Classify free-text items against a user-supplied taxonomy using TF-IDF

Usage

classify_text(
  corpus,
  taxonomy,
  id_col = "id",
  text_col = "text",
  class_id_col = "class_id",
  class_label_col = "class_label",
  num_leaves = 1,
  method = c("tfidf_sum", "cosine"),
  max_dist = 0.1,
  string_dist = NULL,
  stopwords = NULL
)

Arguments

corpus

A data.frame with at minimum an id column and a text column.

taxonomy

Either:

A named character vector: names = class IDs, values = class labels/descriptions
A data.frame with columns identified by class_id_col and class_label_col

id_col

Name of the id column in corpus. Default "id".

text_col

Name of the text column in corpus. Default "text".

class_id_col

Name of the class ID column in taxonomy (if data.frame). Default "class_id".

class_label_col

Name of the class label column in taxonomy (if data.frame). Default "class_label".

num_leaves

Number of top-matching classes to return per item. Default 1.

method

"tfidf_sum" (mirrors labourR) or "cosine" (improved, length-normalised). Default "tfidf_sum".

max_dist

Maximum string distance for fuzzy token matching (used when string_dist is set).

string_dist

String distance method passed to stringdist::amatch(). NULL disables fuzzy matching.

stopwords

Character vector of stopwords to remove. NULL uses a built-in English set.

Value

A data.table with columns: <id_col>, class_id, class_label, score