Method and system for efficiently compiling media content items for a media-on-demand platform
원문보기
IPC분류정보
국가/구분
United States(US) Patent
등록
국제특허분류(IPC7판)
H04N-021/25
H04N-021/231
H04N-021/258
H04N-021/472
H04N-021/482
G06Q-030/02
G06Q-030/06
출원번호
US-0437604
(2013-10-25)
등록번호
US-9843829
(2017-12-12)
우선권정보
EP-12189860 (2012-10-25)
국제출원번호
PCT/EP2013/072457
(2013-10-25)
국제공개번호
WO2014/064281
(2014-05-01)
발명자
/ 주소
Korst, Jan
Barbieri, Mauro
Pronk, Serverius Petrus Paulus
Clout, Ramon Antoine Wiro
Schenk, Paul
출원인 / 주소
FUNKE DIGITAL TV GUIDE GMBH
대리인 / 주소
Ware, Fressola, Maguire & Barber LLP
인용정보
피인용 횟수 :
0인용 특허 :
2
초록▼
For the negotiation of an operator of a media-on-demand platform with its content providers a method and system for efficiently compiling media content items for the media-on-demand platform is provided. The method makes use of a combination of a recommender system to select a suitable set of media
For the negotiation of an operator of a media-on-demand platform with its content providers a method and system for efficiently compiling media content items for the media-on-demand platform is provided. The method makes use of a combination of a recommender system to select a suitable set of media content items to be offered for a next period of service and a number-of-rentals predictor for estimating how many videos individual users will rent the following period of service. Furthermore, the method and system can be executed for estimating profit or loss from rentals over the following period of service as well as estimate customer satisfaction.
대표청구항▼
1. A method for selecting a data set in a form of a group of digital media content items from a plurality of groups of digital media content items for offer on a media-on-demand platform in order to adjust memory storage for the media content items in the media-on-demand platform comprising the step
1. A method for selecting a data set in a form of a group of digital media content items from a plurality of groups of digital media content items for offer on a media-on-demand platform in order to adjust memory storage for the media content items in the media-on-demand platform comprising the steps of: providing a media-on-demand platform for offering groups of media content items for rent to users of the media-on-demand platform, wherein the media-on-demand platform allows for the digital media content items to be streamed from a media-on-demand server to the users via a data network,providing to a recommender system meta data of regarded media content items forming a plurality of regarded media groups, each regarded media group of regarded media content items comprising a plurality of regarded media content items, wherein the regarded media groups of regarded media content items are considered for being offered on the media-on-demand platform,the recommender system generating rated groups of rated media content items by determining, for a plurality of different users, a user specific like-rating for each regarded media content item, wherein the user specific like-rating is determined with regard to an assessment or an estimation based upon a rental history of the particular user of the media-on-demand platform, wherein the rental history and the user specific like-rating is stored in a database, wherein the rental history contains information about the media content items in a form of meta data,a number-of-rentals predictor, which is implemented in a data processor unit, estimating, for each of the rated media groups and for each of the plurality of different users, a respective user-specific number of rated media content items the respective user of the media-on-demand platform would rent from the respective rated group of rated media content items within a defined period of time, using information about the rental history of the particular user of the media-on-demand platform and the respective like-rating of the rated media content items,using a sum of the estimated user-specific numbers of rated media content items the respective user of the media-on-demand platform would rent from the respective rated group of rated media content items within the defined period of time, and using a predetermined price setting to evaluate an estimated revenue for each of the rated groups of rated media content items, andselecting from the rated groups of rated media content items that rated group of rated media content items which is associated with a highest among the estimated revenues, for offer on the media-on-demand platform. 2. The method according to claim 1, wherein the providing to the recommender system meta data of regarded media content items comprises the further step of compiling the regarded media groups, and whereinthe recommender system removes those media content items from the regarded media groups that have a user specific like-rating below a preset value. 3. The method according to claim 1, comprising the further step of: identifying and removing the regarded media content items the particular user has already rented from the regarded media group of regarded media content items by they recommender system. 4. The method according to claim 1, wherein the considered information about the rental history of the particular user comprises information about genre, persons involved in making the media content item, date of media release and/or a rental price of the media content item. 5. The method according to claim 1, comprising the further step of: generating a user specific ranking of the rated media content items by the recommender system according to the respective user specific like-rating of the rated media content items. 6. The method according to claim 5, comprising the further step of: removing rated content items with the worst user specific like-rating from the group of rated media content items by the recommender system. 