CN101860696A - Program recommending method and streaming media program system - Google Patents
Program recommending method and streaming media program system Download PDFInfo
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- CN101860696A CN101860696A CN201010160136A CN201010160136A CN101860696A CN 101860696 A CN101860696 A CN 101860696A CN 201010160136 A CN201010160136 A CN 201010160136A CN 201010160136 A CN201010160136 A CN 201010160136A CN 101860696 A CN101860696 A CN 101860696A
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Abstract
The invention discloses a program recommending method and a streaming media program system, wherein the method comprises the following steps that: the attribute weight of a program is generated according to the program playing behaviors of a user; and the program is recommended to the user according to the attribute weight of the program. The streaming media business system comprises a business management platform and a database, the business management platform comprises a user playing behavior analysis module, the user playing behavior analysis module is connected with the database, generates the attribute weight of the program according to the program playing behavior of the user, and recommends the program to the user according to the attribute weight of the program. Compared with the prior art, the invention calculates the preference of the user to programs by analyzing the program playing behaviors of the user according to the program attribute, recommends programs to the user and improves the recommendation precision.
Description
Technical field
The invention belongs to the streaming media service technical field, be specifically related to a kind of program commending method and flow-medium performance system.
Background technology
All fairly simple to the way of recommendation of content in the present most audio frequency and video operation system, the taste according to the user does not carry out the individual character recommendation.The for example simple recommendation in IPTV and the mobile stream media system.The existing way of recommendation is broadly divided into two kinds: a kind of is to produce temperature according to the number of times that program is played, and has done a ranking list, and its limitation is: Consideration is single, adopts often to add 1 pattern automatically, does not have intelligent.Another kind of is to adopt based on program provider program subjective judgement method, mainly depends on the novel degree of program and has watched the historical evaluation analysis of user to program, excavates the user to program interest, and according to the pattern of discovery the user is carried out program commending.Its limitation is: modeling is not carried out in user's broadcast behavior, lacked the effective processing to user preference, the precision of recommendation is not high.
Summary of the invention
The purpose of this invention is to provide a kind of program commending method and flow-medium performance system, improved the accuracy of program commending.
For achieving the above object, the present invention has adopted following technical scheme: a kind of program commending method comprises step:
Generate the attribute weight value of program according to user's playing programs behavior;
Attribute weight value according to described program is programs recommended to the user.
Preferably, the attribute weight value that generates program according to user's playing programs behavior comprises step:
Set up this user's program commending table according to user's broadcast behavior, described program commending table is arranged with the attribute weight value of program;
The summation of the attribute of all programs that the statistics user plays is calculated the mean value of each weight in user's program commending table then.
Preferably, the mean value of each weight comprises step in the described calculating user program commending table: when the user withdraws from performance system, prompting user feedback program commending degree of being satisfied with according to the satisfaction of user feedback, calculates the mean value of each weight in user's program commending table.
Preferably, according to the satisfaction of user feedback, the mean value that calculates each weight in user's program commending table is specially: if the satisfaction of user feedback is on the low side, then increase weighted mean; If the satisfaction of user feedback is for just in time, then weighted mean is constant; If the satisfaction of user feedback is higher, then reduce weighted mean.
Preferably, by regularly initiating task is set, regularly start-up system recomputate automatically with update system in user's program commending table.
Preferably, described method also comprises step: search is play the similar user of behavior with this user, selects in programs recommended this user's of adding the program commending table from user's program commending table of similar users.
A kind of stream media service system, comprise Business Management Platform and database, described Business Management Platform comprises that the user plays the behavioural analysis module, described user plays the behavioural analysis module and is connected with database, described user plays the attribute weight value of behavioural analysis module according to user's playing programs behavior generation program, and programs recommended to the user according to the attribute weight value of described program.
Preferably, described user behavior analysis module is set up this user's program commending table according to user's broadcast behavior, and described program commending table is arranged with the attribute weight value of program; And the summation of the wherein a certain attribute of all programs of playing of statistics user, calculate the mean value of each weight in user's program commending table then.
Preferably, described Business Management Platform also is used to point out user feedback program commending degree of being satisfied with when the user withdraws from performance system, if the satisfaction of user feedback is on the low side, then increase weighted mean; If the satisfaction of user feedback is for just in time, then the mean value of weight is constant; If the satisfaction of user feedback is higher, then reduce the mean value of weight.
