CN106294462A - A kind of method and system obtaining recommendation video - Google Patents
A kind of method and system obtaining recommendation video Download PDFInfo
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- CN106294462A CN106294462A CN201510293068.8A CN201510293068A CN106294462A CN 106294462 A CN106294462 A CN 106294462A CN 201510293068 A CN201510293068 A CN 201510293068A CN 106294462 A CN106294462 A CN 106294462A
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- G—PHYSICS
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/90—Details of database functions independent of the retrieved data types
- G06F16/95—Retrieval from the web
- G06F16/951—Indexing; Web crawling techniques
Abstract
The present invention is applicable to technical field of information processing, it is provided that a kind of method and system obtaining recommendation video, and described method includes: obtain the video collection of customer group viewing according to default screening conditions；Obtain video frequent item set according to default video support threshold from described video collection, and described video frequent item set is ranked up by described video support；Spark parallel algorithm based on Fp-growth obtains from the video frequent item set after sequence recommends video item collection.Obtain, by the invention it is possible to reduce, the computation complexity recommending video, reduce the calculating time.
Description
Technical field
The invention belongs to technical field of information processing, particularly relate to a kind of method and system obtaining and recommending video.
Background technology
Watching video in video website and have become as a part for people's life, existing video website is usual
It is that the historical record according to customer group viewing video recommends its video that may be interested.But, existing skill
Art, when obtaining recommendation video, needs to scan for whole video database according to historical record, amount of calculation
Huge, and the longest.
Summary of the invention
In consideration of it, the embodiment of the present invention provides a kind of method and system obtaining and recommending video, existing to solve
Technology obtain recommend video time, the amount of calculation existed is huge, the longest problem.
The embodiment of the present invention be achieved in that a kind of obtain recommend video method, described method include with
Lower step:
The video collection of customer group viewing is obtained according to default screening conditions；
Video frequent item set is obtained from described video collection according to default video support threshold, and to described
Video frequent item set is ranked up by described video support；
Spark parallel algorithm based on Fp-growth obtains from the video frequent item set after sequence recommends video
Item collection.
The another object of the embodiment of the present invention is to provide a kind of system obtaining and recommending video, described system bag
Include:
Video collection acquiring unit, for obtaining the video collection of customer group viewing according to the screening conditions preset；
Video frequent item set and sequence acquiring unit, for regarding from described according to the video support threshold preset
The video collection that frequency set acquiring unit obtains obtains video frequent item set, and to described video frequent item set
It is ranked up by described video support；
Recommend video item collection acquiring unit, for Spark parallel algorithm based on Fp-growth from described video
Video frequent item set after the sequence that frequent item set and sequence acquiring unit obtain obtains and recommends video item collection.
The embodiment of the present invention obtains the video collection of customer group viewing according to the screening conditions preset, and according in advance
If video support threshold from described video collection obtain video frequent item set, to described video frequent item set
It is ranked up by described video support, is finally based on the Spark parallel algorithm of Fp-growth after sequence
Video frequent item set obtains and recommends video item collection.Compared with prior art, the embodiment of the present invention needs basis
Described screening conditions and video support threshold first filter out video frequent item set, then based on Fp-growth
Spark parallel algorithm described video frequent item set carried out parallel computation, reduce to obtain and recommend video
Computation complexity, decreases the calculating time.
Accompanying drawing explanation
For the technical scheme being illustrated more clearly that in the embodiment of the present invention, below will be to embodiment or existing skill
In art description, the required accompanying drawing used is briefly described, it should be apparent that, the accompanying drawing in describing below is only
It is only some embodiments of the present invention, for those of ordinary skill in the art, is not paying creative labor
On the premise of dynamic property, it is also possible to obtain other accompanying drawing according to these accompanying drawings.
Fig. 1 is the flow chart obtaining recommendation video method that the embodiment of the present invention provides；
Fig. 2 is the structure chart obtaining recommendation video system that the embodiment of the present invention provides.
Detailed description of the invention
In order to make the purpose of the present invention, technical scheme and advantage clearer, below in conjunction with accompanying drawing and reality
Execute example, the present invention is further elaborated.Only should be appreciated that specific embodiment described herein
Only in order to explain the present invention, it is not intended to limit the present invention.
In order to technical solutions according to the invention are described, illustrate below by specific embodiment.
Embodiment one
It is illustrated in figure 1 the flow chart obtaining recommendation video method that the embodiment of the present invention provides, described method
Comprise the following steps:
Step S101, obtains the video collection of customer group viewing according to default screening conditions.
