Kiwi: Kiwi Class

In elbird: Blazing Fast Morphological Analyzer Based on Kiwi(Korean Intelligent Word Identifier)

Kiwi Class

Description

Kiwi class is provide method for korean mophological analyze result.

Methods

Public methods

• Kiwi$print()

• Kiwi$new()

• Kiwi$add_user_word()

• Kiwi$add_pre_analyzed_words()

• Kiwi$add_rules()

• Kiwi$load_user_dictionarys()

• Kiwi$extract_words()

• Kiwi$analyze()

• Kiwi$tokenize()

• Kiwi$split_into_sents()

• Kiwi$get_tidytext_func()

• Kiwi$clone()

---

Method print()

print method for Kiwi objects

Usage

Kiwi$print(x, ...)

Arguments

x

self

...

ignored

---

Method new()

Create a kiwi instance.

Usage

Kiwi$new(
  num_workers = 0,
  model_size = "base",
  integrate_allomorph = TRUE,
  load_default_dict = TRUE
)

Arguments

num_workers

int(optional): use multi-thread core number. default is 0 which means use all core.

model_size

char(optional): kiwi model select. default is "base". "small", "large" is available.

integrate_allomorph

bool(optional): default is TRUE.

load_default_dict

bool(optional): use defualt dictionary. default is TRUE.

---

Method add_user_word()

add user word with pos and score

Usage

Kiwi$add_user_word(word, tag, score, orig_word = "")

Arguments

word

char(required): target word to add.

tag

Tags(required): tag information about word.

score

num(required): score information about word.

orig_word

char(optional): origin word.

---

Method add_pre_analyzed_words()

TODO

Usage

Kiwi$add_pre_analyzed_words(form, analyzed, score)

Arguments

form

char(required): target word to add analyzed result.

analyzed

data.frame(required): analyzed result expected.

score

num(required): score information about pre analyzed result.

---

Method add_rules()

TODO

Usage

Kiwi$add_rules(tag, pattern, replacement, score)

Arguments

tag

Tags(required): target tag to add rules.

pattern

char(required): regular expression.

replacement

char(required): replace text.

score

num(required): score information about rules.

---

Method load_user_dictionarys()

add user dictionary using text file.

Usage

Kiwi$load_user_dictionarys(user_dict_path)

Arguments

user_dict_path

char(required): path of user dictionary file.

---

Method extract_words()

Extract Noun word candidate from texts.

Usage

Kiwi$extract_words(
  input,
  min_cnt,
  max_word_len,
  min_score,
  pos_threshold,
  apply = FALSE
)

Arguments

input

char(required): target text data

min_cnt

int(required): minimum count of word in text.

max_word_len

int(required): max word length.

min_score

num(required): minimum score.

pos_threshold

num(required): pos threashold.

apply

bool(optional): apply extracted word as user word dict.

---

Method analyze()

Analyze text to token and tag results.

Usage

Kiwi$analyze(text, top_n = 3, match_option = Match$ALL, stopwords = FALSE)

Arguments

text

char(required): target text.

top_n

int(optional): number of result. Default is 3.

match_option

match_option Match: use Match. Default is Match$ALL

stopwords

stopwords option. Default is FALSE which is use nothing. If TRUE, use embaded stopwords dictionany. If char: path of dictionary txt file, use file. If Stopwords class, use it. If not valid value, work same as FALSE.

Returns

list of result.

---

Method tokenize()

Analyze text to token and pos result just top 1.

Usage

Kiwi$tokenize(
  text,
  match_option = Match$ALL,
  stopwords = FALSE,
  form = "tibble"
)

Arguments

text

char(required): target text.

match_option

match_option Match: use Match. Default is Match$ALL

stopwords

stopwords option. Default is FALSE which is use nothing. If TRUE, use embaded stopwords dictionany. If char: path of dictionary txt file, use file. If Stopwords class, use it. If not valid value, work same as FALSE.

form

char(optional): return form. default is "tibble". "list", "tidytext" is available.

---

Method split_into_sents()

Some text may not split sentence by sentence. split_into_sents works split sentences to sentence by sentence.

Usage

Kiwi$split_into_sents(text, match_option = Match$ALL, return_tokens = FALSE)

Arguments

text

char(required): target text.

match_option

match_option Match: use Match. Default is Match$ALL

return_tokens

bool(optional): add tokenized resault.

---

Method get_tidytext_func()

set function to tidytext unnest_tokens.

Usage

Kiwi$get_tidytext_func(match_option = Match$ALL, stopwords = FALSE)

Arguments

match_option

match_option Match: use Match. Default is Match$ALL

stopwords

stopwords option. Default is TRUE which is to use embaded stopwords dictionary. If FALSE, use not embaded stopwords dictionary. If char: path of dictionary txt file, use file. If Stopwords class, use it. If not valid value, work same as FALSE.

Returns

function

Examples

\dontrun{
   kw <- Kiwi$new()
   tidytoken <- kw$get_tidytext_func()
   tidytoken("test")
}

---

Method clone()

The objects of this class are cloneable with this method.

Usage

Kiwi$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Examples

## Not run: 
  kw <- Kiwi$new()
  kw$analyze("test")
  kw$tokenize("test")
  
## End(Not run)

## ------------------------------------------------
## Method `Kiwi$get_tidytext_func`
## ------------------------------------------------

## Not run: 
   kw <- Kiwi$new()
   tidytoken <- kw$get_tidytext_func()
   tidytoken("test")

## End(Not run)

elbird documentation built on Aug. 12, 2022, 5:08 p.m.