Recommendation method of smart TV programs reflecting content consumption concentration calculation

Personalized Recommendation of TV Programs

This paper presents the recommendation techniques applied in Personal Program Guide (PPG), a system generating personalized Electronic Program Guides for digital TV. The PPG recommends TV programs by relying on the integration of heterogeneous user modeling techniques. Copyright Springer Verlag. This paper is going to appear in the Proceedings of the 8th AI*IA Conference, Pisa, 2003, published ...

Fuzzy Clustering Based Ad Recommendation for TV Programs

Advertisements(Ads) are the main revenue earner for Television (TV) broadcasters. As TV reaches a large audience, it acts as the best media for advertisements of products and services. With the emergence of digital TV, it is important for the broadcasters to provide an intelligent service according to the various dimensions like program features, ad features, viewers’ interest and sponsors’ pre...

VecLP: A Realtime Video Recommendation System for Live TV Programs

We propose VecLP, a novel Internet Video recommendation system working for Live TV Programs in this paper. Given little information on the live TV programs, our proposed VecLP system can effectively collect necessary information on both the programs and the subscribers as well as a large volume of related online videos, and then recommend the relevant Internet videos to the subscribers. For tha...

Reflecting on the Workshop on Interactive Content Consumption (WSICC) Series

Starting Dose Calculation for Medicinal Plants in Animal Studies; Recommendation of a Simple and Reliable Method

Background and purpose: Research studies indicate that almost 80% of the present day drugs are derived directly or indirectly from medicinal plants. The estimation of a safe starting dose is a concern when a new substance is to be investigated including medicinal plants, in clinical and laboratory studies. This study was intended to explore a simple and reliable method of calcu...