IPTV Collaborative Filtering Recommendation System
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Solution Overview
Problem
IPTV users face difficulties in efficiently searching and selecting desired programs due to the vast number of channels and programs, with existing electronic program guides being inconvenient and slow, especially when over 10,000 channels are present, leading to most produced content going unused.
Innovation Solution
A system utilizing a collaborative filtering algorithm to recommend personalized favorite programs or channels by calculating user-program relationships, generating a real-time recommended program list, and displaying it on a TV screen, which includes a broadcast provider, service server, relay device, and TV, to efficiently recommend desired channels or programs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a traditional electronic program guide with channel-based/time-based table is used, then program information can be displayed, but the interface becomes inconvenient and difficult to use when more than 10,000 channels are present
Solution Approach 1:
The patent extracts the essential function of program information display from the traditional EPG table structure and presents it through a recommendation list format. Instead of showing all channels in a comprehensive table, the system extracts and presents only the recommended programs based on user preferences, thereby simplifying the interface while maintaining the ability to access extensive channel content.
Solution Approach 2:
The patent segments the vast number of channels into personalized recommendation lists based on user viewing history and preferences. By dividing the complete channel list into multiple themed or preference-based segments, the system makes navigation more manageable and intuitive, transforming the overwhelming 10,000+ channel list into digestible recommendation groups.
2Productivity
If navigation or program change is performed manually in traditional IPTV, then program selection is possible, but the process is too slow to directly see and select programs
Solution Approach 1:
The system performs preliminary action by pre-calculating and preparing personalized program recommendations based on user viewing history and preferences before the user needs to search. The recommendation list is generated in advance using collaborative filtering algorithms, so when the user accesses the EPG, the top recommended programs are already ready for immediate selection, eliminating the need for slow manual navigation through thousands of channels.
3Adaptability or versatility
If all produced TV programs are made available, then program variety is maximized, but 99.995% of produced programs remain unused and unviewed
Solution Approach 1:
The system implements feedback mechanisms by continuously analyzing user viewing behavior, ratings, and preferences to dynamically adjust program recommendations. This feedback loop ensures that the recommendation list evolves based on actual user preferences, maximizing the relevance of recommended programs while gradually reducing the proportion of unused content by learning from user interactions over time.
Solution Approach 2:
The patent applies local quality by tailoring the program recommendation list to individual user preferences and viewing patterns rather than presenting a uniform channel list. Each user receives a customized recommendation list based on their specific interests, ensuring that the high-quality, relevant programs are prioritized for each individual, thereby reducing overall program waste while maintaining variety.
Data Source
AI summary
A system for recommending personalized favorite programs or channels to internet protocol television (IPTV) users based on a collaborative filtering algorithm is disclosed. The system includes a broadcast provider as an IPTV broadcast provider that provides users with TV contents through the Internet, a service server to receive a broadcast signal and program information from the broadcast provider, to store corresponding information in respective databases, to calculate the program information based on a recommendation algorithm to quantitatively calculate priority, and to list the program information in recommendation order based on the currently broadcast or reproduced program, a relay device to receive recommended program list information and a broadcast signal from the service server and to transmit the recommended program list information and the broadcast signal through a network, and a TV to output the recommended program list information and the broadcast signal from the relay device.