Paper Info
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 Ghalandari100.34