A finegrained digestion of news webpages through Event Snippet Extraction
Rui Yan, Liang Kong, Yu Li, Zhang Yan, Xiaoming Li · 2011
We describe a framework to digest news webpages in finer granularity: to extract event snippets from contexts. "Events" are atomic text snippets and a news article is constituted by more than one event snippet. Event Snippet Extraction (ESE) aims to mine these snippets out. The problem is important because its solutions may be applied to many information mining and retrieval tasks. The challenge is to exploit rich features to detect snippet boundaries, including various semantic, syntactic and visual features. We run experiments to present the effectiveness of our approaches.