort to band pushing video to low from height according to recommendation score value, push according to clooating sequence the video obtained again afterwards.
Please refer to Fig. 6, Fig. 6 shows an exemplary process diagram of the device of the behavioural information pushing video according to user according to the embodiment of the present application.
As shown in Figure 6, the device 600 according to the behavioural information pushing video of user can include but not limited to: behavioural information acquiring unit 610, interest parameter generation unit 620, video acquisition unit 630 and video push unit 640.
Wherein, behavioural information acquiring unit 610, is configured for and obtains the behavioural information of user for video.Interest parameter generation unit 620, is configured for the behavioural information according to user, generates the interest parameter of user.Video acquisition unit 630, is configured for video that obtain predetermined number, that meet interest parameter.Video push unit 640, is configured for and pushes to user the video obtained.
Wherein, the behavioural information that behavioural information acquiring unit 610 obtains obtains according to following one or more information: search information, click information, viewing information, score information and Information on Collection.Search information can include but not limited to following one or more: text search information, phonetic search information and picture searching information.The behavioural information that behavioural information acquiring unit 610 obtains can include but not limited to: object of action information, can include but not limited to following one or more: the scoring of video name, video temperature, video, video classification, actor information, product area and the time of product; And/or behavior characteristic information, can include but not limited to following one or more: position occurs for behavior title, behavior quantity, behavior time of origin and behavior, and behavior title can include but not limited to following one or more: search, click, viewing, scoring and collection.Above-mentioned behavioural information can include but not limited to: current behavior information and/or historical behavior information.
Above-mentioned interest parameter can include but not limited to following one or more parameter: the preference information of the scoring of video temperature, video, video classification, actor information, product area, produce time and user's owning user group.
In some implementations, video acquisition unit 630 wraps but is not limited to following arbitrary (not shown): choose unit according to temperature, for according to video temperature, choose the video that predetermined number meets interest parameter; Choose unit according to scoring, for according to video scoring, choose the video that predetermined number meets interest parameter; And random selecting unit, what meet interest parameter for random selecting predetermined number treats pushing video.
In some implementations, video push unit 640 can include but not limited to: score value computing unit 641 and sequence push unit 642.Wherein, score value computing unit 641, is configured for the weights according to interest parameter and default interest parameter, calculates the recommendation score value of the video obtained.Sequence push unit 642, is configured for and pushes after the sequence of obtained video to low from height according to recommendation score value.
In some implementations, the weights of the interest parameter of score value computing unit 641 are by obtaining (not shown) with lower unit: input block, determining unit and statistic unit.
Wherein, input block is configured for the weights of the interest parameter obtaining input; Determining unit is configured for the weights obtaining the interest parameter determined based on the behavioural information of user; And statistic unit is configured for the weights obtaining and add up the interest parameter obtained based on the behavioural information of user's owning user group.
Should be appreciated that all unit recorded in device 600 are corresponding with each step in the method described with reference to figure 2.Thus, the unit that the operation described for the method for the behavioural information pushing video according to user above and feature are equally applicable to device 600 and wherein comprise, does not repeat them here.Corresponding units in device 600 can cooperatively interact the scheme realizing the embodiment of the present application with the unit in terminal device and/or server.
The device of the behavioural information pushing video according to user that the above embodiments of the present application provide, when the behavioural information of analysis user is to generate interest parameter, employs more behavioural information, improves the precision recommending video according to interest parameter.
Below with reference to Fig. 7, it illustrates the structural representation of the computer system 700 of terminal device or the server be suitable for for realizing the embodiment of the present application.
As shown in Figure 7, computer system 700 comprises CPU (central processing unit) (CPU) 701, and it or can be loaded into the program random access storage device (RAM) 703 from storage area 708 and perform various suitable action and process according to the program be stored in ROM (read-only memory) (ROM) 702.In RAM703, also store system 700 and operate required various program and information.CPU701, ROM702 and RAM703 are connected with each other by bus 704.I/O (I/O) interface 705 is also connected to bus 704.
