Article

Free access

The use of MMR, diversity-based reranking for reordering documents and producing summaries

Authors:

SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval

Pages 335 - 336

https://doi.org/10.1145/290941.291025

Published: 01 August 1998 Publication History

PDF eReader

Abstract

No abstract available.

References

[1]

Buckley C. implementation of the smart information retrieval system. Technical Report Tit 85-686, Cornell University.

Digital Library

Google Scholar

[2]

J.G.Carbonell, Y. Geng, and J. Goldstein. Automated query-relevant summarization and diversity-based reranking. In 15th International Joint ConJerence on Artificial Intelligence, Workshop: AI in Digital Libraries, pages 9- 14, Nagoya, Japan, August 1997.

Google Scholar

[3]

J.M. Kupiec, J. Pedersen, and F. Chen. A trainable document summarizer. In Proceeding8 of the 18th Annual Int. A CM/SIGIR Conference on Research and Development in IR, pages 68-73, Seattle, WA, July 1995.

Crossref

Google Scholar

[4]

P.H. Luhn. Automatic creation of literature abstracts. IBM Journal, pages 159-165, 1958.

Digital Library

Google Scholar

[5]

G. Salton. Automatic Text Processing: The Transformation, Analysis, and Retrieval oJ Information by Computer. Addison-Wesley, 1989.

Digital Library

Google Scholar

[6]

In TIPSTER Text Phase 11I 18-Month Workshop, Fairfax, VA, May 1998.

Google Scholar

Cited By

View all

Preiss AArbeit CBerghammer ABollenbacher JMcCarthy JBrom MEnger MRios Villacorta NStraughn S(2024)Evaluation of Text Cluster Naming with Generative Large Language ModelsJournal of Data Science10.6339/24-JDS1149(376-392)Online publication date: 26-Aug-2024
https://doi.org/10.6339/24-JDS1149
Hirata EWatanabe DChalmoukis ALambrou M(2024)A Topic Modeling Approach to Determine Supply Chain Management Priorities Enabled by Digital Twin TechnologySustainability10.3390/su1609355216:9(3552)Online publication date: 24-Apr-2024
https://doi.org/10.3390/su16093552
Son HHan YNam KHan SYoo G(2024)Development of a News Trend Visualization System based on KPF-BERT for Event Changes and Entity Sentiment AnalysisThe Journal of Korean Institute of Information Technology10.14801/jkiit.2024.22.1.20322:1(203-213)Online publication date: 31-Jan-2024
https://doi.org/10.14801/jkiit.2024.22.1.203
Show More Cited By

Index Terms

The use of MMR, diversity-based reranking for reordering documents and producing summaries
1. Information systems
  1. Data management systems
    1. Database management system engines
      1. Database query processing
  2. Information retrieval
    1. Evaluation of retrieval results
      1. Relevance assessment
    2. Information retrieval query processing
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

Recommendations

The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries
SIGIR Test-of-Time Awardees 1978-2001
CCG syntactic reordering models for phrase-based machine translation
WMT '12: Proceedings of the Seventh Workshop on Statistical Machine Translation

Statistical phrase-based machine translation requires no linguistic information beyond word-aligned parallel corpora (Zens et al., 2002; Koehn et al., 2003). Unfortunately, this linguistic agnosticism often produces ungrammatical translations. Syntax, ...
Sentence type based reordering model for statistical machine translation
COLING '08: Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1

Many reordering approaches have been proposed for the statistical machine translation (SMT) system. However, the information about the type of source sentence is ignored in the previous works. In this paper, we propose a group of novel reordering models ...

