TV Content Recommender System
Abstract
The plethora of content available to the consumer has become overwhelming. Increasing amounts of information are being disseminated through terrestrial broadcast, satellite, and cable leading to an information overload. Common modes of searching for TV programs currently in existence include: TV-guide, PreVue channel and rudimentary search tools available through satellite dish TV programming service. These tools are general-purpose in nature and are not specifically tailored to the individual viewer’s taste. Towards that end we advance in this paper a recommender system that searches for TV programs based on their likes/dislikes through implicit personalization techniques.
Cite
Text
Gutta et al. "TV Content Recommender System." AAAI Conference on Artificial Intelligence, 2000.Markdown
[Gutta et al. "TV Content Recommender System." AAAI Conference on Artificial Intelligence, 2000.](https://mlanthology.org/aaai/2000/gutta2000aaai-tv/)BibTeX
@inproceedings{gutta2000aaai-tv,
title = {{TV Content Recommender System}},
author = {Gutta, Srinivas and Kurapati, Kaushal and Lee, K. P. and Martino, Jacquelyn and Milanski, John and Schaffer, J. David and Zimmerman, John},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2000},
pages = {1121-1122},
url = {https://mlanthology.org/aaai/2000/gutta2000aaai-tv/}
}