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Digitalization of television signal has brought many changes not only to the way that data is presented, but also to amount of data that is being transferred. Transport stream provides user with big number of programs and very detailed information about every day's schedule. Aim of our solution is to present user the most appropriate TV shows from schedule and to help user to avoid energy and time consuming browsing through huge amount of data. Our solution should meet users viewing habits and tastes. In this paper experience during implementation of a recommendation engine dedicated to television data is presented. Focus is on requirements and environment (framework) for recommendation of television data. Future plans are also presented.

Age of digital television has brought many changes to television user's experience. On one side there is comfort because of great amount of data available in the stream and possibility of accessing the Internet over TV. On the other side great amount of data brings significant discomfort, if the data is not organized well and user has to browse through it for a long time. This paper describes a solution for recommending similar data originating from digital television stream or from the Internet. Aim of the presented solution is personalization of television content and related data from the Internet and also selection of most proper results. Main approaches are described and the solution is compared to some existing solutions.

Digital television has been a standard way of distributing television content for some time now. Even though digital television standards (e.g. DVB) usually provide some mechanisms for the distribution of metadata related to the broadcasted content (e.g. Electronic Program Guide, teletext, HbbTV, etc.), this information is mostly incomplete, missing and difficult to manage. In this paper, we describe a cloud based solution that copes with these problems by expanding the basic DTV metadata obtained from the broadcasters with content freely available on the internet and by employing a recommendation engine to filter and sort the content before delivering it to the users. For this purpose, we developed an acquisition system for acquiring base DTV metadata, a search engine for base metadata expansion and a simple recommendation engine for per-user content selection.

In last decades a vast number of textual analyzers have been developed. All those analyzers can be applied to textual data from any source, including Digital Video Broadcasting (DVB) stream. In this paper we propose a realization of a system whose primary purpose is DVB stream data acquisition. This solution can be used on a big variety of set-top boxes (STBs), considering their performances and capabilities and it presents an essential starting point for numerous types of systems, including television systems, personalized television systems etc.

This paper presents one solution for a extendable application which is used to collect EPG (Electronic Program Guide) data from various internet sources. The aim of the software is to complement or replace incomplete EPG information received from DTV (Digital television) stream with Internet data. The acquired data is processed and forwarded to remote server which further stores it to a database.