TextReuseTextDocument: TextReuseTextDocument

In ropensci/textreuse: Detect Text Reuse and Document Similarity

TextReuseTextDocument

Description

This is the constructor function for TextReuseTextDocument objects. This class is used for comparing documents.

Usage

TextReuseTextDocument(
  text,
  file = NULL,
  meta = list(),
  tokenizer = tokenize_ngrams,
  ...,
  hash_func = hash_string,
  minhash_func = NULL,
  keep_tokens = FALSE,
  keep_text = TRUE,
  skip_short = TRUE
)

is.TextReuseTextDocument(x)

has_content(x)

has_tokens(x)

has_hashes(x)

has_minhashes(x)

Arguments

text	A character vector containing the text of the document. This argument can be skipped if supplying file.
file	The path to a text file, if text is not provided.
meta	A list with named elements for the metadata associated with this document. If a document is created using the text parameter, then you must provide an id field, e.g., meta = list(id = "my_id"). If the document is created using file, then the ID will be created from the file name.
tokenizer	A function to split the text into tokens. See tokenizers. If value is NULL, then tokenizing and hashing will be skipped.
...	Arguments passed on to the tokenizer.
hash_func	A function to hash the tokens. See hash_string.
minhash_func	A function to create minhash signatures of the document. See minhash_generator.
keep_tokens	Should the tokens be saved in the document that is returned or discarded?
keep_text	Should the text be saved in the document that is returned or discarded?
skip_short	Should short documents be skipped? (See details.)
x	An R object to check.

Details

This constructor function follows a three-step process. It reads in the text, either from a file or from memory. It then tokenizes that text. Then it hashes the tokens. Most of the comparison functions in this package rely only on the hashes to make the comparison. By passing FALSE to keep_tokens and keep_text, you can avoid saving those objects, which can result in significant memory savings for large corpora.

If skip_short = TRUE, this function will return NULL for very short or empty documents. A very short document is one where there are two few words to create at least two n-grams. For example, if five-grams are desired, then a document must be at least six words long. If no value of n is provided, then the function assumes a value of n = 3. A warning will be printed with the document ID of a skipped document.

Value

An object of class TextReuseTextDocument. This object inherits from the virtual S3 class TextDocument in the NLP package. It contains the following elements:

content

The text of the document.

tokens

The tokens created from the text.

hashes

Hashes created from the tokens.

minhashes

The minhash signature of the document.

metadata

The document metadata, including the filename (if any) in file.

See Also

Accessors for TextReuse objects.

Examples

file <- system.file("extdata/legal/ny1850-match.txt", package = "textreuse")
doc  <- TextReuseTextDocument(file = file, meta = list(id = "ny1850"))
print(doc)
meta(doc)
head(tokens(doc))
head(hashes(doc))
## Not run: 
content(doc)

## End(Not run)

ropensci/textreuse documentation built on Aug. 8, 2024, 9:17 a.m.