CN102917269B - A kind of television program recommendation system and method - Google Patents
A kind of television program recommendation system and method Download PDFInfo
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- CN102917269B CN102917269B CN201210375238.3A CN201210375238A CN102917269B CN 102917269 B CN102917269 B CN 102917269B CN 201210375238 A CN201210375238 A CN 201210375238A CN 102917269 B CN102917269 B CN 102917269B
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Abstract
The present invention provides a kind of TV programme suggesting method and system, comprising: S1. records the program that user is interested；S2. at least one second user of common factor is had according to the program that described program searching interested and described first user are interested；S3. relatively and obtain the program that program interested from described first user in the program that described second user is interested is different；S4. the different program of program interested from described first user in described second user program interested is recommended to first user.The invention enables and can better contact between TV and user, the TV programme interested for user search and recommendation that television set can be more intelligent.
Description
Technical field
The present invention relates to intelligent television technical field, particularly relate to a kind of television program recommendation system and method.
Background technology
Under the promotion of intelligent television technology, home entertaining also begins to develop towards intelligent direction, popularization degree is also more and more higher, intelligent television is as main force therein, comprehensive intellectuality of TV will push more peak to, TV programme also can be more and more rich and varied, in the face of the TV programme that kind is day by day various, user often becomes to have no way of doing it in daily life, television channel have to be constantly changed according to EPG information, by searching the TV programme of magnanimity, just can find certain program oneself preferred, rethink next time and watch this type of program, step before just can only repeating, continuous zapping, long this so goes down, people often cannot obtain oneself information really interested from numerous media programs, and the mode of the searching TV program frequently repeated, user can be made to be weary of the selection to program, lose the interest to watching television program.
Additionally, the interest of oneself is understood by user certain limitation, often to oneself potential program interested unclear, so feeling sometimes and oneself wanting to see the thing that some are fresh, but where do not know interest again, and user is not intended to carry out too much active operation and goes to excavate the interest of oneself, therefore, help the media content that usage mining is interested, or help user to find oneself potential point of interest, allow machine know more about user, allow user know more about oneself, be the problem of intelligent required solution at present.
Summary of the invention
(1) technical problem
The problem to be solved in the present invention is so that between TV and user and can better contact, the TV programme interested for user search and recommendation that television set can be more intelligent.
(2) technical scheme
The present invention provides a kind of television program recommendation system, comprising:
Record unit, for recording the program that user is interested；
Processing unit, at least one second user of common factor is had, then relatively and obtain the program that program interested from described first user in the program that described second user is interested is different for the program that the program searching interested according to first user and described first user are interested；
Transmitting element, for recommending first user by programs different for program interested from described first user in program interested for described second user.
Optionally, in the scheduled time before the program recommended starts, recommend to first user.
Optionally, it is recommended that program support user preengage.
Optionally, described processing unit sends based on user request or carry out described search and acquisition every the scheduled time.
Optionally, the program that described user is interested is that the behavior according to user obtains.
Optionally, described processing unit farther includes:
Analysis module, for the program interested according to the behavior analysis first user of described first user；
Retrieval module, for traveling through the behavior of second user outside first user in user behavior record；
Recommending module, whether the behavior of behavior and described second user for judging first user has common factor on program interested, if there being common factor, then obtain the behavior of described second user, otherwise, drive the behavior of described another the second user of retrieval module walks, until the time of traversal reaches predetermined threshold or finds the behavior with described first user to have at least one second user of common factor；Then relatively and obtain the program that program interested from described first user in the program that described second user is interested is different.
The present invention also provides for a kind of TV programme suggesting method, and it comprises the steps:
S1. the program that record user is interested；
S2. at least one second user of common factor is had according to the program that described program searching interested and described first user are interested；
S3. relatively and obtain the program that program interested from described first user in the program that described second user is interested is different；
S4. the different program of program interested from described first user in described second user program interested is recommended to first user.
Optionally, the program that described user is interested is that the behavior according to user obtains.
Optionally, the behavior of user includes user and watches frequency and the time of a program, and described program interested is the program that viewing exceedes pre-determined number or scheduled duration.
Optionally, in described step S2 based on user send request or carry out described search every the scheduled time.
