Text.WordCloud.Backend behaviour (Text v0.5.0)

Behaviour for Text.WordCloud scoring backends.

Each backend takes a pre-tokenized stream of words (or, in the case of phrase-aware scorers, the raw text plus options carrying the resolved language and stopwords) and returns a list of scored candidate terms. The orchestrator in Text.WordCloud then normalises the raw scores to [0.0, 1.0], sorts, and trims to :max_terms.

All backends return scores in higher-is-better form. YAKE!, whose published score is "lower = more relevant", inverts internally before returning so the orchestrator's normalisation does not need a per-backend direction flag.

Callback contract

@callback score(input, options) :: [scored_term()]

input — the original text or [text] argument passed to Text.WordCloud.terms/2. Backends that work in pre-tokenized space can call the internal tokenisation helpers under lib/word_cloud/tokens.ex to share the orchestrator's tokenization pipeline.
options — the resolved keyword list. The orchestrator has already filled in :language, :stopwords, :case_fold, and :ngram_range, so backends do not need to re-derive them.

Each returned tuple is {term, raw_score, count, kind} with:

term — the surface form to display.
raw_score — a non-negative number, higher = more important.
count — how many times the term occurs in the input.
kind — :word or :phrase (n > 1).

Summary

Types

scored_term()

Callbacks

score(input, options)

Types

scored_term()

@type scored_term() ::
  {term :: String.t(), raw_score :: number(), count :: pos_integer(),
   kind :: :word | :phrase}

Callbacks

score(input, options)

@callback score(input :: String.t() | [String.t()], options :: keyword()) :: [
  scored_term()
]