Essec\Faculty\Model\Contribution {#2220
  #_index: "academ_contributions"
  #_id: "16547"
  #_source: array:26 [
    "id" => 16547
    "slug" => "16547-automated-extraction-of-conceptual-representations-from-research-articles-using-large-language-models"
    "yearMonth" => "2026-06"
    "year" => 2026
    "title" => "Automated Extraction of Conceptual Representations from Research Articles Using Large Language Models"
    "description" => "AKOKA, J., WATTIAU, I. et DU MOUZA, C. (2026). Automated Extraction of Conceptual Representations from Research Articles Using Large Language Models. Dans: Francesca Zerbato, Jelena Zdravkovic, Luise Pufahl, Geert Poels, Marite Kirikova eds. <i>Intelligent Information Systems</i>. 1 ed. Cham: Springer Nature Switzerland, pp. 11-19."
    "authors" => array:3 [
      0 => array:3 [
        "name" => "WATTIAU Isabelle"
        "bid" => "B00000530"
        "slug" => "wattiau-isabelle"
      ]
      1 => array:1 [
        "name" => "Akoka Jacky"
      ]
      2 => array:1 [
        "name" => "du Mouza Cédric"
      ]
    ]
    "ouvrage" => "Intelligent Information Systems"
    "keywords" => array:5 [
      0 => "Path of knowledge type"
      1 => "large language model (LLM)"
      2 => "AI-assisted academic research"
      3 => "design science research (DSR)"
      4 => "information systems (IS)"
    ]
    "updatedAt" => "2026-06-29 09:43:55"
    "publicationUrl" => "https://doi.org/10.1007/978-3-032-27997-2_2"
    "publicationInfo" => array:3 [
      "pages" => "11-19"
      "volume" => "LNBIP, volume 587"
      "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" => "Dive into a pioneering approach that leverages large language models to revolutionize how research articles are analyzed and synthesized. The chapter introduces a method to automatically generate 'paths of knowledge contributions'—structured representations that map out the artifacts and their relationships within a paper, such as concepts, frameworks, or implemented systems. By fine-tuning LLMs on annotated datasets of information systems research, the authors demonstrate how these models can extract and organize key contributions from abstracts and introductions with remarkable precision. The study evaluates four leading LLMs—ChatGPT, Grok, Claude, and Gemini—revealing distinct strategies in path generation, from Grok’s concise, core-focused outputs to ChatGPT’s detailed, multi-node structures. With a focus on reproducibility and structural rigor, this method not only simplifies literature reviews but also enables richer comparisons across research corpora. Discover how this automated approach could transform your workflow, saving time while ensuring transparency and depth in academic analysis."
      "en" => "Dive into a pioneering approach that leverages large language models to revolutionize how research articles are analyzed and synthesized. The chapter introduces a method to automatically generate 'paths of knowledge contributions'—structured representations that map out the artifacts and their relationships within a paper, such as concepts, frameworks, or implemented systems. By fine-tuning LLMs on annotated datasets of information systems research, the authors demonstrate how these models can extract and organize key contributions from abstracts and introductions with remarkable precision. The study evaluates four leading LLMs—ChatGPT, Grok, Claude, and Gemini—revealing distinct strategies in path generation, from Grok’s concise, core-focused outputs to ChatGPT’s detailed, multi-node structures. With a focus on reproducibility and structural rigor, this method not only simplifies literature reviews but also enables richer comparisons across research corpora. Discover how this automated approach could transform your workflow, saving time while ensuring transparency and depth in academic analysis."
    ]
    "authors_fields" => array:2 [
      "fr" => "Systèmes d'Information, Data Analytics et Opérations"
      "en" => "Information Systems, Data Analytics and Operations"
    ]
    "indexedAt" => "2026-07-06T14:23:27.000Z"
    "docTitle" => "Automated Extraction of Conceptual Representations from Research Articles Using Large Language Models"
    "docSurtitle" => "Book chapters"
    "authorNames" => "<a href="/cv/wattiau-isabelle">WATTIAU Isabelle</a>, Akoka Jacky, du Mouza Cédric"
    "docDescription" => "<span class="document-property-authors">WATTIAU Isabelle, Akoka Jacky, du Mouza Cédric</span><br><span class="document-property-authors_fields">Information Systems, Data Analytics and Operations</span> | <span class="document-property-year">2026</span>"
    "keywordList" => "<a href="#">Path of knowledge type</a>, <a href="#">large language model (LLM)</a>, <a href="#">AI-assisted academic research</a>, <a href="#">design science research (DSR)</a>, <a href="#">information systems (IS)</a>"
    "docPreview" => "<b>Automated Extraction of Conceptual Representations from Research Articles Using Large Language Models</b><br><span>2026-06 | Book chapters </span>"
    "docType" => "research"
    "publicationLink" => "<a href="https://doi.org/10.1007/978-3-032-27997-2_2" target="_blank">Automated Extraction of Conceptual Representations from Research Articles Using Large Language Models</a>"
  ]
  +lang: "en"
  +"_score": 9.018857
  +"_ignored": array:3 [
    0 => "abstract.en.keyword"
    1 => "abstract.fr.keyword"
    2 => "description.keyword"
  ]
  +"parent": null
}