Optionally, described step S2 farther includes:
S21. according to the program that the behavior analysis first user of described first user is interested；
S22. the behavior of second user outside traversal first user in user behavior record；
S23. judge whether the behavior of first user and the behavior of described second user have common factor on program interested, if there being common factor, then obtain the behavior of described second user, otherwise, then travel through the behavior of another the second user, until the time of traversal reaches predetermined threshold or finds the behavior with described first user to have at least one second user of common factor.
The present invention also provides for a kind of TV programme suggesting method, and it comprises the steps:
S1. the program that record user is interested；
S2 '. according to the program that user is interested, user is carried out cluster and generate at least one core customer's group, described core customer's group is made up of the user being not less than the first predetermined quantity, and the common program that user in described core customer's group is interested is not less than the second predetermined quantity；
S3 '. judge whether first user belongs at least one core customer's group, if, then using other users in described core customer's group as the second user having common factor with first user, if it is not, then terminate or search for the program interested with described first user within the scheduled time have at least one second user of common factor;
S4 '. relatively and obtain the program that program interested from described first user in the program that described second user is interested is different；
S5 '. the program that program interested from described first user in the program that first user described second user of recommendation is interested is different.
Optionally, described step S3 ' also includes: judge that the group of the core customer belonging to first user whether and has common user between other core customer's groups, if, then the user in other core customer's groups is also served as and have the second user of common factor with first user, if it is not, then directly perform step S4 '.
Optionally, the program that user is interested is divided into different likes grade, carries out described search and acquisition under the program that favor program the highest grade.
(3) technique effect
The present invention helps the media content that usage mining is interested, or help user to find oneself potential point of interest, machine is allowed to know more about user, user is allowed to know more about oneself, make can better contact between TV and user, the TV programme interested for user search and recommendation that television set can be more intelligent.
Accompanying drawing explanation
Fig. 1 represents the flow chart of program commending method of the present invention；
Fig. 2 represents the graph of a relation in the present invention between first user and the second user；
Fig. 3 represents the structure chart of heretofore described program recommendation system.
Detailed description of the invention
Embodiment 1:
The present invention provides a kind of television program recommendation system, comprising:
Record unit (1), for recording the program that user is interested；
Processing unit (2), at least one second user of common factor is had, then relatively and obtain the program that program interested from described first user in the program that described second user is interested is different for the program that the program searching interested according to first user and described first user are interested；
Transmitting element (3), for recommending first user by programs different for program interested from described first user in program interested for described second user.
The present invention mode by searching for and comparing, program that the program like other users or program category and oneself being also possible to is liked or program category convenient recommend oneself, described television program recommendation system can be server, it constantly collects the behavior of oneself and other user, make it more efficient and quickly find target program category, after finding the program of recommendation, before this program starts in the scheduled time (such as 5 minutes), can recommend to first user.
Optionally, request that described processing unit sends based on user or carry out described search and acquisition every the scheduled time, make to obtain, according to the requirement of user or periodicity, the program recommended to user, after finding the program can recommended to first user, the program recommended can be preengage by user, also can before this program starts in the scheduled time (such as 5 minutes), recommend to first user, thus solving following technical problem of the prior art: the TV programme that user watches at present are not likely to be most interested, but it is interested that other programs that other channels are during this period of time newly play are probably this user, but user does not know the broadcasting of this program, thus missing program interested.
Optionally, as it is shown on figure 3, described processing unit farther includes:
Analysis module (4), for the program interested according to the behavior analysis first user of described first user；
Retrieval module (5), for traveling through the behavior of second user outside first user in user behavior record；
Recommending module (6), whether the behavior of behavior and described second user for judging first user has common factor on program interested, if there being common factor, then obtain the behavior of described second user, otherwise, drive the behavior of described another the second user of retrieval module walks, until the time of traversal reaches predetermined threshold or finds the behavior with described first user to have at least one second user of common factor；Then relatively and obtain the program that program interested from described first user in the program that described second user is interested is different.
