Title | ||
---|---|---|
Revisiting the Centroid-based Method: A Strong Baseline for Multi-Document Summarization. |
Abstract | ||
---|---|---|
The centroid-based model for extractive document summarization is a simple and fast baseline that ranks sentences based on their similarity to a centroid vector. In this paper, we apply this ranking to possible summaries instead of sentences and use a simple greedy algorithm to find the best summary. Furthermore, we show possi- bilities to scale up to larger input docu- ment collections by selecting a small num- ber of sentences from each document prior to constructing the summary. Experiments were done on the DUC2004 dataset for multi-document summarization. We ob- serve a higher performance over the orig- inal model, on par with more complex state-of-the-art methods. |
Year | DOI | Venue |
---|---|---|
2017 | 10.18653/v1/w17-4511 | NFiS@EMNLP |
DocType | Volume | Citations |
Journal | abs/1708.07690 | 0 |
PageRank | References | Authors |
0.34 | 5 | 1 |
Name | Order | Citations | PageRank |
---|---|---|---|
Demian Gholipour Ghalandari | 1 | 0 | 0.34 |