Connecting the Dots Using Contextual Information Hidden in Text and Images
Abstract
Creation of summaries of events of interest from multitude of unstructured data is a challenging task commonly faced by intelligence analysts while seeking increased situational awareness. This paper proposes a framework called Storyboarding that leverages unstructured text and images to explain events as sets of sub-events. The framework first generates a textual context for each human face detected from images and then builds a chain of coherent documents where two consecutive documents of the chain contain a common theme as well as a context. Storyboarding helps analysts quickly narrow down large number of possibilities to a few significant ones for further investigation. Empirical studies on Wikipedia documents, images and news articles show that Storyboarding is able to provide deeper insights on events of interests.
Cite
Text
Kader et al. "Connecting the Dots Using Contextual Information Hidden in Text and Images." AAAI Conference on Artificial Intelligence, 2016. doi:10.1609/AAAI.V30I1.9930Markdown
[Kader et al. "Connecting the Dots Using Contextual Information Hidden in Text and Images." AAAI Conference on Artificial Intelligence, 2016.](https://mlanthology.org/aaai/2016/kader2016aaai-connecting/) doi:10.1609/AAAI.V30I1.9930BibTeX
@inproceedings{kader2016aaai-connecting,
title = {{Connecting the Dots Using Contextual Information Hidden in Text and Images}},
author = {Kader, Md. Abdul and Naim, Sheikh Motahar and Boedihardjo, Arnold P. and Hossain, Mahmud Shahriar},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2016},
pages = {4220-4221},
doi = {10.1609/AAAI.V30I1.9930},
url = {https://mlanthology.org/aaai/2016/kader2016aaai-connecting/}
}