Artex is AnotheR TEXt summarizer
This is an incremental improvement for text summarization tasks, potentially benefiting researchers and practitioners in natural language processing.
The paper tackles automatic text summarization by introducing Artex, which ranks sentences using inner products with document and lexical vectors and assembles top-ranked sentences without rule-based post-processing, achieving interesting results on multilingual datasets from DUC and TAC.
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.