{
  "@context": {
    "dcterms": "http://purl.org/dc/terms/",
    "dcmitype": "http://purl.org/dc/dcmitype/"
  },
  "dcterms:identifier": [
    "tag:aim-pro.eu,2026:oer/2d014ec5467d",
    "https://zenodo.org/records/20833466",
    "doi:10.5281/zenodo.20833466",
    "zenodo-record:20833466"
  ],
  "dcterms:title": [
    "Transforming Knowledge Organization, Information Retrieval and Library Services in the Digital Age"
  ],
  "dcterms:type": [
    {
      "@id": "dcmitype:Text"
    },
    "Book chapter"
  ],
  "dcterms:creator": [
    "Divyansh Mishra",
    "Rajesh Kumar Mishra",
    "Rekha Agarwal"
  ],
  "dcterms:description": [
    "This chapter provides a comprehensive examination of Artificial Intelligence (AI) and Machine Learning (ML) as transformative forces within Library and Information Science (LIS). Beginning with a historical overview of AI adoption in library contexts, the chapter progresses through core ML methodologies—including supervised and unsupervised learning, natural language processing, and deep learning architectures—before analysing their applied impact on cataloguing, classification, reference services, collection development, and digital preservation. The chapter addresses the critical ethical dimensions of algorithmic bias, data privacy, and the evolving professional identity of library and information professionals. Particular attention is given to large language models and generative AI as emergent technologies reshaping scholarly communication and information literacy. The chapter concludes with a forward-looking synthesis of strategic imperatives for LIS institutions navigating an AI-mediated information environment."
  ],
  "dcterms:subject": [
    "Artificial Intelligence",
    "Machine Learning",
    "Natural Language Processing",
    "Knowledge Organization",
    "Information Retrieval",
    "Algorithmic Bias",
    "Digital Libraries",
    "Generative AI",
    "LIS Profession"
  ],
  "dcterms:language": [
    "en"
  ],
  "dcterms:license": [
    {
      "@id": "https://creativecommons.org/licenses/by/4.0/"
    }
  ],
  "dcterms:rights": [
    "CC-BY-4.0 — assessed as OPEN by the harvester's licence gate. Conditions: attribution required. open, permissive"
  ],
  "dcterms:accessRights": [
    "open"
  ],
  "dcterms:format": [
    "application/pdf",
    "text/markdown"
  ],
  "dcterms:extent": [
    "421389 bytes (original)",
    "45477 bytes (extracted text)"
  ],
  "dcterms:issued": [
    "2026-04-30"
  ],
  "dcterms:modified": [
    "2026-06-24"
  ],
  "dcterms:created": [
    "2026-06-24"
  ],
  "dcterms:isVersionOf": [
    {
      "@id": "https://doi.org/10.5281/zenodo.20833465"
    }
  ],
  "dcterms:provenance": [
    "Retrieved from Zenodo on 2026-10-09 in response to the search string “(\"artificial intelligence\" OR \"machine learning\" OR \"generative AI\" OR \"deep learning\" OR \"reinforcement learning\" OR \"large language model\" OR \"AI\") AND (\"AI concepts\" OR \"types of AI\" OR \"AI fundamentals\" OR \"recognizing AI\" OR \"recognising AI\" OR \"general versus narrow AI\" OR \"narrow AI\" OR \"general AI\" OR \"machine intelligence\" OR \"AI strengths and weaknesses\" OR \"traditional software\" OR \"rule-based systems\" OR \"introduction to AI\" OR \"introduction to artificial intelligence\" OR \"artificial intelligence introduction\" OR \"AI primer\" OR \"foundations of artificial intelligence\" OR \"overview of AI\" OR \"understanding AI\" OR \"history of AI\" OR \"AI essentials\" OR \"AI terminology\" OR \"metaphors for AI\" OR \"AI fundamental concepts\" OR \"AI key concepts\" OR \"philosophy of AI\" OR \"critical AI literacy\")”. Zenodo served the resource and is not asserted to be its publisher or author.",
    "Text extracted from pdf to Markdown by pdf-inspector; the original is retained unchanged beside it."
  ],
  "inferred": {
    "dcterms:references": [
      {
        "value": {
          "@id": "https://arxiv.org/abs/1301.3781",
          "title": "arXiv:1301.3781"
        },
        "method": "inferred",
        "rule": "citation",
        "rule_version": "links/1",
        "evidence": {
          "links": [
            {
              "how": "citation",
              "line": 180,
              "basis": "reference",
              "literal": "arXiv:1301.3781"
            }
          ],
          "kind": "citation"
        }
      },
      {
        "value": {
          "@id": "https://arxiv.org/abs/2303.08774",
          "title": "arXiv:2303.08774"
        },
        "method": "inferred",
        "rule": "citation",
        "rule_version": "links/1",
        "evidence": {
          "links": [
            {
              "how": "citation",
              "line": 219,
              "basis": "reference",
              "literal": "arXiv:2303.08774"
            }
          ],
          "kind": "citation"
        }
      },
      {
        "value": {
          "@id": "https://arxiv.org/abs/2304.00612",
          "title": "arXiv:2304.00612"
        },
        "method": "inferred",
        "rule": "citation",
        "rule_version": "links/1",
        "evidence": {
          "links": [
            {
              "how": "citation",
              "line": 220,
              "basis": "reference",
              "literal": "arXiv:2304.00612"
            }
          ],
          "kind": "citation"
        }
      }
    ]
  }
}