What whole commending system to do is exactly the hobby first recording first user, recording mode can watch frequency and the time of certain program by the user behavior module record first user of collecting of television set, exceed certain number of times or duration then the hobby program that this program marker is first user, the TV programme of user preferences can have a lot of, give an example, one of program of first user hobby is making progress every day of HNTV, when user wishes that watching other programs is not desired to again oneself constantly search searching, television set can be passed through and send a request, then this request is sent to server, then server helps to select other users in customer group, at this moment have found the second user, second user is similar with first user, also the multiple programs oneself liked are had, now, the analysis module of server starts to analyze and judge, if the program of first user and the second user preferences does not have similar, then return and re-search for, if the hobby that the second user found has part identical with first user, second user also likes seeing and makes progress every day, the analysis module of server then starts to contrast first user and the second user, it is found that other programs that the second user likes, now, the recommending module of server is then responsible for these other programs are recommended first user, chosen whether that viewing still continues search for by first user again.
During the program that record user likes, it is possible to be divided into and different like grade, scan under the program that favor program the highest grade.Can find immediate with oneself interest other people, in the program of these people hobby, the probability that oneself is likely to like too will be greatly increased.
The present invention can recommend program for user more rapidly and effectively, meets user's curiosity to the program that other people like, and helps to find the program category oneself liked.
Embodiment 2
The present invention also provides for a kind of TV programme suggesting method, as it is shown in figure 1, it comprises the steps:
S1. the program that record user is interested；
Specifically, first user is first to some or when a certain class program is interested, and this can pass through to analyze the behavior interested that user is conventional, for instance can analyze user and watch the historical record of TV, or the evaluation to TV programme, thus obtain user behavior record.
S2. at least one second user of common factor is had according to the program that described program searching interested and described first user are interested；
S3. relatively and obtain the program that program interested from described first user in the program that described second user is interested is different；
Optionally, the program that described user is interested is that the behavior according to user obtains, specifically, analyze the program that user is interested, can pass through to analyze user, have the second user of similarity to find behavior and first user, the difference of the behavior obtaining the second user the behavior contrasting first user and the second user, search for the TV programme involved by the behavior that the second user is different from first user, and they are recommended first user.Such first user just can know that with which type of program the second user oneself liking same class program also can like, and thus considerably increases first user and likes the possibility of recommended program, also new program category is recommended to give first user.Certain first user is likely to the program not liking these recommendations.System can help him to continue search for other users such as the 3rd user, fourth user etc..The behavior of described user includes first user and watches frequency and the time of a program, and described program interested can be the program that viewing exceedes pre-determined number or scheduled duration.
As shown in Figure 2, if first user likes the program seen to be A, B, C, the interest behavior of the second user is A, E, F, first user and the second user have the program category of the identical hobby of part, the method is exactly to first user the television recommendations of E, F type, if first user also likes this type of program, then searches for successfully, if first user does not like this type of program, then can continue search for other the 3rd user, fourth user ... ..
S4. the different program of program interested from described first user in described second user program interested is recommended to first user.
The improving of this method helps user very easy to wait that TV recommends good-looking television program type to oneself from differing all over being changed into all over the search channel repeated.
Optionally, in described step S2 based on user send request or carry out described search every the scheduled time.
Optionally, described step S2 farther includes:
S21. according to the program that the behavior analysis first user of described first user is interested；
S22. the behavior of second user outside traversal first user in user behavior record；
S22. judge whether the behavior of first user and the behavior of described second user have common factor on program interested, if there being common factor, then obtain the behavior of described second user, otherwise, then travel through the behavior of another the second user, until the time of traversal reaches predetermined threshold or finds the behavior with described first user to have at least one second user of common factor.
Although current TV programme are easily achieved the behavior collecting and analyzing user, similar program being recommended user's viewing, the technical scheme emphasis described in the present embodiment is excavated by the possible program interested of user and recommendation aspect has been improved.When first user wishes to watch further types of program, but when being not desired to again try to search for, we are by collecting the behavior of other users, other users herein refer to there is the identical behavior of part with first user, namely the viewing TV interest behavior that part is common is had with first user, the TV programme that the behavior that so these other users are different from first user relates to also can be likely the television program type that first user is liked seeing, so recommending a first user will be greatly improved Consumer's Experience these programs, more seem intelligent.
