@inproceedings{lu2016cross-media,
author = {Lu, Di and Voss, Clare R. and Tao, Fangbo and Ren, Xiang and Guan, Rachel and Korolov, Rostyslav and Zhang, Tongtao and Wang, Dongang and Li, Hongzhi and Cassidy, Taylor and Ji, Heng and Chang, Shih-fu and Han, Jiawei and Wallace, William and Hendler, James and Si, Mei and Kaplan,  Lance},
title = {Cross-media Event Extraction and Recommendation},
booktitle = {Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations},
year = {2016},
month = {June},
abstract = {The sheer volume of unstructured multimedia data (e.g., texts, images, videos) posted on the Web during events of general interest is overwhelming and difficult to distill if seeking information relevant to a particular concern. We have developed a comprehensive system that searches, identifies, organizes and summarizes complex events from multiple data modalities. It also recommends events related to the user’s ongoing search based on previously selected attribute values and dimensions of events being viewed. In this paper we briefly present the algorithms of each component and demonstrate the system’s capabilities.},
publisher = {Association for Computational Linguistics},
url = {http://approjects.co.za/?big=en-us/research/publication/cross-media-event-extraction-recommendation/},
pages = {72-76},
edition = {Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations},
}