Device and method for recommending program to IPTV (Internet protocol television) terminal user

Abstract

The invention relates to a device for recommending a program to an IPTV (Internet protocol television) terminal user, which is used for recommending a basic time period for watching a new program to the IPTV terminal user, wherein the basic time period has periodicity. The device comprises a user watch record database, a preference defining unit and a recommending unit, wherein the user watch record database is used for recording the program information of the programs watched by the user, and the program information includes the basic time periods of the programs watched by the user; the preference defining unit obtains the user watch record from the user watch record database, defines and calculates the preference weights of the programs watched in different basic time periods by the user, and sorts the preference weights according to the magnitude; and the recommending unit recommends the basic time period with high preference weight to the user to watch the new program according to the weight sorting result output by the preference defining unit. Through the invention, the functions of the IPTV service are expanded in a personalized manner, and the experience and satisfaction degree of the user are improved.

Description

technical field [0001] The present invention relates to the field of IPTV, and more specifically, relates to a device and method for recommending programs for IPTV terminal users. Background technique [0002] In the research fields related to social science and natural science, a large number of decision-making problems are inseparable from prediction, ranging from personal life to the entire country, will make predictions and judgments on the feasibility and pros and cons of some programs, so as to choose the most good behavior. As the basis of decision-making, forecast plays a very important role in program selection. At the same time, the information about things is often incomplete, and the relevant theories are not omnipotent and perfect. People's relevant understanding of things is limited to observation data, that is, time series, and then they can only use existing historical data to establish relevant models. And then predict the future. [0003] As an emerging ...

AI Technical Summary

Problems solved by technology

[0004] In the prior art, many personalized program recommendation schemes have been proposed, which essentially analyze the behavior of a single user (such as purchase behavior, viewing behavior, evaluation behavior, etc.) to predict the user's future behavior. The solution considers more factors such as recommending programs that IPTV users may like and how to implement the recommendation function based on the IP multimedia system, while ignoring the timing of the recommendation

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