{
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  "Package": "lsa",
  "Title": "Latent Semantic Analysis",
  "Version": "0.73.4",
  "Authors@R": "person(given = \"Fridolin\",\nfamily = \"Wild\",\nrole = c(\"aut\", \"cre\"),\nemail = \"wild@brookes.ac.uk\")",
  "Description": "The basic idea of latent semantic analysis (LSA) is, that\ntext do have a higher order (=latent semantic) structure which,\nhowever, is obscured by word usage (e.g. through the use of\nsynonyms or polysemy). By using conceptual indices that are\nderived statistically via a truncated singular value\ndecomposition (a two-mode factor analysis) over a given\ndocument-term matrix, this variability problem can be overcome.",
  "License": "GPL (>= 2)",
  "Encoding": "UTF-8",
  "LazyData": "yes",
  "BuildResaveData": "no",
  "NeedsCompilation": "no",
  "Packaged": {
    "Date": "2026-05-15 10:16:50 UTC",
    "User": "root"
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  "Author": "Fridolin Wild [aut, cre]",
  "Maintainer": "Fridolin Wild <wild@brookes.ac.uk>",
  "Repository": "https://fwild.r-universe.dev",
  "Date/Publication": "2026-01-11 12:36:12 UTC",
  "RemoteUrl": "https://github.com/cran/lsa",
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  "MD5sum": "4d632700a8d6548daa37cb4919ed4ef9",
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  "_published": "2026-06-02T19:15:13.116Z",
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    "name": "Fridolin Wild",
    "description": "R veteran (and maintainer of NLP task view), C# Unity AR, but otherwise very multilingual (PHP, Perl, JavaScript, C, XoTcl, etc.). Loves a good interface."
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    "extra/citation.html",
    "extra/citation.json",
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    "manual.pdf"
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      "date": "2022-05-09"
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    "associate",
    "cosine",
    "delTriple",
    "dimcalc_kaiser",
    "dimcalc_ndocs",
    "dimcalc_raw",
    "dimcalc_share",
    "entropy",
    "fold_in",
    "getTriple",
    "gw_entropy",
    "gw_gfidf",
    "gw_idf",
    "gw_normalisation",
    "lsa",
    "lw_bintf",
    "lw_logtf",
    "lw_tf",
    "print.textmatrix",
    "query",
    "sample.textmatrix",
    "setTriple",
    "summary.textmatrix",
    "textmatrix",
    "textvector"
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      "object": "alnumx",
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      ],
      "fields": [],
      "table": false,
      "tojson": true
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        "data6_02.txt",
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      ],
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      "table": false,
      "tojson": false
    },
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      "class": [
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      ],
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      ],
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      "table": true,
      "tojson": true
    },
    {
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      "title": "Corpora (Essay Scoring)",
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        "data6_base_04.txt",
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      "table": false,
      "tojson": false
    },
    {
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      "object": "specialchars",
      "class": [
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      ],
      "fields": [],
      "table": true,
      "tojson": true
    },
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      "title": "Stopwordlists in German, English, Dutch, French, Polish, and Arab",
      "object": "stopwords_ar",
      "class": [
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      "fields": [],
      "table": false,
      "tojson": true
    },
    {
      "name": "stopwords_de",
      "title": "Stopwordlists in German, English, Dutch, French, Polish, and Arab",
      "object": "stopwords_de",
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      "fields": [],
      "table": false,
      "tojson": true
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      "object": "stopwords_en",
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      "fields": [],
      "table": false,
      "tojson": true
    },
    {
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      "table": false,
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      "tojson": true
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        "alnumx"
      ]
    },
    {
      "page": "as.textmatrix",
      "title": "Display a latent semantic space generated by Latent Semantic Analysis (LSA)",
      "topics": [
        "as.textmatrix"
      ]
    },
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      "title": "Find close terms in a textmatrix",
      "topics": [
        "associate"
      ]
    },
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      "title": "Corpora (Essay Scoring)",
      "topics": [
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        "corpus_scores",
        "corpus_training"
      ]
    },
    {
      "page": "cosine",
      "title": "Cosine Measure (Matrices)",
      "topics": [
        "cosine"
      ]
    },
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      "page": "dimcalc",
      "title": "Dimensionality Calculation Routines (LSA)",
      "topics": [
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        "dimcalc_fraction",
        "dimcalc_kaiser",
        "dimcalc_ndocs",
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        "dimcalc_share"
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    },
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      "topics": [
        "lsa"
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    },
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    },
    {
      "page": "sample.textmatrix",
      "title": "Create a random sample of files",
      "topics": [
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    },
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      "topics": [
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        "stopwords_de",
        "stopwords_en",
        "stopwords_fr",
        "stopwords_nl",
        "stopwords_pl"
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        "textvector"
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