7. The method according to claim 1, comprising the further step of: generating a quantified group of quantified media content items by determining the specific rated media content items the particular user will prospectively rent from the rated group of rated media content items by the number-of-rentals predictor, based on the determined user specific number of media content items the user will rent of the rated group and the particular user specific like-ratings of the rated media content items. 8. The method according to claim 7, comprising the further step of: determining the costs for renting each quantified media content item of the quantified group from a respective content provider by a financial evaluator unit. 9. The method according to claim 8, comprising the further step of: determining the turnover for renting the determined specific media content items to the particular user by the financial evaluator unit. 10. The method according to claim 9, comprising the further step of: calculating the difference between the determined costs and determined turnover and determining the expected profit or loss by the financial evaluator unit. 11. The method according to claim 10, wherein the media content items of the quantified group of each regarded user are merged to a merged group of media content items by the financial evaluator unit and the expected profit or expected loss is compared with a preset profit value or loss value by the financial evaluator unit. 12. The method according to claim 11, comprising the step of: adding the merged specific media content items the plurality of users will probably rent to the media-on-demand platform by the recommender system in case the expected profit is higher or equal to the preset profit value or the expected loss is lower or equal to the preset loss value. 13. The method according to claim 1, wherein the media content items of the quantified group of each regarded user are merged to a merged group of media content items by a financial evaluator unit. 14. The method according to claim 1, wherein the media content items are digital media content items. 15. The method according to claim 14, wherein the digital media content items are digital videos, digital photos, digital music, computer programs or digital texts. 16. A system for automatically executing the method for efficiently selecting media content items for offer on a media-on-demand platform according to claim 1, comprising: a recommender unit for determining user-specific like-ratings for media content items;a number-of-rentals predictor for determining the amount of media content items a user is expected to rent from the rated group of media content items; anda financial evaluator unit for generating a merged group of quantified media content items and for determining the expected profit or loss for providing specific media content items. 17. A method for efficiently compiling a data set in a form of a group of digital media content items from a plurality of groups of digital media content items for offer on a media-on-demand platform in order to adjust memory storage for the multiple of media content items in the media-on-demand platform comprising the steps of: providing a media-on-demand platform for offering groups of media content items for rent to users of the media-on-demand platform, wherein the media-on-demand platform allows for the digital media content items to be streamed from a media-on-demand server to the users via a data network,providing to a recommender system meta data of a regarded media group of regarded media content items forming a plurality of regarded media groups, each regarded media group of regarded media content items comprising a plurality of regarded media content items, wherein the regarded media groups of regarded media content items are considered for being offered on the media-on-demand platform,the recommender system generating rated groups of rated media content items by determining, for a plurality of different users, a user specific like-rating for each regarded media content item, wherein the user specific like-rating is determined with regard to an estimation based upon a rental history of the particular user and another representative of the media-on-demand platform, wherein the rental history and the user specific like-rating is stored in a database, wherein the rental history contains information about the media content items in a form of meta data, anda number-of-rentals predictor, which is implemented in a data processor unit, estimating, for each of the rated media groups and for each of the plurality of different users, a respective user specific number of rated media content items the respective user of the media-on-demand platform would rent from the respective rated group of rated media content items within a defined period of time, using information about the rental history of the particular user and other representative users of the media-on-demand platform and the respective like-rating of the rated media content items,using a sum of the estimated user-specific numbers of rated media content items the respective user of the media-on-demand platform would rent from the respective rated group of rated media content items within the defined period of time, and using a predetermined price setting to evaluate an estimated revenue for each of the rated groups of rated media content items, andcompiling from the rated media content items that rated group of rated media content items which is associated with a highest among the estimated revenues, for offer on the media-on-demand platform.
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이 특허에 인용된 특허 (2)
Kelly, Matthew F.; Kelly, Bryan M.; Petermeier, Norman B.; Kroeckel, John G.; Link, John E., Networked gaming system.
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