<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="avvaru-pandey-2019-codeforthechange">
    <titleInfo>
        <title>CodeForTheChange at SemEval-2019 Task 8: Skip-Thoughts for Fact Checking in Community Question Answering</title>
    </titleInfo>
    <name type="personal">
        <namePart type="given">Adithya</namePart>
        <namePart type="family">Avvaru</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <name type="personal">
        <namePart type="given">Anupam</namePart>
        <namePart type="family">Pandey</namePart>
        <role>
            <roleTerm authority="marcrelator" type="text">author</roleTerm>
        </role>
    </name>
    <originInfo>
        <dateIssued>2019-06</dateIssued>
    </originInfo>
    <typeOfResource>text</typeOfResource>
    <relatedItem type="host">
        <titleInfo>
            <title>Proceedings of the 13th International Workshop on Semantic Evaluation</title>
        </titleInfo>
        <name type="personal">
            <namePart type="given">Jonathan</namePart>
            <namePart type="family">May</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Ekaterina</namePart>
            <namePart type="family">Shutova</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Aurelie</namePart>
            <namePart type="family">Herbelot</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Xiaodan</namePart>
            <namePart type="family">Zhu</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Marianna</namePart>
            <namePart type="family">Apidianaki</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <name type="personal">
            <namePart type="given">Saif</namePart>
            <namePart type="given">M</namePart>
            <namePart type="family">Mohammad</namePart>
            <role>
                <roleTerm authority="marcrelator" type="text">editor</roleTerm>
            </role>
        </name>
        <originInfo>
            <publisher>Association for Computational Linguistics</publisher>
            <place>
                <placeTerm type="text">Minneapolis, Minnesota, USA</placeTerm>
            </place>
        </originInfo>
        <genre authority="marcgt">conference publication</genre>
    </relatedItem>
    <abstract>The strengths of the scalable gradient tree boosting algorithm, XGBoost and distributed sentence encoder, Skip-Thought Vectors are not explored yet by the cQA research community. We tried to apply and combine these two effective methods for finding factual nature of the questions and answers. The work also include experimentation with other popular classifier models like AdaBoost Classifier, DecisionTree Classifier, RandomForest Classifier, ExtraTrees Classifier, XGBoost Classifier and Multi-layer Neural Network. In this paper, we present the features used, approaches followed for feature engineering, models experimented with and finally the results.</abstract>
    <identifier type="citekey">avvaru-pandey-2019-codeforthechange</identifier>
    <identifier type="doi">10.18653/v1/S19-2199</identifier>
    <location>
        <url>https://aclanthology.org/S19-2199</url>
    </location>
    <part>
        <date>2019-06</date>
        <extent unit="page">
            <start>1138</start>
            <end>1143</end>
        </extent>
    </part>
</mods>
</modsCollection>

%0 Conference Proceedings
%T CodeForTheChange at SemEval-2019 Task 8: Skip-Thoughts for Fact Checking in Community Question Answering
%A Avvaru, Adithya
%A Pandey, Anupam
%Y May, Jonathan
%Y Shutova, Ekaterina
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Apidianaki, Marianna
%Y Mohammad, Saif M.
%S Proceedings of the 13th International Workshop on Semantic Evaluation
%D 2019
%8 June
%I Association for Computational Linguistics
%C Minneapolis, Minnesota, USA
%F avvaru-pandey-2019-codeforthechange
%X The strengths of the scalable gradient tree boosting algorithm, XGBoost and distributed sentence encoder, Skip-Thought Vectors are not explored yet by the cQA research community. We tried to apply and combine these two effective methods for finding factual nature of the questions and answers. The work also include experimentation with other popular classifier models like AdaBoost Classifier, DecisionTree Classifier, RandomForest Classifier, ExtraTrees Classifier, XGBoost Classifier and Multi-layer Neural Network. In this paper, we present the features used, approaches followed for feature engineering, models experimented with and finally the results.
%R 10.18653/v1/S19-2199
%U https://aclanthology.org/S19-2199
%U https://doi.org/10.18653/v1/S19-2199
%P 1138-1143

Markdown (Informal)

[CodeForTheChange at SemEval-2019 Task 8: Skip-Thoughts for Fact Checking in Community Question Answering](https://aclanthology.org/S19-2199) (Avvaru & Pandey, SemEval 2019)

• CodeForTheChange at SemEval-2019 Task 8: Skip-Thoughts for Fact Checking in Community Question Answering (Avvaru & Pandey, SemEval 2019)

ACL

• Adithya Avvaru and Anupam Pandey. 2019. CodeForTheChange at SemEval-2019 Task 8: Skip-Thoughts for Fact Checking in Community Question Answering. In Proceedings of the 13th International Workshop on Semantic Evaluation, pages 1138–1143, Minneapolis, Minnesota, USA. Association for Computational Linguistics.