{
  "annotation_id": "5bffa107-3931-45a9-98d2-4de80c5d6323",
  "date_created": "2026-03-02T18:01:18.022000Z",
  "date_modified": "2026-03-02T18:01:18.022000Z",
  "file_hash": "93b7a4682a5caf2aaccc4ad5492f3b9292eca5691f4fd86a37e6c005d7ba7201",
  "private": false,
  "record": {
    "abstract": "The difficulties involved in spelling error detection and correction in a\nlanguage have been investigated in this work through the conceptualization of\nSpellNet - the weighted network of words, where edges indicate orthographic\nproximity between two words. We construct SpellNets for three languages -\nBengali, English and Hindi. Through appropriate mathematical analysis and/or\nintuitive justification, we interpret the different topological metrics of\nSpellNet from the perspective of the issues related to spell-checking. We make\nmany interesting observations, the most significant among them being that the\nprobability of making a real word error in a language is propotionate to the\naverage weighted degree of SpellNet, which is found to be highest for Hindi,\nfollowed by Bengali and English.",
    "arxiv_id": "physics/0703198",
    "authors": [
      "Monojit Choudhury",
      "Markose Thomas",
      "Animesh Mukherjee",
      "Anupam Basu",
      "Niloy Ganguly"
    ],
    "categories": [
      "physics.soc-ph"
    ],
    "title": "How Difficult is it to Develop a Perfect Spell-checker? A   Cross-linguistic Analysis through Complex Network Approach",
    "url": "https://arxiv.org/abs/physics/0703198"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "dc215531-0e22-467a-b350-bca3ebc51fc9",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}