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Adaptive maximum marginal relevance based multi-email summarization

  • School of Computer Science and Technology, Harbin Institute of Technology

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

Abstract

By analyzing the inherent relationship between the maximum marginal relevance (MMR) model and the content cohesion of emails with the same subject, this paper presents an adaptive maximum marginal relevance based multi-email summarization method. Due to the adoption of approximate computing of email content cohesion, the adaptive MMR is able to automatically adjust the parameters according to the changing of the email sets. The experimental results have shown that the email summarizing system based on this technique can increase the precision while reducing the redundancy of the automatic summary results, consequently improve the average quality of email summaries.

Original languageEnglish
Title of host publicationArtificial Intelligence and Computational Intelligence - International Conference, AICI 2009, Proceedings
Pages417-424
Number of pages8
DOIs
StatePublished - 2009
Externally publishedYes
EventInternational Conference on Artificial Intelligence and Computational Intelligence, AICI 2009 - Shanghai, China
Duration: 7 Nov 20098 Nov 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5855 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Artificial Intelligence and Computational Intelligence, AICI 2009
Country/TerritoryChina
CityShanghai
Period7/11/098/11/09

Keywords

  • Adaptive model
  • Content cohesion
  • Maximum marginal relevance
  • Multi-email summarization

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