Extractive-based Text Summarization Algorithm
(Redirected from extractive summarization)
An Extractive-based Text Summarization Algorithm is a data-driven text summarization algorithm that includes a sentence extraction task.
- Context:
- It can (typically) be a Sentence Extraction-based Text Summarization Algorithm.
- It can range from being a Single-Document Extractive Summarization Algorithm to being a Multi-Document Extractive Summarization Algorithm.
- It can range from being a General Extractive Summarization Algorithm to being a Topic-focused Extractive Summarization Algorithm.
- …
- Example(s):
- Counter-Example(s):
- See: MEAD Algorithm.
References
2015
- (Jha et al., 2015) ⇒ Rahul Jha, Reed Coke, and Dragomir Radev. (2015). “Surveyor: A System for Generating Coherent Survey Articles for Scientific Topics.” In: Ann Arbor, 1001.
- QUOTE: We investigate the task of generating coherent survey articles for scientific topics. We introduce an extractive summarization algorithm that combines a content model with a discourse model to generate coherent and readable summaries of scientific topics using text from scientific articles relevant to the topic.
2014
- (Wikipedia, 2014) ⇒ http://en.wikipedia.org/wiki/Automatic_summarization#Extraction-based_summarization Retrieved:2014-9-10.
- Two particular types of summarization often addressed in the literature are keyphrase extraction, where the goal is to select individual words or phrases to "tag" a document, and document summarization, where the goal is to select whole sentences to create a short paragraph summary.
2007
- (Das & Martins, 2007) ⇒ Dipanjan Das, and André F. T. Martins. (2007). “A Survey on Automatic Text Summarization." Literature Survey for the Language and Statistics II course at CMU, November, 2007 (unpublished).
2005
- (Melli et al., 2005) ⇒ Gabor Melli, Yang Wang, Yudong Liu, M. M. Kashani, Zhongmin Shi, Baohua Gu, Anoop Sarkar, and Fred Popowich. (2005). “Description of SQUASH, the SFU Question Answering Summary Handler for the DUC-2005 Summarization Task.” In: Proceedings of the Document Understanding Conference (DUC-2005).
2004
- (Erkan & Radev, 2004) ⇒ Günes Erkan, Dragomir R. Radev. (2004). “LexPageRank: Prestige in Multi-Document Text Summarization.” In: Proceedings of Empirical Methods in Natural Language Processing (EMNLP 2004).