Paper: Multi-Document Summarisation Using Generic Relation Extraction

ACL ID D09-1044
Title Multi-Document Summarisation Using Generic Relation Extraction
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2009
Authors
  • Ben Hachey (Macquarie University, Sydney Australia; Capital Markets CRC Limited, Sydney Australia)

Experiments are reported that investi- gate the effect of various source docu- ment representations on the accuracy of the sentence extraction phase of a multi- document summarisation task. A novel representation is introduced based on generic relation extraction (GRE), which aims to build systems for relation iden- tification and characterisation that can be transferred across domains and tasks with- out modification of model parameters. Re- sults demonstrate performance that is sig- nificantly higher than a non-trivial base- line that uses tf*idf-weighted words and at least as good as a comparable but less gen- eral approach from the literature. Anal- ysis shows that the representations com- pared are complementary, suggesting that extraction performance could be further improved through...