Language-Independent Multi-Document Text Summarization with Document-Specific Word Associations

Forskningsoutput: Kapitel i bok/rapport/konferenshandlingKonferensbidragVetenskapligPeer review


The goal of automatic text summarization is to generate an abstract of a document or a set of documents. In this paper we propose a
word association based method for generating summaries in a variety of
languages. We show that a robust statistical method for finding associations
which are specific to the given document(s) is applicable to many languages.
We introduce strategies that utilize the discovered associations
to effectively select sentences from the document(s) to constitute the summary.
Empirical results indicate that the method works
reliably in a relatively large set of languages and outperforms methods reported
in MultiLing 2013.
Titel på värdpublikationSAC '16 Proceedings of the 31st Annual ACM Symposium on Applied Computing
Antal sidor8
UtgivningsortNew York, NY
FörlagACM, Association for Computing Machinery
ISBN (tryckt)978-1-4503-3739-7
StatusPublicerad - 2016
MoE-publikationstypA4 Artikel i en konferenspublikation
EvenemangACM Symposium on Applied Computing - Pisa, Italien
Varaktighet: 4 apr. 20168 apr. 2016
Konferensnummer: 31


  • 113 Data- och informationsvetenskap

Citera det här