On the Trade-off between Redundancy and Local Coherence in Summarization

Understand

Extractive summaries are usually presented as lists of sentences with no expected cohesion between them and with plenty of redundant information if not accounted for.

• In this paper, we investigate the trade-offs incurred when aiming to control for inter-sentential cohesion and redundancy in extracted summaries, and their impact on their informativeness.
• As case study, we focus on the summarization of long, highly redundant documents and consider two optimization scenarios, reward-guided and with no supervision.
• In the reward-guided scenario, we compare systems that control for redundancy and cohesion during sentence scoring.