@inproceedings{c188878e602a4d75a299f628af2904a8,
title = "Modeling human intention in a live-feeling platform",
abstract = "This paper presents a Bayesian Network (BN) model of human intention in an entertainment environment. We present a framework for live-feeling communication that allows an intelligent system to reconfigure its action based on user preferences and intention. The user intentions are learned from a training set of model situations and a hierarchical model of soccer game is integrated with the user intention into a single BN. The trained model is tested on a data set gathered from users. The BN model shows an accuracy of up to 85%.",
keywords = "Live entertainment, Live-feeling communication, User intention estimation",
author = "Martin Lukac and Gaziza Oteniyaz and Michitaka Kameyama",
note = "Publisher Copyright: Copyright {\textcopyright} TRECVID 2016.All rights reserved. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 14th International Conference on Cognitive Modeling, ICCM 2016 ; Conference date: 03-08-2016 Through 06-08-2016",
year = "2016",
language = "English",
series = "Proceedings of ICCM 2016 - 14th International Conference on Cognitive Modeling",
publisher = "The Pennsylvania State University",
pages = "270--272",
editor = "David Reitter and Ritter, {Frank E.}",
booktitle = "Proceedings of ICCM 2016 - 14th International Conference on Cognitive Modeling",
}