Multimodal News Article Analysis
Abstract
The intersection of Computer Vision and Natural Language Processing has been a hot topic of research in recent years, with results that were unthinkable only a few years ago. In view of this progress, we want to highlight online news articles as a potential next step for this area of research. The rich interrelations of text, tags, images or videos, as well as a vast corpus of general knowledge are an exciting benchmark for high-capacity models such as the deep neural networks. In this paper we present a series of tasks and baseline approaches to leverage corpus such as the BreakingNews dataset.
Cite
Text
Ramisa. "Multimodal News Article Analysis." International Joint Conference on Artificial Intelligence, 2017. doi:10.24963/IJCAI.2017/737Markdown
[Ramisa. "Multimodal News Article Analysis." International Joint Conference on Artificial Intelligence, 2017.](https://mlanthology.org/ijcai/2017/ramisa2017ijcai-multimodal/) doi:10.24963/IJCAI.2017/737BibTeX
@inproceedings{ramisa2017ijcai-multimodal,
title = {{Multimodal News Article Analysis}},
author = {Ramisa, Arnau},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2017},
pages = {5136-5140},
doi = {10.24963/IJCAI.2017/737},
url = {https://mlanthology.org/ijcai/2017/ramisa2017ijcai-multimodal/}
}