Paper: Timeline Generation through Evolutionary Trans-Temporal Summarization

ACL ID D11-1040
Title Timeline Generation through Evolutionary Trans-Temporal Summarization
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2011
Authors

We investigate an important and challeng- ing problem in summary generation, i.e., Evolutionary Trans-Temporal Summarization (ETTS), which generates news timelines from massive data on the Internet. ETTS greatly facilitates fast news browsing and knowl- edge comprehension, and hence is a neces- sity. Given the collection of time-stamped web documents related to the evolving news, ETTS aims to return news evolution along the time- line, consisting of individual but correlated summaries on each date. Existing summariza- tion algorithms fail to utilize trans-temporal characteristics among these component sum- maries. We propose to model trans-temporal correlations among component summaries for timelines, using inter-date and intra-date sen- tence dependencies, and present a novel com- binatio...