Essec\Faculty\Model\Contribution {#2216 ▼
#_index: "academ_contributions"
#_id: "13860"
#_source: array:26 [
"id" => "13860"
"slug" => "13860-uncertainty-detection-in-historical-databases"
"yearMonth" => "2022-06"
"year" => "2022"
"title" => "Uncertainty Detection in Historical Databases"
"description" => "KOUADRI, W.M., AKOKA, J., WATTIAU, I. et DU MOUZA, C. (2022). Uncertainty Detection in Historical Databases. Dans: Paolo Rosso, Valerio Basile, Raquel Martínez, Elisabeth Métais, Farid Meziane eds. <i>Natural Language Processing and Information Systems</i>. 1 ed. Springer International Publishing, pp. 73-85. 
KOUADRI, W.M., AKOKA, J., WATTIAU, I. et DU MOUZA, C. (2022). Uncertainty Detection in Historical Da "
"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" => "KOUADRI Wissam Mammar"
]
3 => array:1 [
"name" => "DU MOUZA Cedric"
]
]
"ouvrage" => "Natural Language Processing and Information Systems"
"keywords" => array:4 [
0 => "Uncertainty"
1 => "Automatic detection"
2 => "Historical data"
3 => "Dictionary Pattern"
]
"updatedAt" => "2023-03-15 16:31:03"
"publicationUrl" => "https://link.springer.com/chapter/10.1007/978-3-031-08473-7_7"
"publicationInfo" => array:3 [
"pages" => "73-85"
"volume" => ""
"number" => ""
]
"type" => array:2 [
"fr" => "Chapitres"
"en" => "Book chapters"
]
"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. Historians analyze information from diverse and heterogeneous sources to verify hypotheses and/or to "
"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. Historians analyze information from diverse and heterogeneous sources to verify hypotheses and/or to "
]
"authors_fields" => array:2 [
"fr" => "Systèmes d'Information, Data Analytics et Opérations"
"en" => "Information Systems, Data Analytics and Operations"
]
"indexedAt" => "2025-03-30T08:21:41.000Z"
"docTitle" => "Uncertainty Detection in Historical Databases"
"docSurtitle" => "Book chapters"
"authorNames" => "AKOKA Jacky, <a href="/cv/wattiau-isabelle">WATTIAU Isabelle</a>, KOUADRI Wissam Mammar, DU MOUZA Cedric AKOKA Jacky, <a href="/cv/wattiau-isabelle">WATTIAU Isabelle</a>, KOUADRI Wissam Mammar, DU MOUZA Ce "
"docDescription" => "<span class="document-property-authors">AKOKA Jacky, WATTIAU Isabelle, KOUADRI Wissam Mammar, DU MOUZA Cedric</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2022</span> <span class="document-property-authors">AKOKA Jacky, WATTIAU Isabelle, KOUADRI Wissam Mammar, DU MOU "
"keywordList" => "<a href="#">Uncertainty</a>, <a href="#">Automatic detection</a>, <a href="#">Historical data</a>, <a href="#">Dictionary Pattern</a> <a href="#">Uncertainty</a>, <a href="#">Automatic detection</a>, <a href="#">Historical data</a>, < "
"docPreview" => "<b>Uncertainty Detection in Historical Databases</b><br><span>2022-06 | Book chapters </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> <a href="https://link.springer.com/chapter/10.1007/978-3-031-08473-7_7" target="_blank">Uncertainty "
]
+lang: "en"
+"_type": "_doc"
+"_score": 9.026337
+"parent": null
}
