IdentifyTermsInStudies: IdentifyTermsInStudies

In shihikoo/AutoAnnotation: Auto annotator with custom dictionary

Description

Identify terms in studies

Usage

IdentifyTermsInStudies(
  searchingData = NULL,
  dictionary = NULL,
  textSearchingHeaders = "",
  linkSearchHeaders = "",
  dictionaryNameHeader = "Name",
  dictionaryRegexHeader = "Regex",
  ignoreCase = TRUE,
  ignoreExistingTextFile = TRUE,
  cutIntro = FALSE,
  cutRefs = FALSE,
  extractStrings = FALSE,
  conversionSoftware = "pdftotext"
)

Arguments

searchingData	Either a dataset or a link to the dataset to search from
dictionary	Either a dictionary dataset, or a link to the dictionary dataset to run the function on. It should consist two columns: name of the term and search string of the term. Regular expression (Perl) is accepted for the search string. If there is only one column, that column will be used both as name and regular expression.
textSearchingHeaders	A list of the headers of the columns to search from. A list of character. Default value is empty string
linkSearchHeaders	A list of the headers of the columns to read and search from. A list of character. Default value is empty string
dictionaryNameHeader	The header string of name column in dictionary
dictionaryRegexHeader	The header string of regular expression column in dictionary
ignoreCase	boolean to decide whether to ignore the case in searching the content in dictionary in the searchingData or not
ignoreExistingTextFile	ignoreExistingTextFile
cutIntro	boolean varible to indicate whether introduction/background should be removed from pdfs
cutRefs	boolean varible to indicate whether reference section should be removed from pdfs
extractStrings	= boolean variable to indicate whether matching strings from full text should be extracted
conversionSoftware	Software used to covert pdf to text. Default value is 'pdftotext'

Value

A data frame with result of the dictionary search. One column for each term in the dictionary, with the name of the term as header.

shihikoo/AutoAnnotation documentation built on April 3, 2021, 10:58 a.m.