In this book chapter, we discuss several pertinent aspects of an automatic system that generates summaries in multiple languages for sets of topic-related news articles (multilingual multi-document summarisation), gathered by news aggregation systems. The discussion follows a framework based on Latent Semantic Analysis (LSA) because LSA was shown to be a high-performing method across many different languages. Starting from a sentence-extractive approach we show how domain-specific aspects can be used and how a compression and paraphrasing method can be plugged in. We also discuss the challenging problem of summarisation evaluation in different languages. In particular, we describe two approaches: the first uses a parallel corpus and the second statistical machine translation.
Appears in Collections
Appears in Collections:
Institute for the Protection and Security of the Citizen
978-1-4666-5019-0 (print),978-1-4666-5020-6 (online)
2327-1981 (print),2327-199X (online)
Innovative Document Summarization Techniques: Revolutionizing Knowledge Understanding p. 277-294