Name
Abstract | ||
|---|---|---|
We propose an approach to summarization exploiting both lexical information and the output of an automatic anaphoric resolver, and using Singular Value Decomposition (SVD) to identify the main terms. We demonstrate that adding anaphoric information results in significant performance improvements over a previously developed system, in which only lexical terms are used as the input to SVD. However, we also show that how anaphoric information is used is crucial: whereas using this information to add new terms does result in improved performance, simple substitution makes the performance worse. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.3115/1220575.1220576 | HLT/EMNLP |
Keywords | Field | DocType |
anaphoric information result,singular value decomposition,improved performance,main term,automatic anaphoric resolver,significant performance improvement,anaphoric information,anaphora resolution,improving lsa-based summarization,new term,lexical information,lexical term,singular value | Singular value decomposition,Resolver,Automatic summarization,Computer science,Speech recognition,Artificial intelligence,Natural language processing | Conference |
Volume | Citations | PageRank |
H05-1 | 14 | 0.89 |
References | Authors | |
13 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| josef steinberger | 1 | 355 | 26.95 |
| Mijail A. Kabadjov | 2 | 80 | 4.13 |
| Massimo Poesio | 3 | 1869 | 170.68 |
| Olivia Sanchez-Graillet | 4 | 55 | 5.10 |