Embodiment 3
The present embodiment includes all the elements of embodiment 2, additionally includes following content:
Due to said method be each user recommend program time, the behavior of the user that to be required in Ergodic Theory similar with its behavior characteristics, so, when whole system configure arithmetic speed on the low side, and the customer volume of system big when, then can increase system burden, so, in order to the algorithm of system is optimized more, the burden of reduction system, and making the program of recommendation more accurate, the present embodiment can further utilize in the following manner to realize, method about:
1, user is clustered, and generate several core customer's group, analyze the TV programme that the user in each core classification likes；
2, other core customers are recommended to organize included TV programme to user；
For example, there are four users, are specifically shown in following table:
| User | Program interested |
| First user | A、B、C、D、E |
| Second user | B、C、D、E、W、Y、Z |
| 3rd user | B、C、E、H、W、Y、Z |
| Fourth user | O、P、W、Y、Z |
Then the common portion of first user-fourth user is analyzed, can set that the threshold value a of a program of interest herein, and number of users threshold value b, after reaching above-mentioned two threshold value, then will generate core customer's group, for instance: require number of users threshold value b more than 3, the common portion amount threshold a of program of interest more than 3, then can become core customer's group, after upper table is calculated, obtaining core customer's group is:
The way of recommendation 1: core customer is organized internal referral mode, such as core customer organizes 1, due to first user, the second user, the 3rd user all interested in B, C, E program, may be considered as then that interest is identical, then core customer is organized to the member in 1, core customer can be recommended to organize the program beyond the common portion that in 1, other members are interested to it, for instance first user program A interested can recommend the second user, the 3rd user etc.
The way of recommendation 2: for the way of recommendation between core customer's group, such as core customer organizes 1 and organizes 2 with core customer, owing to the two core customer group all includes the second user and the 3rd user, so may determine that the relatedness between above-mentioned two core customer's group with potential interest, the program of interest common portion W of 2 can be organized to the first user preferential recommendation core customer that core customer organizes in 1, Y, Z, this way of recommendation is owing to being recommend core customer to organize 2 most interested programs, these programs are considered the program that the most people with this relatedness is all interested, so the effect recommended when recommending for first user is best, certainly, the 3rd user and other programs interested of fourth user can also be recommended, the program O that such as fourth user is liked, P recommends first user, certain recommendation effect can also be played.
3, for further illustrating here, 1 is organized owing to first user only belongs to core customer, so its way of recommendation can be selected the way of recommendation 1, it is also possible to select the way of recommendation 2；But when the second user is recommended, namely belong to core customer to organize 1 and fall within core customer due to it and organize 2, at this moment adopt the way of recommendation 2 to its recommend core customer organize 1 or core customer to organize the program of 2 common portion interested just improper, in fact for the second user, just passable only with the way of recommendation 1.
The program interested for how judging each user, can by analyze user view histories (viewing time of such as TV programme reaches to a certain degree, it can be considered as then program interested, the time period watching certain channel every day can also be analyzed, then also will be considered that content that this time period user likes certain channel to broadcast etc., the analysis prior art of this kind of view histories has a lot of method, repeat no more), or further, after above-mentioned historical analysis, attribute tags can be sticked for user, such as (spectators swordsman, basketball spectators etc.), thus completing the cluster of user and the basis of program recommendation, user's evaluation to TV programme can also be adopted, etc..
Embodiment of above is merely to illustrate the present invention; and it is not limitation of the present invention; those of ordinary skill about technical field; without departing from the spirit and scope of the present invention; can also make a variety of changes and modification; therefore all equivalent technical schemes fall within scope of the invention, and the scope of patent protection of the present invention should be defined by the claims.