I/O interface 705 is connected to: the importation 706 comprising keyboard, mouse etc. with lower component; Comprise the output 707 of such as cathode-ray tube (CRT) (CRT), liquid crystal display (LCD) etc. and loudspeaker etc.; Comprise the storage area 708 of hard disk etc.; And comprise the communications portion 709 of network interface unit of such as LAN card, modulator-demodular unit etc.Communications portion 709 is via the network executive communication process of such as the Internet.Driver 710 is also connected to I/O interface 705 as required.Detachable media 711, such as disk, CD, magneto-optic disk, semiconductor memory etc., be arranged on driver 710 as required, so that the computer program read from it is mounted into storage area 708 as required.
Especially, according to embodiment of the present disclosure, the process that reference flow sheet describes above may be implemented as computer software programs.Such as, embodiment of the present disclosure comprises a kind of computer program, and it comprises the computer program visibly comprised on a machine-readable medium, and described computer program comprises the program code for the method shown in flowchart.In such embodiments, this computer program can be downloaded and installed from network by communications portion 709, and/or is mounted from detachable media 711.
Process flow diagram in accompanying drawing and block diagram, illustrate according to the architectural framework in the cards of the system of various embodiments of the invention, method and computer program product, function and operation.In this, each square frame in process flow diagram or block diagram can represent a part for module, program segment or a code, and a part for described module, program segment or code comprises one or more executable instruction for realizing the logic function specified.Also it should be noted that at some as in the realization of replacing, the function marked in square frame also can be different from occurring in sequence of marking in accompanying drawing.Such as, in fact the square frame that two adjoining lands represent can perform substantially concurrently, and they also can perform by contrary order sometimes, and this determines according to involved function.Also it should be noted that, the combination of the square frame in each square frame in block diagram and/or process flow diagram and block diagram and/or process flow diagram, can realize by the special hardware based system of the function put rules into practice or operation, or can realize with the combination of specialized hardware and computer instruction.
Be described in unit involved in the embodiment of the present application to be realized by the mode of software, also can be realized by the mode of hardware.Described unit also can be arranged within a processor, such as, can be described as: a kind of processor comprises behavioural information acquiring unit, interest parameter generation unit, video acquisition unit and video push unit.Wherein, the title of these unit does not form the restriction to this unit itself under certain conditions, and such as, behavioural information acquiring unit can also be described to " for obtaining the unit of user for the behavioural information of video ".
As another aspect, present invention also provides a kind of computer-readable recording medium, this computer-readable recording medium can be the computer-readable recording medium comprised in device described in above-described embodiment; Also can be individualism, be unkitted the computer-readable recording medium allocated in terminal.Described computer-readable recording medium stores more than one or one program, and described program is used for performance description in the method for the behavioural information pushing video according to user of the application by one or more than one processor.
More than describe and be only the preferred embodiment of the application and the explanation to institute's application technology principle.Those skilled in the art are to be understood that, invention scope involved in the application, be not limited to the technical scheme of the particular combination of above-mentioned technical characteristic, also should be encompassed in when not departing from described inventive concept, other technical scheme of being carried out combination in any by above-mentioned technical characteristic or its equivalent feature and being formed simultaneously.The technical characteristic that such as, disclosed in above-mentioned feature and the application (but being not limited to) has similar functions is replaced mutually and the technical scheme formed.
Claims (14)
1. according to a method for the behavioural information pushing video of user, it is characterized in that, described method comprises:
Obtain the behavioural information of user for video, wherein, described behavioural information obtains according to following one or more information: search information, click information, viewing information, score information and Information on Collection;
According to the behavioural information of user, generate the interest parameter of user, wherein, described interest parameter comprises following one or more parameter: the preference information of the scoring of video temperature, video, video classification, actor information, product area, produce time and user's owning user group;
Video that obtain predetermined number, that meet described interest parameter;
The video obtained is pushed to user.
2. method according to claim 1, is characterized in that, describedly pushes to user the video obtained and comprises:
According to the weights of described interest parameter and default interest parameter, calculate the recommendation score value of the video obtained;
Push to low after the sequence of obtained video from height according to described recommendation score value.