In embodiments of the present invention, according to default video screening conditions, from the website of customer group viewing video
Server, obtain customer group viewing video collection.Wherein, described screening conditions include but not limited to
Lower at least one: viewing video duration, the viewing time period of video, video drags frequency and single drags
Video maximum duration.
Step S102, obtains video frequent episode according to default video support threshold from described video collection
Collection, and described video frequent item set is ranked up by described video support.
In embodiments of the present invention, preset video support threshold, from described video collection, obtain symbol
Close the video frequent item set of described video support threshold, and the video item in described video frequent item set is pressed
It is ranked up according to video support, obtains video frequent item set.As the video frequent item set in table 1 is ordered as
[g(4)、d(4)、b(3)、c(3)、n(3)、q(3)]。
| User | Video name | Week is several | Time period |
| U1 | g、b、d、e、h、n、q | 2 | AM |
| U1 | b、c、d、g、m、n、p | 2 | AM |
| U2 | c、g、i、k、p | 2 | AM |
| U1 | c、d、l、t、q | 2 | AM |
| U3 | b、g、d、f、m、q、n、o | 2 | AM |
Table 1
The video collection that above-mentioned table 1 is watched for customer group.Table 2 be according to preset video support threshold from
In the video collection of table 1, video frequent item set and this video frequent item set of screening are carried out by video support
Descending.Wherein, the video support threshold preset is " video support >=3 ".
| Video item | Video support |
| g | 4 |
| d | 4 |
| b | 3 |
| c | 3 |
| n | 3 |
| q | 3 |
Table 2
Step S103, Spark parallel algorithm based on Fp-growth is from the video frequent item set after sequence
Obtain and recommend video item collection.
In embodiments of the present invention, the Spark parallel algorithm of Fp-growth is based on Map-Reduce model
The distributed algorithm realized.The Spark parallel algorithm based on Fp-growth video frequent item set after sequence
Middle acquisition recommends video item collection specifically to may include that
1, at Map mapping phase, each video item in described video frequent item set is obtained according to described sequence
Conditional pattern base.
In embodiments of the present invention, described Spark parallel algorithm is divided into Map mapping phase and Reduce rule
The about stage.In the Map stage, obtain the bar of each video item in described video frequent item set according to described sequence
Part pattern base.It is the conditional pattern base of acquisition as shown in table 3:
Table 3
2, in the Reduce stipulations stage, according to the mechanism of shuffling of Shuffle function in Spark algorithm, by phase
With the conditional pattern base stipulations of video item to together, and according to described video support threshold from described stipulations to
Conditional pattern base together obtains the local Fp-tree of described each video item.
In embodiments of the present invention, in the Reduce stage, Shuffle function is by regarding in video frequent item set
Frequently item is rearranged by random order, the conditional pattern base of the same video item rearranged by stipulations to together,
According to above-mentioned video support threshold, obtain the local Fp-tree of each video item (i.e. at Reduce in table 4
The conditional pattern base of input input video item, after stipulations, the outfan at Reduce exports local
Fp-tree).Table 4 show the local Fp-tree of each video item obtained in the Reduce stage according to table 3.
Table 4
3, to video item all of in described video frequent item set, obtained by the local Fp-tree of video item
The recommendation video item subset of described video item.
In embodiments of the present invention, select a video item x, look for from the local Fp-tree of described video item x
To the described all long paths of video item x, the node on described all long paths is found out all compound modes,
And described node merged the first frequent item set obtaining video item x, will described first frequent item set and
Video item x merges, and obtains the second frequent item set, and the i.e. second frequent item set is that the first frequent item set is plus video
Item x, the second frequent item set is the recommendation video item subset of video item x, and described node is video item x
Locally relevant to video item x in Fp-tree video item.
4, described recommendation video item subset is merged, it is thus achieved that recommend video item collection.
In embodiments of the present invention, as shown in table 2, video frequent item set includes: g, d, b, c, n,
Q, can obtain recommendation video item subset, can be designated as: g ', d ', b ', c ', n ', q ' each video item,
The most final recommendation video Xiang Jiwei: g '+d '+b '+c '+n '+q '.
During concrete use, the video watched according to customer group, it is assumed that for g, then can be from pushing away
Recommend video item and concentrate the recommendation video that acquisition is relevant to g, send this recommendation video to customer group.For recommending
It also can be ranked up by video according to frequent degree, and can only recommend the video that frequent degree is high.
