Summarizing online user reviews using bicliques
Paper i proceeding, 2016

With vast amounts of text being available in electronic format, such as news and social media, automatic multi-document summarization can help extract the most important information. We present and evaluate a novel method for automatic extractive multi-document summarization. The method is purely combinatorial, based on bicliques in the bipartite word-sentence occurrence graph. It is particularly suited for collections of very short, independently written texts (often single sentences) with many repeated phrases, such as customer reviews of products. The method can run in subquadratic time in the number of documents, which is relevant for the application to large collections of documents.

extractive summarization

bipartite clique

word frequency

Författare

Muhammad Azam Sheikh

Saudi Electronic University (SEU)

Peter Damaschke

Chalmers, Data- och informationsteknik, Datavetenskap

Olof Mogren

Chalmers, Data- och informationsteknik, Datavetenskap

Lecture Notes in Computer Science

0302-9743 (ISSN)

Vol. 9587 569-579

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Beräkningsmatematik

Systemvetenskap

Fundament

Grundläggande vetenskaper

DOI

10.1007/978-3-662-49192-8_46

ISBN

9783662491911

Mer information

Skapat

2017-10-08