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With the popularization of digital TV and Internet protocol TV (IPTV), more digital programs are being produced. In order to find the programs users want to watch, it is sometimes difficult and time-consuming for them to read the programs' information provided by electronic program guide (EPG). Therefore, the next generation EPG composed of content search, content recommendation, and content management is expected to help users quickly, and easily find programs they are interested in. In content recommendation, this study proposes a community-based program recommendation (CPR) for the next generation EPG. It analyzes and categorizes users with similar viewing habits into one community, then recommends programs to users to help them quickly find the programs they want to watch. The results show that this method can provide good precision and convenience to users.

With the rapid development of home network technology, sharing multimedia content among AV devices has become easier, however, the operation of these AV devices have become more complicated. These devices display status and related information through on-screen display (OSD) or liquid crystal display module (LCM) display, but the displays have some issues with OSD interference to reception or require users to understand all the symbols on the LCM display. This paper proposes a universal remote control based on AV device virtualization, called V-URC (virtualization based universal remote control), in order to control AV devices V-URC dynamically generates user interfaces, which conform to the current state of devices; this not only simplifies the operation of AV devices, but also eliminates the issues caused by LCM display and OSD-based AV devices In addition, for new AV devices, V-URC can be used directly without the need to go through complicated learning programs or update of firmware.

This paper has discussed a low complexity channel recommendation system on TV remote controller, which aims to, with limited processing speed and memory capacity, recommend interesting channels to viewers in various time intervals according to different preferences and habits. This system comprises two important parts: "three-dimensional bitmap for user behavior" and "channel-reference-bits algorithm". "Three-dimensional bitmap for user behavior" is used to record the behavior mode of watching TV and storage mode of preference data in a three-dimensional data space, while "channel-viewed-bits algorithm" is used to screen habitual channels of viewers from stored data.