As an alternative embodiment of the present invention, described method also includes:
Recommendation video renewal frequency is set, according to described renewal frequency, described recommendation video item collection is updated.
In embodiments of the present invention, a recommendation video renewal frequency (such as: update once for 24 hours) can be preset,
Repeat step S101～S103 according to this recommendation video renewal frequency recommendation video item collection is updated, thus
Make customer group group can obtain up-to-date recommendation video timely.
Embodiment two
It is illustrated in figure 2 the structure chart obtaining recommendation video system that the embodiment of the present invention provides, for the ease of
Illustrate, the part relevant to the embodiment of the present invention is only shown.
The described recommendation video system that obtains can be to be built in intelligent terminal (such as mobile phone, flat board electroplax, intelligence
Can television set) in the unit of software unit, hardware cell or software and hardware combining, described acquisition is recommended
Video system includes: video collection acquiring unit 201, video frequent item set and sequence acquiring unit 202 with
And recommend video item collection acquiring unit 203, wherein:
Video collection acquiring unit 201, for obtaining the video of customer group viewing according to the screening conditions preset
Set；
Video frequent item set and sequence acquiring unit 202, be used for according to the video support threshold preset from institute
State and the video collection that video collection acquiring unit 201 obtains obtains video frequent item set, and to described video
Frequent item set is ranked up by described video support；
Recommend video item collection acquiring unit 203, calculate parallel for Spark based on Fp-growth and regard from described
Frequently the video frequent item set after the sequence that frequent item set and sequence acquiring unit 202 obtain obtains and recommends video
Item collection.
Further, described recommendation video item collection acquiring unit 203 includes:
Conditional pattern base obtains subelement 2031, at Map mapping phase, obtaining according to described sequence
The conditional pattern base of each video item in described video frequent item set；
Locally Fp-tree obtains subelement 2032, in the Reduce stipulations stage, according to Spark algorithm
The mechanism of shuffling of middle Shuffle function, obtains subelement 2031 by the described conditional pattern base of same video item
The conditional pattern base stipulations obtained to together, and according to described video support threshold from described stipulations to together
Conditional pattern base in obtain the local Fp-tree of described each video item；
In embodiments of the present invention, in the Reduce stage, locally Fp-tree acquisition subelement 2032 passes through
Video item in video frequent item set is rearranged by Shuffle function by random order, the phase after rearranging
With the conditional pattern base of video item by stipulations to together, according to above-mentioned video support threshold, obtain each
The local Fp-tree of video item.
Video item subset is recommended to obtain subelement 2033, for all of video in described video frequent item set
, obtain, by described local Fp-tree, the local Fp-tree described video item of acquisition that subelement 2032 obtains
Recommendation video item subset；
In embodiments of the present invention, select a video item x, look for from the local Fp-tree of described video item x
To the described all long paths of video item x, the node on described all long paths is found out all compound modes,
And described node merged counting obtain first frequent item set of video item x, by described first frequent episode
Collection merges with video item x, obtains the second frequent item set, and the i.e. second frequent item set is that the first frequent item set adds
Video item x, the second frequent item set is the recommendation video item subset of video item x, and described node is video item x
Local Fp-tree in the video item relevant to video item x.
Recommend video item collection to obtain subelement 2034, for described recommendation video item subset is merged, obtain
Video item collection must be recommended.
In embodiments of the present invention, as shown in table 2, video frequent item set includes: g, d, b, c, n,
Q, can obtain recommendation video item subset, can be designated as: g ', d ', b ', c ', n ', q ' each video item,
The most final recommendation video Xiang Jiwei: g '+d '+b '+c '+n '+q '.
As an alternative embodiment of the present invention, described acquisition recommends video system also to include:
Renewal frequency arranges unit 304, is used for arranging recommendation video renewal frequency, according to described renewal frequency
Described recommendation video item collection is updated.
In sum, the embodiment of the present invention obtains the video collection of customer group viewing according to the screening conditions preset,
And obtain video frequent item set according to default video support threshold from described video collection, to described video
Frequent item set is ranked up by described video support, be finally based on the Spark parallel algorithm of Fp-growth from
Video frequent item set after sequence obtains and recommends video item collection.Compared with prior art, the embodiment of the present invention
Need first to filter out video frequent item set according to described screening conditions and video support threshold, then based on
The Spark parallel algorithm of Fp-growth carries out parallel computation to described video frequent item set, reduces acquisition and pushes away
Recommend the computation complexity of video, decrease the calculating time.And week time of video can be watched according to user
Phase recommends possible video interested to user, has stronger usability and practicality.