Claims (2)
1. a TV programme suggesting method, it is characterised in that comprise the steps:
S1. the program that the view histories record user of analysis user is interested is passed through；
S2 '. according to the program that user is interested, user is carried out cluster and generate at least one core customer's group, described core customer's group is made up of the user being not less than the first predetermined quantity, and the common program that user in described core customer's group is interested is not less than the second predetermined quantity；
S3 '. judge whether first user belongs at least one core customer's group, if, then using other users in described core customer's group as the second user having common factor with first user, if it is not, then terminate or search for the program interested with described first user within the scheduled time have at least one second user of common factor；
S4 '. relatively and obtain the program that program interested from described first user in the program that described second user is interested is different；
S5 '. the program that program interested from described first user in the program that first user described second user of recommendation is interested is different；Wherein,
Described step S3 ' also includes: judge that the group of the core customer belonging to first user whether and has common user between other core customer's groups, if, then the user in other core customer's groups is also served as and have the second user of common factor with first user, if it is not, then directly perform step S4 '.
2. the TV programme suggesting method as described in any one of claim 1, is further characterized in that, the program that user is interested is divided into different likes grade, carries out described search and acquisition under the program that favor program the highest grade.
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| CN104104999B (en) * | 2013-04-10 | 2018-10-09 | 华为技术有限公司 | Audio/video information recommends method and apparatus |
| CN104123315B (en) * | 2013-04-28 | 2018-01-30 | 北京音之邦文化科技有限公司 | The recommendation method and recommendation server of multimedia file |
| CN103491441B (en) * | 2013-09-09 | 2017-02-01 | 东软集团股份有限公司 | Recommendation method and system of live television programs |
| CN103702145A (en) * | 2013-12-26 | 2014-04-02 | 京东方科技集团股份有限公司 | Program playing reminding method, program playing reminding system and display device |
| CN104869131B (en) * | 2014-02-21 | 2018-04-13 | 冠捷投资有限公司 | Multiple electronic device interactive approaches and its system based on user's purpose |
| CN104320709A (en) * | 2014-10-13 | 2015-01-28 | 四川长虹电器股份有限公司 | Recommendation method for television program and playing terminal for television program |
| CN104537115B (en) * | 2015-01-21 | 2019-07-16 | 北京字节跳动科技有限公司 | The heuristic approach and device of user interest |
| CN105142025A (en) * | 2015-07-16 | 2015-12-09 | Tcl集团股份有限公司 | Information push method and system based on intelligent television terminal |
| CN105812946A (en) * | 2016-03-21 | 2016-07-27 | 深圳市九洲电器有限公司 | Book recommending method and system based on digital television device |
| CN106095819A (en) * | 2016-05-31 | 2016-11-09 | 北京奇艺世纪科技有限公司 | A kind of video recommendation method and device |
| WO2018023678A1 (en) * | 2016-08-05 | 2018-02-08 | 吴晓敏 | Information pushing method during interest recognition and recognition system |
| WO2018023679A1 (en) * | 2016-08-05 | 2018-02-08 | 吴晓敏 | Method for recognizing user's interests on basis of time and recognition system |
| WO2018023680A1 (en) * | 2016-08-05 | 2018-02-08 | 吴晓敏 | Data acquisition method for time-based content recommendation technology and recommendation system |
| WO2018023677A1 (en) * | 2016-08-05 | 2018-02-08 | 吴晓敏 | Data acquisition method for time-based interest recognition technology and recognition system |
| CN106604068B (en) * | 2016-12-30 | 2019-11-05 | 中广热点云科技有限公司 | A kind of method and its system of more new media program |
| CN106844769A (en) * | 2017-02-27 | 2017-06-13 | 百度在线网络技术（北京）有限公司 | With reference to the pattern of passing through and in limited time reading model information flow recommend method and apparatus |
| CN107463675B (en) * | 2017-08-03 | 2020-11-03 | 北京京东尚科信息技术有限公司 | Data processing method and system |
| CN109429103B (en) * | 2017-08-25 | 2021-08-13 | Tcl科技集团股份有限公司 | Method and device for recommending information, computer readable storage medium and terminal equipment |
| CN107948755B (en) * | 2017-12-06 | 2021-05-18 | 绵阳欢网科技有限责任公司 | Video content recommendation method and system combining user watching duration |
| CN109217957A (en) * | 2018-09-11 | 2019-01-15 | 广东翼卡车联网服务有限公司 | A kind of radio station push program method |
| CN113949931A (en) * | 2021-10-13 | 2022-01-18 | 深圳市视壮科技有限公司 | IPTV program recommendation method and system |
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