3. method according to claim 2, is characterized in that, the weights of described interest parameter are obtained by following either type:
Obtain the weights of the interest parameter of input;
Obtain the weights of the interest parameter determined based on the behavioural information of user; And
Obtain the weights adding up the interest parameter obtained based on the behavioural information of user's owning user group.
4., according to the method one of claims 1 to 3 Suo Shu, it is characterized in that, described acquisition predetermined number, the video that meets described interest parameter comprises following arbitrary:
According to video temperature, choose the video that predetermined number meets described interest parameter;
According to video scoring, choose the video that predetermined number meets described interest parameter; And
Random selecting predetermined number meets the video of described interest parameter.
5. method according to claim 1, is characterized in that, described behavioural information comprises:
Object of action information, comprises following one or more: the scoring of video name, video temperature, video, video classification, actor information, product area and the time of product; And/or
Behavior characteristic information, comprises following one or more: position occurs for behavior title, behavior quantity, behavior time of origin and behavior, and described behavior title comprises following one or more: search, click, viewing, scoring and collection.
6. method according to claim 1, is characterized in that, described search information comprises following one or more: text search information, phonetic search information and picture searching information.
7. method according to claim 1, is characterized in that, described behavioural information comprises: current behavior information and/or historical behavior information.
8. according to a device for the behavioural information pushing video of user, it is characterized in that, described device comprises:
Behavioural information acquiring unit, for obtaining the behavioural information of user for video, wherein, described behavioural information obtains according to following one or more information: search information, click information, viewing information, score information and Information on Collection;
Interest parameter generation unit, for the behavioural information according to user, generate the interest parameter of user, wherein, described interest parameter comprises following one or more parameter: the preference information of the scoring of video temperature, video, video classification, actor information, product area, produce time and user's owning user group;
Video acquisition unit, for obtain predetermined number, the video that meets described interest parameter;
Video push unit, for pushing the video obtained to user.
9. device according to claim 8, is characterized in that, described video push unit comprises:
Score value computing unit, for the weights according to described interest parameter and default interest parameter, calculates the recommendation score value of the video obtained;
Sequence push unit, for pushing to low after the sequence of obtained video from height according to described recommendation score value.
10. device according to claim 9, is characterized in that, the weights of the interest parameter of described score value computing unit are obtained by following arbitrary unit:
Input block, for obtaining the weights of the interest parameter of input;
Determining unit, the weights of the interest parameter that the behavioural information for obtaining based on user is determined; And
Statistic unit, adds up the weights of the interest parameter obtained for the behavioural information obtained based on user's owning user group.
The device that one of 11. according to Claim 8 to 10 are described, it is characterized in that, described video acquisition unit comprises following arbitrary:
Choose unit according to temperature, for according to video temperature, choose the video that predetermined number meets described interest parameter;
Choose unit according to scoring, for according to video scoring, choose the video that predetermined number meets described interest parameter; And
Random selecting unit, what meet described interest parameter for random selecting predetermined number treats pushing video.
12. devices according to claim 8, is characterized in that, the described behavioural information that described behavioural information acquiring unit obtains comprises:
Object of action information, comprises following one or more: the scoring of video name, video temperature, video, video classification, actor information, product area and the time of product; And/or
Behavior characteristic information, comprises following one or more: position occurs for behavior title, behavior quantity, behavior time of origin and behavior, and described behavior title comprises following one or more: search, click, viewing, scoring and collection.
13. devices according to claim 8, is characterized in that, the described search information of described behavioural information acquiring unit comprises following one or more: text search information, phonetic search information and picture searching information.
14. devices according to claim 8, is characterized in that, the described behavioural information of described behavioural information acquiring unit comprises: current behavior information and/or historical behavior information.
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| CN201510434312.8A CN105095431A (en) | 2015-07-22 | 2015-07-22 | Method and device for pushing videos based on behavior information of user |
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| CN201510434312.8A CN105095431A (en) | 2015-07-22 | 2015-07-22 | Method and device for pushing videos based on behavior information of user |
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