Preferably, described Business Management Platform also comprises time block, is connected with the user behavior analysis module, is used for regularly initiating task, regularly start-up system recomputate automatically with update system in user's program commending table.
Preferably, described Business Management Platform also comprises search module, and described search module is used to search for this user behavior plays the similar user of behavior, selects in programs recommended this user's of adding the program commending table from user's program commending table of similar users.
Compared with prior art, the present invention to playing programs behavior and programme attribute, calculates the preference of user to program by analysis user, and is programs recommended to the user, improved the accuracy of recommending.
Description of drawings
A kind of program commending method flow chart that Fig. 1 provides for the embodiment of the invention;
A kind of stream media service system block diagram that Fig. 2 provides for the embodiment of the invention.
Embodiment
For making the purpose, technical solutions and advantages of the present invention clearer, describe the present invention below in conjunction with the accompanying drawings and the specific embodiments.
Core concept of the present invention is: Mathematical Modeling is set up in behavior according to user's playing programs, design program intelligent recommendation system, play history record and program characteristics by analysis user, identification user's preference, recommend satisfied program to the user, improve the accuracy of recommending, have intelligent preferably.
(1) increasing programme attribute (asking the inventor to illustrate which attribute programme attribute specifically comprises) in the uploading step of operator's management platform sets, hypothetical program is m, then to go into library information be that (Attribute 1 for Gm=to a program, Attribute2, Attribue3, ...), wherein Attribute is the weighted value of corresponding attribute, system increases a programme attribute weight table.Described attribute is meant the type that film comprises, such as action, love, science fiction, terror etc.
(2) in system, increase a program hot statistics table (generally all existing among existing mobile flow medium and the IPTV), when user's certain program that finishes playing, then this program temperature value adds 1 automatically, suppose that the temperature information definition is HOT=(Content_m, Hot_value, Date), wherein Content_m is a programm name, Hot_value is the temperature value, and Date is a Time of Day.
See also shown in Figure 1ly, Fig. 1 is a kind of program commending method flow chart that the embodiment of the invention provides, and may further comprise the steps:
S101: when certain user lands stream media service system, judge this user, if login user first enters step S102 whether for landing first; If not login user first, enter step S104.
S102: directly recommend several the highest (such as 10) programs of present temperature to give the user, change step S104 over to.
S103: from user's program commending table of database, get this user's program commending table, select to play for the user.
S104: temperature adds a weight unit automatically when user's broadcast program finishes.
Suppose user's program commending table one recorded information, wherein W represents total weight of program attribute, and AllValue represents the total broadcasting time of user, and Content represents programs recommended, Rm=(W1, W2, W3...AllValue, Content1, Content2 ...).
S105:, suppose into library information to be that (UserID, Content Date), all empty this user history information before the warehouse-in Action=with user's broadcast behavior warehouse-in.
S106: after the user behavior warehouse-in, the user was upgraded the timed task warehouse-in of recommending the same day, whether at first inquire about this user recommends to upgrade the timed task data and put in storage the same day, put in storage once more if put in storage then do not needed, otherwise with timed task warehouse-in, suppose into library information be Task=(Userid, Date), wherein Userid is a user ID, and Date is a Time of Day.When other programs are play in user's broadcast once more, jump to step S105.
S107: when the user withdraws from whole stream media service system, the prompting user feedback program commending situation of being satisfied with.Preferably, information: program weight n, select: higher, on the low side, just in time, with field feedback access customer feedback data table FB=(UserID, W1, W2 ...), three kinds of state values-1 of W definable, 0,1 wherein, represent respectively on the low side, just in time, higher.
S108-S110: commending system is by timed task, such as every day when morning, whole traffic carrying capacity was little, start the calculating and the renewal of user's program commending table.Traversal user on the same day recommends to upgrade the timed task table, the user when system service in the sky take out one by one calculate delete after the user behavior value Task show in this record.
In the present embodiment, rudimentary algorithm is:
Wherein i represents the programme content sequence valve that the user play the same day, and the n initial value is 1, is broadcasting program number purpose accumulated value among the user one day.For example: play 10 films the same day, n=9 so, the value of i is [1,9], and Attribute represents the attribute of film, and Atrribute_Wj represents the weighted value summation of j attribute in all films that the user play the same day., this user's weighted value (W value and AllValue) in renewal user's program commending table (Rm table), basic calculation: use the value of calculating to upgrade Rm literary name section Rm.Wj=Rm.Wj+Atrribute_Wj, Rm.n=Rm.n+1.
