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  "Title": "Summarize Text by Ranking Sentences and Finding Keywords",
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  "Author": "Jan Wijffels [aut, cre, cph], BNOSAC [cph]",
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  "Description": "The 'textrank' algorithm is an extension of the 'Pagerank'\nalgorithm for text. The algorithm allows to summarize text by\ncalculating how sentences are related to one another. This is\ndone by looking at overlapping terminology used in sentences in\norder to set up links between sentences. The resulting sentence\nnetwork is next plugged into the 'Pagerank' algorithm which\nidentifies the most important sentences in your text and ranks\nthem. In a similar way 'textrank' can also be used to extract\nkeywords. A word network is constructed by looking if words are\nfollowing one another. On top of that network the 'Pagerank'\nalgorithm is applied to extract relevant words after which\nrelevant words which are following one another are combined to\nget keywords. More information can be found in the paper from\nMihalcea, Rada & Tarau, Paul (2004)\n<https://www.aclweb.org/anthology/W04-3252/>.",
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  "Date/Publication": "2020-10-12 11:33:30 UTC",
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    "textrank_candidates_lsh",
    "textrank_jaccard",
    "textrank_keywords",
    "textrank_sentences"
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        "paragraph_id",
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        "token",
        "lemma",
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      "page": "joboffer",
      "title": "The text of a job offer, annotated with the package udpipe",
      "topics": [
        "joboffer"
      ]
    },
    {
      "page": "summary.textrank_sentences",
      "title": "Extract the most important sentences which were identified with textrank_sentences",
      "topics": [
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      ]
    },
    {
      "page": "textrank_candidates_all",
      "title": "Get all combinations of sentences",
      "topics": [
        "textrank_candidates_all"
      ]
    },
    {
      "page": "textrank_candidates_lsh",
      "title": "Use locality-sensitive hashing to get combinations of sentences which contain words which are in the same minhash bucket",
      "topics": [
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      ]
    },
    {
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      "topics": [
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      ]
    },
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      "title": "Textrank - extract relevant keywords",
      "topics": [
        "textrank_keywords"
      ]
    },
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      "title": "Textrank - extract relevant sentences",
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        "Identify relevant keywords",
        "Example text",
        "Textrank for keyword extraction",
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