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

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationSAC '16 Proceedings of the 31st Annual ACM Symposium on Applied Computing
Number of pages8
Place of PublicationNew York, NY
PublisherACM, Association for Computing Machinery
Publication date2016
Pages853-860
ISBN (Print)978-1-4503-3739-7
DOIs
Publication statusPublished - 2016
MoE publication typeA4 Article in conference proceedings
EventACM Symposium on Applied Computing - Pisa, Italy
Duration: 4 Apr 20168 Apr 2016
Conference number: 31

Fields of Science

  • 113 Computer and information sciences

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