Those skilled in the art is it can be understood that arrive, for convenience of description and succinctly, only more than
State each functional unit, the division of subelement is illustrated, in actual application, can as desired by
Above-mentioned functions distribution is completed by different functional units, module, will the internal structure of described system be divided into
Different functional units or module, to complete all or part of function described above.Each in embodiment
Functional unit, subelement can be integrated in a processing unit, it is also possible to be that the independent physics of unit is deposited
, it is also possible to two or more unit are integrated in a unit, and above-mentioned integrated unit both can be adopted
Realize by the form of hardware, it would however also be possible to employ the form of SFU software functional unit realizes.It addition, each functional unit,
The specific name of subelement, also only to facilitate mutually distinguish, is not limited to the protection domain of the application.
In said system, the specific works process of unit, subelement, is referred to the correspondence in preceding method embodiment
Process, does not repeats them here.
Those of ordinary skill in the art are it is to be appreciated that combine respectively showing of the embodiments described herein description
The unit of example and algorithm steps, it is possible to come with the combination of electronic hardware or computer software and electronic hardware
Realize.These functions perform with hardware or software mode actually, depend on the application-specific of technical scheme
And design constraint.Each specifically should being used for can be used different methods to realize by professional and technical personnel
Described function, but this realization is it is not considered that beyond the scope of this invention.
In embodiment provided by the present invention, it should be understood that disclosed system and method, Ke Yitong
The mode crossing other realizes.Such as, system embodiment described above is only schematically, such as,
Described module or the division of unit, be only a kind of logic function and divide, actual can have when realizing other
Dividing mode, the most multiple unit or assembly can in conjunction with or be desirably integrated into another system, or some
Feature can be ignored, or does not performs.Another point, shown or discussed coupling each other or directly coupling
Close or communication connection can be the INDIRECT COUPLING by some interfaces, device or unit or communication connection, permissible
It is electrical, machinery or other form.
The described unit illustrated as separating component can be or may not be physically separate, as
The parts that unit shows can be or may not be physical location, i.e. may be located at a place, or
Can also be distributed on multiple NE.Can select therein some or all of according to the actual needs
Unit realizes the purpose of the present embodiment scheme.
It addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit,
Can also be that unit is individually physically present, it is also possible to two or more unit are integrated in a unit
In.Above-mentioned integrated unit both can realize to use the form of hardware, it would however also be possible to employ SFU software functional unit
Form realizes.
If described integrated unit realizes using the form of SFU software functional unit and as independent production marketing or
During use, can be stored in a computer read/write memory medium.Based on such understanding, the present invention
Part that prior art is contributed by the technical scheme of embodiment the most in other words or this technical scheme
Completely or partially can embody with the form of software product, this computer software product is stored in one and deposits
In storage media, including some instructions with so that a computer equipment (can be personal computer, service
Device, or the network equipment etc.) or processor (processor) perform each embodiment institute of the embodiment of the present invention
State all or part of step of method.And aforesaid storage medium includes: USB flash disk, portable hard drive, read-only deposit
Reservoir (ROM, Read-Only Memory), random access memory (RAM, Random Access
Memory), the various medium that can store program code such as magnetic disc or CD.
Embodiment described above only in order to technical scheme to be described, is not intended to limit；Although reference
The present invention has been described in detail by previous embodiment, it will be understood by those within the art that: its
Still the technical scheme described in foregoing embodiments can be modified, or special to wherein portion of techniques
Levy and carry out equivalent；And these amendments or replacement, do not make the essence of appropriate technical solution depart from this
The spirit and scope of bright embodiment each embodiment technical scheme.
Claims (8)
1. one kind obtains the method recommending video, it is characterised in that described method includes:
The video collection of customer group viewing is obtained according to default screening conditions；
Video frequent item set is obtained from described video collection according to default video support threshold, and to described
Video frequent item set is ranked up by described video support；
Spark parallel algorithm based on Fp-growth obtains recommendation from the video frequent item set after sequence and regards
Frequently item collection.
2. the method for claim 1, it is characterised in that at Spark based on Fp-growth also
Line algorithm obtains after recommending video item collection from the video frequent item set after sequence, and described method also includes:
Recommendation video renewal frequency is set, according to described renewal frequency, described recommendation video item collection is updated.
