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Exploring semi-automatic nugget extraction for Japanese one click access evaluation

Authors:

Matthew Ekstrand-Abueg,

Mayu IwataAuthors Info & Claims

SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

Pages 749 - 752

https://doi.org/10.1145/2484028.2484153

Published: 28 July 2013 Publication History

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Abstract

Building test collections based on nuggets is useful evaluating systems that return documents, answers, or summaries. However, nugget construction requires a lot of manual work and is not feasible for large query sets. Towards an efficient and scalable nugget-based evaluation, we study the applicability of semi-automatic nugget extraction in the context of the ongoing NTCIR One Click Access (1CLICK) task. We compare manually-extracted and semi-automatically-extracted Japanese nuggets to demonstrate the coverage and efficiency of the semi-automatic nugget extraction. Our findings suggest that the manual nugget extraction can be replaced with a direct adaptation of the English semi-automatic nugget extraction system, especially for queries for which the user desires broad answers from free-form text.

References

[1]

C. L. Clarke, M. Kolla, G. V. Cormack, O. Vechtomova, A. Ashkan, S. Büttcher, and I. MacKinnon. Novelty and diversity in information retrieval evaluation. In ACM SIGIR 2008, pages 659--666, 2009.

Digital Library

Google Scholar

[2]

J. A. et al. Frontiers, challenges and opportunities for information retrieval: Report from SWIRL 2012. SIGIR Forum, 46(1):2--32, 2012.

Digital Library

Google Scholar

[3]

Y. Freund and R. E. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. COLT '95.

Digital Library

Google Scholar

[4]

J. Li, S. Huffman, and A. Tokuda. Good abandonment in mobile and PC internet search. In ACM SIGIR 2009, pages 43--50, 2009.

Digital Library

Google Scholar

[5]

C.-Y. Lin. ROUGE: A package for automatic evaluation of summaries. In ACL 2004 Workshop on Text Summarization Branches Out, 2004.

Google Scholar

[6]

J. Lin and D. Demner-Fushman. Methods for automatically evaluating answers to complex questions. Information Retrieval, 9(5):565--587, 2006.

Digital Library

Google Scholar

[7]

T. Mitamura, H. Shima, T. Sakai, N. Kando, T. Mori, K. Takeda, C.-Y. Lin, R. Song, C.-J. Lin, and C.-W. Lee. Overview of the NTCIR-8 ACLIA tasks: Advanced cross-lingual information access. In NTCIR-8, pages 15--24, 2010.

Google Scholar

[8]

S. Rajput, M. Ekstrand-Abueg, V. Pavlu, and J. A. Aslam. Constructing test collections by inferring document relevance via extracted relevant information. In ACM CIKM 2012, pages 145--154, 2012.

Digital Library

Google Scholar

[9]

T. Sakai, M. P. Kato, and Y.-I. Song. Click the search button and be happy: Evaluating direct and immediate information access. In ACM CIKM 2011, pages 621--630, 2011.

Digital Library

Google Scholar

Cited By

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Wu DLiang S(2022)Mobile Search BehaviorsundefinedOnline publication date: 10-Mar-2022
Pareek JJhaveri M(2017)DLNEx: A Tool to Automatically Extract Desired Learning Nuggets from Various Learning MaterialsSmart Trends in Systems, Security and Sustainability10.1007/978-981-10-6916-1_30(319-330)Online publication date: 31-Dec-2017
Kato MSakai TYamamoto TIwata MJones GSheridan PKelly Dde Rijke MSakai T(2013)Report from the NTCIR-10 1CLICK-2 Japanese subtaskProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484117(753-756)Online publication date: 28-Jul-2013

Index Terms

Exploring semi-automatic nugget extraction for Japanese one click access evaluation
1. Information systems
  1. Information retrieval

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Published In

SIGIR '13: Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval

July 2013

1188 pages

ISBN:9781450320344

DOI:10.1145/2484028

General Chairs:
Gareth J.F. Jones
Dublin City University, Ireland
,
Páraic Sheridan
Dublin City University, Ireland
,
Program Chairs:
Diane Kelly
University of North Carolina, Chapel Hill, USA
,
Maarten de Rijke
University of Amsterdam, The Netherlands
,
Tetsuya Sakai
Microsoft Research Asia, China

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Association for Computing Machinery

New York, NY, United States

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Published: 28 July 2013

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SIGIR '13: The 36th International ACM SIGIR conference on research and development in Information Retrieval

July 28 - August 1, 2013

Dublin, Ireland

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SIGIR '13 Paper Acceptance Rate 73 of 366 submissions, 20%;

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

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Wu DLiang S(2022)Mobile Search BehaviorsundefinedOnline publication date: 10-Mar-2022
Pareek JJhaveri M(2017)DLNEx: A Tool to Automatically Extract Desired Learning Nuggets from Various Learning MaterialsSmart Trends in Systems, Security and Sustainability10.1007/978-981-10-6916-1_30(319-330)Online publication date: 31-Dec-2017
Kato MSakai TYamamoto TIwata MJones GSheridan PKelly Dde Rijke MSakai T(2013)Report from the NTCIR-10 1CLICK-2 Japanese subtaskProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484117(753-756)Online publication date: 28-Jul-2013

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Creation and evaluation of large keyphrase extraction collections with multiple opinions

IR system evaluation using nugget-based test collections

Automatic office document classification and information extraction

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