Summarization of Historical Articles Using Temporal Event Clustering
James Gung, Jugal Kumar Kalita · 2012
In this paper, we investigate the use of temporal information for improving extractive summarization of historical articles. Our method clusters sentences based on their timestamps and temporal similarity. Each resulting cluster is assigned an importance score which can then be used as a weight in traditional sentence ranking techniques. Temporal importance weighting offers consistent improvements over baseline systems. 1