# `Text.WordCloud.Backends.TextRank`
[🔗](https://github.com/kipcole9/text/blob/v0.6.2/lib/word_cloud/backends/text_rank.ex#L1)

TextRank backend for `Text.WordCloud`.

Implements the keyword-extraction variant of TextRank (Mihalcea &
Tarau, [*Bringing Order into Texts*](https://aclanthology.org/W04-3252/),
2004). Builds an undirected, weighted graph where vertices are
non-stopword tokens and edges connect tokens that co-occur within a
sliding window. Weighted PageRank over that graph yields a relevance
score per token; phrase candidates are then composed by joining
adjacent high-scoring tokens.

### Strengths

* No reference corpus required.

* Truly multilingual — like YAKE!, TextRank's only language-specific
  dependency is the stopword list.

* Resilient to long documents — graph density grows linearly, not
  quadratically.

### Caveats

* Slower than YAKE! for short inputs (PageRank iterations dominate).

* Phrase composition is heuristic: adjacent top-scoring tokens are
  glued, which can produce odd cuts on very dense topical text.

### Options

* `:window_size` — co-occurrence window. Default `4` (Mihalcea &
  Tarau use 2–10; 4 is a common middle ground).

* `:damping` — PageRank damping factor. Default `0.85`.

* `:tolerance` — convergence threshold (max delta across vertices).
  Default `1.0e-5`.

* `:max_iterations` — safety cap. Default `100`.

Standard `Text.WordCloud` orchestrator options (`:language`,
`:stopwords`, `:case_fold`, `:ngram_range`, `:locale`) are honoured.

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*Consult [api-reference.md](api-reference.md) for complete listing*