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    <titleInfo>
        <title>Predicting Judgments and Grants for Civil Cases of Alimony for the Elderly</title>
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    <name type="personal">
        <namePart type="given">Wei-Zhi</namePart>
        <namePart type="family">Liu</namePart>
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    <name type="personal">
        <namePart type="given">Po-Hsien</namePart>
        <namePart type="family">Wu</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Hong-Ren</namePart>
        <namePart type="family">Lin</namePart>
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            <roleTerm authority="marcrelator" type="text">author</roleTerm>
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    <name type="personal">
        <namePart type="given">Chao-Lin</namePart>
        <namePart type="family">Liu</namePart>
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            <title>Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)</title>
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            <publisher>The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)</publisher>
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    <abstract>The needs for mediation are increasing rapidly along with the increasing number of cases of the alimony for the elderly in recent years. Offering a prediction mechanism for predicting the outcomes of some prospective lawsuits may alleviate the workload of the mediation courts. This research aims to offer the predictions for the judgments and the granted alimony for the plaintiffs of such civil cases in Chinese, based on our analysis of results of the past lawsuits. We hope that the results can be helpful for both the involved parties and the courts. To build the current system, we segment and vectorize the texts of the judgement documents, and apply the logistic regression and model tree models for predicting the judgments and for estimating the granted alimony of the cases, respectively.</abstract>
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        <url>https://aclanthology.org/2022.rocling-1.16</url>
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        <date>2022-11</date>
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            <start>121</start>
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%0 Conference Proceedings
%T Predicting Judgments and Grants for Civil Cases of Alimony for the Elderly
%A Liu, Wei-Zhi
%A Wu, Po-Hsien
%A Lin, Hong-Ren
%A Liu, Chao-Lin
%S Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022)
%D 2022
%8 November
%I The Association for Computational Linguistics and Chinese Language Processing (ACLCLP)
%C Taipei, Taiwan
%G Chinese
%F liu-etal-2022-predicting
%X The needs for mediation are increasing rapidly along with the increasing number of cases of the alimony for the elderly in recent years. Offering a prediction mechanism for predicting the outcomes of some prospective lawsuits may alleviate the workload of the mediation courts. This research aims to offer the predictions for the judgments and the granted alimony for the plaintiffs of such civil cases in Chinese, based on our analysis of results of the past lawsuits. We hope that the results can be helpful for both the involved parties and the courts. To build the current system, we segment and vectorize the texts of the judgement documents, and apply the logistic regression and model tree models for predicting the judgments and for estimating the granted alimony of the cases, respectively.
%U https://aclanthology.org/2022.rocling-1.16
%P 121-128

Markdown (Informal)

[Predicting Judgments and Grants for Civil Cases of Alimony for the Elderly](https://aclanthology.org/2022.rocling-1.16) (Liu et al., ROCLING 2022)

• Predicting Judgments and Grants for Civil Cases of Alimony for the Elderly (Liu et al., ROCLING 2022)

ACL

• Wei-Zhi Liu, Po-Hsien Wu, Hong-Ren Lin, and Chao-Lin Liu. 2022. Predicting Judgments and Grants for Civil Cases of Alimony for the Elderly. In Proceedings of the 34th Conference on Computational Linguistics and Speech Processing (ROCLING 2022), pages 121–128, Taipei, Taiwan. The Association for Computational Linguistics and Chinese Language Processing (ACLCLP).