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        <title type="main">SIS 2017. Statistics and Data Science: new challenges, new generations</title>
        <title type="sub">Proceedings of the Conference of the Italian Statistical Society, Florence 28-30 June 2017</title>
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          <persName n="1" ref="https://orcid.org/0000-0001-9952-0396" type="ORCID">
            <forename>Alessandra</forename>
            <surname>Petrucci</surname>
            <placeName type="affiliation">University of Florence, Italy</placeName>
          </persName>
          <persName n="2" ref="https://orcid.org/0000-0002-9959-4675" type="ORCID">
            <forename>Rosanna</forename>
            <surname>Verde</surname>
            <placeName type="affiliation">University of Campania Luigi Vanvitelli, Italy</placeName>
          </persName>
        </editor>
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        <publisher>Firenze University Press</publisher>
        <pubPlace>Florence</pubPlace>
        <date when="2017">2017</date>
        <idno type="DOI">https://doi.org/10.36253/978-88-6453-521-0</idno>
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          <p>Available for academic research purposes</p>
          <p>Open Access</p>
          <p>Copyright Author(s)</p>
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            <p>Content licence CC BY 4.0</p>
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        <idno type="ISSN" subtype="print">2704-601X</idno>
        <idno type="ISSN" subtype="electronic">2704-5846</idno>
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          <date>2017</date>
          <idno type="ISBN" subtype="electronic">978-88-6453-521-0</idno>
          <biblScope unit="page">1066 pages</biblScope>
          <extent>251,49 MB</extent>
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            <p>This is original content, published in Open Access. It is also available to read for free online at <ref target="https://media.fupress.com/files/pdf/24/3407/3407_11724">https://media.fupress.com/files/pdf/24/3407/3407_11724</ref></p>
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          <date>2017</date>
          <idno type="ISBN" subtype="electronic">978-88-9273-185-1</idno>
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        <tag>peer-reviewed</tag>
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      <abstract xml:lang="en">
        <p>The 2017 SIS Conference aims to highlight the crucial role of the Statistics in Data Science. In this new domain of ‘meaning’ extracted from the data, the increasing amount of produced and available data in databases, nowadays, has brought new challenges. That involves different fields of statistics, machine learning, information and computer science, optimization, pattern recognition. These afford together a considerable contribute in the analysis of ‘Big data’, open data, relational and complex data, structured and no-structured.
The interest is to collect the contributes which provide from the different domains of Statistics, in the high dimensional data quality validation, sampling extraction, dimensional reduction, pattern selection, data modelling, testing hypotheses and confirming conclusions drawn from the data.
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      <p>It is available online at https://doi.org/10.36253/978-88-6453-521-0<ref target="https://doi.org/10.36253/978-88-6453-521-0" /></p>
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