Further, calculate average weight Average (the Wi)=Rm.Wi/n of each weights W in the Rm table, data and average weight data Average (Wi) in the COMPREHENSIVE CALCULATING feedback form (FB).
Preferably, in the present embodiment,, then increase corresponding weighted mean if the satisfaction of user feedback is on the low side; If the satisfaction of user feedback is for just in time, then Dui Ying weighted mean is constant; If the satisfaction of user feedback is higher, then reduce corresponding weighted mean.If such as the W value is-1, then Average (Wi) * 120%, and the full marks value that exceeds Average (Wi) is calculated with full marks; If be 0, then Average (Wi) is constant; If be 1, then Average (Wi) * 80%.
S111-S112: start immediate several (preferred 8) programs (called after C8) of final average weight value that search engine search content table (Gm) weight comprehensive grading and user calculate.
Further, search out and immediate several users of this user weight, preferred 2, get up-to-date broadcast in this 2 user Action table and be different from each 1 of the program of C8 in the GM table, have 10 programs altogether, with the Content1...Content10 in these 10 program updating Rm tables.
Repeating step S108-S112, the data in timing updating task table all deletion are finished.
See also shown in Figure 2ly, Fig. 2 is a kind of stream media service system block diagram that the embodiment of the invention provides.Stream media service system comprises Business Management Platform 21 and database 22, and described Business Management Platform 21 comprises that the user plays behavioural analysis module 210, time block 211 and search module 212.
Described user plays behavioural analysis module 210 and is connected with database 22, and described user plays the attribute weight value of behavioural analysis module according to user's playing programs behavior generation program, and programs recommended to the user according to the attribute weight value of described program.
Preferably, described user behavior analysis module 210 is set up this user's program commending table according to user's broadcast behavior, and described program commending table is arranged with the attribute weight value of program; And the summation of the wherein a certain attribute of all programs of playing of statistics user, calculate the mean value of each weight in user's program commending table then.
Preferably, described Business Management Platform 21 also is used to point out user feedback program commending degree of being satisfied with when the user withdraws from performance system, and the user has three kinds of selections: on the low side, just in time, higher.
Preferably, described user behavior analysis module 210 is according to the satisfaction of user feedback, and the average weight value of calculating each weight in user's program commending table is specially: if the satisfaction of user feedback is on the low side, then increase weighted mean; If the satisfaction of user feedback is for just in time, then weighted mean is constant; If the satisfaction of user feedback is higher, then reduce weighted mean.
Time block 212 is connected with the user behavior analysis module, is used for regularly initiating task, regularly start-up system recomputate automatically with update system in user's program commending table.
Search module 213 is used to search for user behavior plays similar program and the user of behavior, and the behavior table of comprehensive similar program and similar users is selected programs recommended this user's of going into program commending table.
Preferably, described Business Management Platform 21 also is used to point out user feedback program commending degree of being satisfied with when the user withdraws from performance system.
With media business systems such as existing IPTV, mobile flow medium and P2P is that example describes, and passes through EPG/ portal page module in the existing business system to user's presenting programs recommendation tables.When operator landed business management system upload of media file, the business management system module was gone into database with data.When user's broadcast or download behavior or feedback recommendation end, data are gone into database by EPG/ portal page module.Commending system increases timed task module, user behavior analysis module, feedback adjusting module and search engine module newly.Wherein trigger user's program commending table system by timed task module (for example morning, 2:00 was to 6:000 in morning) when whole operation system is not busy, trigger earlier the behavior on user behavior analysis module analysis user same day and data that feedback will be analyzed this moment and write data (feedback information is adjusted through the feedback adjusting module), start search engine finishing after and search for the program relevant and go into program commending table database with user behavior.Wherein the business management system module increases the programme attribute setting in uploading step, hypothetical program is m, then to go into library information be Gm=(Attribute1 to a program, Attribute2, Attribue3, ...), wherein Attribute is the weighted value of corresponding attribute, system increases a programme attribute weight table.Increase a program hot statistics table (generally all existing among existing mobile flow medium and the IPTV) in addition in the database, when user's certain program that finishes playing, then program temperature value is added 1 automatically by 103 modules, suppose that the temperature information definition is HOT=(Content_m, Hot_value, Date).
