Essec\Faculty\Model\Contribution {#2216
  #_index: "academ_contributions"
  #_id: "13312"
  #_source: array:26 [
    "id" => "13312"
    "slug" => "uncertainty-detection-in-historical-databases"
    "yearMonth" => "2022-06"
    "year" => "2022"
    "title" => "Uncertainty Detection in Historical Databases"
    "description" => "MAMMAR KOUADRI, W., AKOKA, J., WATTIAU, I. et DU MOUZA, C. (2022). Uncertainty Detection in Historical Databases. Dans: <i>Natural Language Processing and Information Systems: 27th International Conference on Applications of Natural Language to Information Systems, NLDB 2022, Valencia, Spain, June 15–17, 2022, Proceedings</i>. Springer, pp. 73-85."
    "authors" => array:4 [
      0 => array:2 [
        "name" => "AKOKA Jacky"
        "bid" => "B00714200"
      ]
      1 => array:3 [
        "name" => "WATTIAU Isabelle"
        "bid" => "B00000530"
        "slug" => "wattiau-isabelle"
      ]
      2 => array:1 [
        "name" => "MAMMAR KOUADRI Wissam"
      ]
      3 => array:1 [
        "name" => "DU MOUZA Cédric"
      ]
    ]
    "ouvrage" => "Natural Language Processing and Information Systems: 27th International Conference on Applications of Natural Language to Information Systems, NLDB 2022, Valencia, Spain, June 15–17, 2022, Proceedings"
    "keywords" => array:5 [
      0 => "Uncertainty"
      1 => "Automatic detection"
      2 => "Historical data"
      3 => "Dictionary"
      4 => "Pattern"
    ]
    "updatedAt" => "2024-03-11 15:01:49"
    "publicationUrl" => "https://link.springer.com/chapter/10.1007/978-3-031-08473-7_7"
    "publicationInfo" => array:3 [
      "pages" => "73-85"
      "volume" => "Lecture Notes in Computer Science book series (LNCS,volume 13286)"
      "number" => ""
    ]
    "type" => array:2 [
      "fr" => "Actes d'une conférence"
      "en" => "Conference Proceedings"
    ]
    "support_type" => array:2 [
      "fr" => "Editeur"
      "en" => "Publisher"
    ]
    "countries" => array:2 [
      "fr" => null
      "en" => null
    ]
    "abstract" => array:2 [
      "fr" => "Historians analyze information from diverse and heterogeneous sources to verify hypotheses and/or to propose new ones. Central to any historical project is the concept of uncertainty, reflecting a lack of confidence. This may limit the scope of the hypotheses formulated. Uncertainty encompasses a variety of aspects including ambiguity, incompleteness, vagueness, randomness, and inconsistency. These aspects cannot be easily detected automatically in plain-text documents. The objective of this article is to propose a process for detecting uncertainty, combining dictionary-based approaches, and pattern identification. The process is validated through experiments conducted on a real historical data set."
      "en" => "Historians analyze information from diverse and heterogeneous sources to verify hypotheses and/or to propose new ones. Central to any historical project is the concept of uncertainty, reflecting a lack of confidence. This may limit the scope of the hypotheses formulated. Uncertainty encompasses a variety of aspects including ambiguity, incompleteness, vagueness, randomness, and inconsistency. These aspects cannot be easily detected automatically in plain-text documents. The objective of this article is to propose a process for detecting uncertainty, combining dictionary-based approaches, and pattern identification. The process is validated through experiments conducted on a real historical data set."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2024-12-30T17:21:46.000Z"
    "docTitle" => "Uncertainty Detection in Historical Databases"
    "docSurtitle" => "Conference Proceedings"
    "authorNames" => "AKOKA Jacky, <a href="/cv/wattiau-isabelle">WATTIAU Isabelle</a>, MAMMAR KOUADRI Wissam, DU MOUZA Cédric"
    "docDescription" => "<span class="document-property-authors">AKOKA Jacky, WATTIAU Isabelle, MAMMAR KOUADRI Wissam, DU MOUZA Cédric</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2022</span>"
    "keywordList" => "<a href="#">Uncertainty</a>, <a href="#">Automatic detection</a>, <a href="#">Historical data</a>, <a href="#">Dictionary</a>, <a href="#">Pattern</a>"
    "docPreview" => "<b>Uncertainty Detection in Historical Databases</b><br><span>2022-06 | Conference Proceedings </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://link.springer.com/chapter/10.1007/978-3-031-08473-7_7" target="_blank">Uncertainty Detection in Historical Databases</a>"
  ]
  +lang: "en"
  +"_type": "_doc"
  +"_score": 8.447113
  +"parent": null
}