Year: 2012
Type: preprint
Abstract: This paper describes Artex, another algorithm for Automatic Text Summarization. In order to rank sentences, a simple inner product is calculated between each sentence, a document vector (text topic) and a lexical vector (vocabulary used by a sentence). Summaries are then generated by assembling the highest ranked sentences. No ruled-based linguistic post-processing is necessary in order to obtain summaries. Tests over several datasets (coming from Document Understanding Conferences (DUC), Text Analysis Conferences (TAC), evaluation campaigns, etc.) in French, English and Spanish have shown that summarizer achieves interesting results.
Source: arXiv (Cornell University)
Author: Torres-Moreno, Juan-Manuel
Institution: Université d'Avignon et des Pays de Vaucluse
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W1784635377