In Taiwan, there are different types of TV programs, and each program usually has its broadcast length and frequency. We accumulate the broadcasted TV programs’ word-ofmouth on Facebook and apply the Backpropagation Network to predict the latest program audience rating. TV audience rating is an important indicator regarding the popularity of programs and it is also a factor to influence the rev...

Matrix Factorization (MF) is known as an effective technique in collaborative filtering for recommendation. The MF approaches have often been applied for movie recommender systems which have user rating data. However, they cannot effectively be applicable for TV program recommender systems because (i) explicit rating values are not available; (ii) many TV programs are broadcast under single TV ...

This paper presents a novel method of measuring the similarity between TV programs by using summaries of the Electronic Program Guide (EPG). Most previous methods use statistics such as the TFIDF based cosine measure of word vectors, whose elements are words appearing in the summaries. However, these approaches are not effective because TV program summaries, especially short ones, do not necess...

In this paper, we present TV Scout, a recommendation system providing users with personalized TV schedules. The TV Scout architecture addresses the “cold-start” problem of information filtering systems, i.e. that filtering systems have to gather information about the user’s interests before they can compute personalized recommendations. Traditionally, gathering this information involves upfront...

It is common today to see digital content made by nonprofessionals. This is particularly true on the Internet where numerous armature movies can be found in blogs and Social Network Systems such as Facebook, Twitter, etc. and in movie sharing services such as YouTube. However, TV-program-like film clips with high production value are found less frequently. There is still a considerable barrier ...

This paper describes a TV program generation system using digest video scenes that are retrieved from video streams with the program indexes. The key features of the system are: (1) TV programs can be dynamically generated from digest video scenes selected by user preference. (2) Directions can be added using a happiness or sadness level based on the user preferences. (3) Personalized TV progra...

Collaborative filtering(CF) for the personalized recommendation is a successful and popular method in recommender systems. But the mainly researched and implemented cases focus on dealing with independent items with explicit feedback by users. For the domain of TV program recommendation in VOD service platform, we need to consider the unique characteristic and constraints of the domain. In this...

Recently, many researchers are paying close attention to TV program recommendation methods because of the enormous increase of available TV programs for users. As TV programs are often watched by multiple users like a family, this paper proposes a smart TV program recommendation method for multi-users using Bayesian networks and AHP (analytic hierarchy process). The proposed method uses Bayesia...

This paper presents Composer, an authoring tool to help creating interactive TV programs for the Brazilian Terrestrial Digital TV System. In Composer, several abstractions are defined creating different document views (structural, temporal, layout and textual). One of these views, the temporal view, preserves as much as possible the timeline paradigm, so popular in TV program editing. Using thi...

The present study was undertaken to study of creativity in relation to TV viewing habits of secondary school students. The sample consists of 400 secondary school students of Rampur city. Verbal test of creativity and TV viewing habits questionnaire were used for this investigation. The result of this study shows that on some behalf TV viewing is negatively related to creativity but overall TV ...