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

Published: 28 July 2013 Publication History

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.

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Cited By

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  • (2018)Mobile Search Behavious: An In-depth Analysis based on Contexts, APPs, and DevicesSynthesis Lectures on Information Concepts, Retrieval, and Services10.2200/S00831ED1V01Y201802ICR06310:2(i-159)Online publication date: 19-Mar-2018
  • (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
  • (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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  1. Exploring semi-automatic nugget extraction for Japanese one click access evaluation

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    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
    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 the author(s) 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].

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    Publication History

    Published: 28 July 2013

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    Author Tags

    1. evaluation
    2. information units
    3. ntcir
    4. nuggets
    5. summaries
    6. test collections

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

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    View all
    • (2018)Mobile Search Behavious: An In-depth Analysis based on Contexts, APPs, and DevicesSynthesis Lectures on Information Concepts, Retrieval, and Services10.2200/S00831ED1V01Y201802ICR06310:2(i-159)Online publication date: 19-Mar-2018
    • (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
    • (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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