Advertisement
Published in:
2013 | OriginalPaper | Chapter
Sub-sentence Extraction Based on Combinatorial Optimization
Authors : Norihito Yasuda, Masaaki Nishino, Tsutomu Hirao, Masaaki Nagata
Published in: Advances in Information Retrieval
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
This paper describes the prospect of word extraction for text summarization based on combinatorial optimization. Instead of the commonly used sentence-based approach, word-based approaches are preferable if highly-compressed summarizations are required. However, naively applying conventional methods for word extraction yields excessively fragmented summaries. We avoid this by restricting the number of selected fragments from each sentence to at most one when formulating the maximum coverage problem. Consequently, the method only choose
sub-sentences
as fragments. Experiments show that our method matches the ROUGE scores of state-of-the-art systems without requiring any training or special parameters.