Comments

Information & Contributors

Information

Published In

SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval

August 1998

394 pages

ISBN:1581130155

DOI:10.1145/290941

Chairmen:
W. Bruce Croft
Univ. of Massachusetts
,
Alistair Moffat
Univ. of Melbourne, Victoria, Australia
,
C. J. van Rijsbergen
Univ. of Glasgow, Scotland, UK
,
Ross Wilkinson
RMIT Univ., Australia and CSIRO
,
Justin Zobel
RMIT Univ., Australia

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 1998

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Article

Conference

SIGIR98

Sponsor:

University of Melbourne
SIGIR

SIGIR98: 21st Annual ACM/SIGIR International Conference on Research and Development in Information Retrieval

August 24 - 28, 1998

Melbourne, Australia

Acceptance Rates

Overall Acceptance Rate 792 of 3,983 submissions, 20%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

1,659
Total Citations
View Citations
8,747
Total Downloads

Downloads (Last 12 months)1,494
Downloads (Last 6 weeks)175

Reflects downloads up to 14 Sep 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Preiss AArbeit CBerghammer ABollenbacher JMcCarthy JBrom MEnger MRios Villacorta NStraughn S(2024)Evaluation of Text Cluster Naming with Generative Large Language ModelsJournal of Data Science10.6339/24-JDS1149(376-392)Online publication date: 26-Aug-2024
https://doi.org/10.6339/24-JDS1149
Hirata EWatanabe DChalmoukis ALambrou M(2024)A Topic Modeling Approach to Determine Supply Chain Management Priorities Enabled by Digital Twin TechnologySustainability10.3390/su1609355216:9(3552)Online publication date: 24-Apr-2024
https://doi.org/10.3390/su16093552
Son HHan YNam KHan SYoo G(2024)Development of a News Trend Visualization System based on KPF-BERT for Event Changes and Entity Sentiment AnalysisThe Journal of Korean Institute of Information Technology10.14801/jkiit.2024.22.1.20322:1(203-213)Online publication date: 31-Jan-2024
https://doi.org/10.14801/jkiit.2024.22.1.203
Schmidl SNaumann FPapenbrock T(2024)AutoTSAD: Unsupervised Holistic Anomaly Detection for Time Series DataProceedings of the VLDB Endowment10.14778/3681954.368197817:11(2987-3002)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.14778/3681954.3681978
Erlich AJung DLong J(2024)Covering the Campaign: Computational Tools for Measuring Differences in Candidate and Party News Coverage With Application to an Emerging DemocracySocial Science Computer Review10.1177/08944393241247420Online publication date: 18-Apr-2024
https://doi.org/10.1177/08944393241247420
Hark CUçkan TKarcı A(2024)A new multi-document summarisation approach using saplings growing-up optimisation algorithmsJournal of Information Science10.1177/0165551522110184150:3(635-650)Online publication date: 1-Jun-2024
https://dl.acm.org/doi/10.1177/01655515221101841
Fu ZNiu XWu XRahman R(2024)A Deep Learning Model for Cross-Domain Serendipity RecommendationsACM Transactions on Recommender Systems10.1145/3690654Online publication date: 29-Aug-2024
https://doi.org/10.1145/3690654
Xi YLiu WDai XTang RLiu QZhang WYu Y(2024)Utility-Oriented Reranking with Counterfactual ContextACM Transactions on Knowledge Discovery from Data10.1145/367100418:8(1-22)Online publication date: 4-Jun-2024
https://dl.acm.org/doi/10.1145/3671004
Zhao YWang YLiu YCheng XAggarwal CDerr T(2024)Fairness and Diversity in Recommender Systems: A SurveyACM Transactions on Intelligent Systems and Technology10.1145/3664928Online publication date: 21-May-2024
https://doi.org/10.1145/3664928
Wu HMitra BCraswell NOosterhuis HBast HXiong C(2024)Towards Group-aware Search SuccessProceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval10.1145/3664190.3672526(123-131)Online publication date: 2-Aug-2024
https://dl.acm.org/doi/10.1145/3664190.3672526
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Cited By

Index Terms

Recommendations

The Use of MMR, Diversity-Based Reranking for Reordering Documents and Producing Summaries

CCG syntactic reordering models for phrase-based machine translation

Sentence type based reordering model for statistical machine translation