Sentence ordering with event-enriched semantics and two-layered clustering for multi-document news summarization

Renxian Zhang, Wenjie Li, Qin Lu

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

10 Citations (Scopus)

Abstract

We propose an event-enriched model to alleviate the semantic deficiency problem in the IR-style text processing and apply it to sentence ordering for multi-document news summarization. The ordering algorithm is built on event and entity coherence, both locally and globally. To accommodate the eventenriched model, a novel LSA-integrated two-layered clustering approach is adopted. The experimental result shows clear advantage of our model over event-agonistic models.
Original languageEnglish
Title of host publicationColing 2010 - 23rd International Conference on Computational Linguistics, Proceedings of the Conference
Pages1489-1497
Number of pages9
Publication statusPublished - 1 Dec 2010
Event23rd International Conference on Computational Linguistics, Coling 2010 - Beijing, China
Duration: 23 Aug 201027 Aug 2010

Conference

Conference23rd International Conference on Computational Linguistics, Coling 2010
Country/TerritoryChina
CityBeijing
Period23/08/1027/08/10

ASJC Scopus subject areas

  • Language and Linguistics
  • Computational Theory and Mathematics
  • Linguistics and Language

Fingerprint

Dive into the research topics of 'Sentence ordering with event-enriched semantics and two-layered clustering for multi-document news summarization'. Together they form a unique fingerprint.

Cite this