3. the method for claim 1, it is characterised in that described screening conditions include following at least
: when viewing video duration, the viewing time period of video, video drag frequency and single dragging video maximum
Long.
4. the method as described in any one of claims 1 to 3, it is characterised in that described based on Fp-growth
Spark parallel algorithm from sequence after video frequent item set obtain recommend video item collection include:
At Map mapping phase, obtain the bar of each video item in described video frequent item set according to described sequence
Part pattern base；
In the Reduce stipulations stage, according to the mechanism of shuffling of Shuffle function in Spark algorithm, by identical
The conditional pattern base stipulations of video item are to together, and according to described video support threshold from described stipulations to
The conditional pattern base risen obtains the local Fp-tree of described each video item；
To video item all of in described video frequent item set, obtained described by the local Fp-tree of video item
The recommendation video item subset of video item；
Described recommendation video item subset is merged, it is thus achieved that recommend video item collection.
5. one kind obtains the system recommending video, it is characterised in that described system includes:
Video collection acquiring unit, for obtaining the video collection of customer group viewing according to the screening conditions preset；
Video frequent item set and sequence acquiring unit, for regarding from described according to the video support threshold preset
The video collection that frequency set acquiring unit obtains obtains video frequent item set, and to described video frequent item set
It is ranked up by described video support；
Recommend video item collection acquiring unit, regard from described for Spark parallel algorithm based on Fp-growth
Frequently the video frequent item set after the sequence that frequent item set and sequence acquiring unit obtain obtains and recommends video item
Collection.
6. system as claimed in claim 5, it is characterised in that described system also includes:
Renewal frequency arranges unit, is used for arranging recommendation video renewal frequency, according to described renewal frequency to institute
State recommendation video item collection to be updated.
7. system as claimed in claim 5, it is characterised in that described video collection acquiring unit is preset
Screening conditions include following at least one: viewing video duration, viewing video time section, video drag frequency,
Single drags video maximum duration.
8. the system as described in any one of claim 5 to 7, it is characterised in that described recommendation video item collection
Acquiring unit includes:
Conditional pattern base obtains subelement, at Map mapping phase, regarding described in described sequence acquisition
Frequently frequent episode concentrates the conditional pattern base of each video item；
Locally Fp-tree obtains subelement, in the Reduce stipulations stage, according to Shuffle in Spark algorithm
The mechanism of shuffling of function, by the conditional pattern base stipulations of same video item to together, and props up according to described video
Degree of holding threshold value obtains the local of described each video item from described stipulations to conditional pattern base together
Fp-tree；
Recommend video item subset to obtain subelement, be used for video item all of in described video frequent item set,
The recommendation video item subset of described video item is obtained by the local Fp-tree of video item；
Video item collection is recommended to obtain subelement, for described recommendation video item subset being merged, it is thus achieved that push away
Recommend video item collection.
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| CN108804454A (en) * | 2017-04-28 | 2018-11-13 | 华为技术有限公司 | One population portrait method, group's portrait device and server |
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| CN107872713A (en) * | 2017-11-16 | 2018-04-03 | 北京小米移动软件有限公司 | Short processing system for video, method and device |
| CN108133031B (en) * | 2017-12-29 | 2021-01-29 | 北京搜狐新媒体信息技术有限公司 | Method and device for filtering recommended video candidate result |
| CN108133031A (en) * | 2017-12-29 | 2018-06-08 | 北京搜狐新媒体信息技术有限公司 | A kind of method and device of filtered recommendation video candidate result |
| CN108182294A (en) * | 2018-01-31 | 2018-06-19 | 湖北工业大学 | A kind of film based on frequent item set growth algorithm recommends method and system |
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| CN110839167B (en) * | 2018-08-16 | 2021-05-28 | Tcl科技集团股份有限公司 | Video recommendation method and device and terminal equipment |
| CN110839167A (en) * | 2018-08-16 | 2020-02-25 | Tcl集团股份有限公司 | Video recommendation method and device and terminal equipment |
| CN111382154A (en) * | 2018-12-29 | 2020-07-07 | 赫狮网络科技(上海)有限公司 | Advertisement matching system based on FP tree and most frequent item and working method thereof |
| CN111382154B (en) * | 2018-12-29 | 2023-07-14 | 赫狮网络科技(上海)有限公司 | Advertisement matching system based on FP tree and maximum frequent item and working method thereof |
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