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    <Journal>
      <PublisherName>ijesm</PublisherName>
      <JournalTitle>International Journal of Engineering, Science and</JournalTitle>
      <PISSN>I</PISSN>
      <EISSN>S</EISSN>
      <Volume-Issue>Volume 6, Issue 5</Volume-Issue>
      <PartNumber/>
      <IssueTopic>Multidisciplinary</IssueTopic>
      <IssueLanguage>English</IssueLanguage>
      <Season>September 2017</Season>
      <SpecialIssue>N</SpecialIssue>
      <SupplementaryIssue>N</SupplementaryIssue>
      <IssueOA>Y</IssueOA>
      <PubDate>
        <Year>-0001</Year>
        <Month>11</Month>
        <Day>30</Day>
      </PubDate>
      <ArticleType>Engineering, Science and Mathematics</ArticleType>
      <ArticleTitle>QUANTITATIVE DATA MINING: STATIESTICS TECHNIQUES __ampersandsign OPERATIONS RESEARCH APPROACHES</ArticleTitle>
      <SubTitle/>
      <ArticleLanguage>English</ArticleLanguage>
      <ArticleOA>Y</ArticleOA>
      <FirstPage>150</FirstPage>
      <LastPage>157</LastPage>
      <AuthorList>
        <Author>
          <FirstName>Bhanudas Suresh</FirstName>
          <LastName>Panchabhai</LastName>
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>N</CorrespondingAuthor>
          <ORCID/>
          <FirstName>R.C.Patel ACS</FirstName>
          <LastName>College</LastName>
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>Y</CorrespondingAuthor>
          <ORCID/>
          <FirstName>Shirpur</FirstName>
          <AuthorLanguage>English</AuthorLanguage>
          <Affiliation/>
          <CorrespondingAuthor>Y</CorrespondingAuthor>
          <ORCID/>
        </Author>
      </AuthorList>
      <DOI/>
      <Abstract>This research paper reviews the main applications of statistics and operations research techniques to the quantitative and aspects of Knowledge Discovery (KD) and Data Mining (DM), fulfilling a demanding need. Data Mining, one of the most important phases of the Knowledge Discovery in Databases activity, is becoming ubiquitous with the current information explosion. As a result, there is an increasing need for training professionals to work as analysts or to interface with these. On the other hand, such professionals already exist. Statisticians and operations researchers combine three skills widely used in Data Mining: computer applications, systems optimization and data analysis techniques. This review alerts them about the challenging opportunities that, with little extra training, await them in Data Mining.</Abstract>
      <AbstractLanguage>English</AbstractLanguage>
      <Keywords>Data Mining, data, data quality, applied statistics, data analysis</Keywords>
      <URLs>
        <Abstract>https://ijesm.co.in/ubijournal-v1copy/journals/abstract.php?article_id=3438&amp;title=QUANTITATIVE DATA MINING: STATIESTICS TECHNIQUES __ampersandsign OPERATIONS RESEARCH APPROACHES</Abstract>
      </URLs>
      <References>
        <ReferencesarticleTitle>References</ReferencesarticleTitle>
        <ReferencesfirstPage>16</ReferencesfirstPage>
        <ReferenceslastPage>19</ReferenceslastPage>
        <References/>
      </References>
    </Journal>
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