The present invention has set up a data model according to the user to playing programs behavior and programme attribute, and define the specific implementation in each stage respectively, data analysis principle and Mathematical Modeling have been fully utilized, by analysis user to playing programs behavior and programme attribute, calculate the preference of user to program, programs recommended to the user, improve and recommend efficient.Further, system can adjust automatically according to user's feedback information, thereby improves the accuracy of recommending, and has intelligent preferably.
The present invention is applicable to any business operation system relevant with media services, by the further user preferences recommend method of setting forth in a kind of stream media service system of the present invention of following specific embodiment, below embodiment is described in detail, but not as a limitation of the invention.
Above content be in conjunction with concrete execution mode to further describing that the present invention did, can not assert that concrete enforcement of the present invention is confined to these explanations.For the general technical staff of the technical field of the invention, without departing from the inventive concept of the premise, can also make some simple deduction or replace, all should be considered as belonging to protection scope of the present invention.
Claims (11)
1. a program commending method is characterized in that, comprises step:
Generate the attribute weight value of program according to user's playing programs behavior;
Attribute weight value according to described program is programs recommended to the user.
2. method according to claim 1 is characterized in that, the attribute weight value that generates program according to user's playing programs behavior comprises step:
Set up this user's program commending table according to user's broadcast behavior, described program commending table is arranged with the attribute weight value of program;
The summation of the attribute of all programs that the statistics user plays is calculated the mean value of each weight in user's program commending table then.
3. method according to claim 2, it is characterized in that, the mean value of each weight comprises step in the described calculating user program commending table: when the user withdraws from performance system, prompting user feedback program commending degree of being satisfied with, according to the satisfaction of user feedback, calculate the mean value of each weight in user's program commending table.
4. method according to claim 3 is characterized in that, according to the satisfaction of user feedback, the mean value that calculates each weight in user's program commending table is specially: if the satisfaction of user feedback is on the low side, then increase weighted mean; If the satisfaction of user feedback is for just in time, then weighted mean is constant; If the satisfaction of user feedback is higher, then reduce weighted mean.
5. according to the method for claim 1 to 4 described in each, it is characterized in that, by regularly initiating task is set, regularly start-up system recomputate automatically with update system in user's program commending table.
6. according to the method for claim 1 to 4 described in each, it is characterized in that, also comprise step: search is play the similar user of behavior with this user, selects in programs recommended this user's of adding the program commending table from user's program commending table of similar users.
7. stream media service system, comprise Business Management Platform and database, it is characterized in that, described Business Management Platform comprises that the user plays the behavioural analysis module, described user plays the behavioural analysis module and is connected with database, described user plays the attribute weight value of behavioural analysis module according to user's playing programs behavior generation program, and programs recommended to the user according to the attribute weight value of described program.
8. system according to claim 7 is characterized in that, described user behavior analysis module is set up this user's program commending table according to user's broadcast behavior, and described program commending table is arranged with the attribute weight value of program; And the summation of the wherein a certain attribute of all programs of playing of statistics user, calculate the mean value of each weight in user's program commending table then.
9. system according to claim 8 is characterized in that, described Business Management Platform also is used to point out user feedback program commending degree of being satisfied with when the user withdraws from performance system, if the satisfaction of user feedback is on the low side, then increase weighted mean; If the satisfaction of user feedback is for just in time, then the mean value of weight is constant; If the satisfaction of user feedback is higher, then reduce the mean value of weight.
10. according to each described system of claim 7 to 9, it is characterized in that described Business Management Platform also comprises time block, be connected with the user behavior analysis module, be used for regularly initiating task, regularly start-up system recomputate automatically with update system in user's program commending table.
11. according to each described system of claim 7 to 9, it is characterized in that, described Business Management Platform also comprises search module, described search module is used to search for this user behavior plays the similar user of behavior, selects in programs recommended this user's of adding the program commending table from user's program commending table of similar users.
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| US11539993B2 (en) | 2017-07-27 | 2022-12-27 | Google Llc | Methods, systems, and media for presenting notifications indicating recommended content |
| CN109121007A (en) * | 2018-09-18 | 2019-01-01 | 深圳市酷开网络科技有限公司 | Movie and television contents recommended method, smart television and system based on plurality of human faces identification |
| CN109121007B (en) * | 2018-09-18 | 2020-11-03 | 深圳市酷开网络科技有限公司 | Movie content recommendation method based on multi-face recognition, smart television and system |
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