有人可以帮我解决如何使用R在文本中找到最常用的两个和三个单词吗？
我的文字是......
text <- c("There is a difference between the common use of the term phrase and its technical use in linguistics. In common usage, a phrase is usually a group of words with some special idiomatic meaning or other significance, such as \"all rights reserved\", \"economical with the truth\", \"kick the bucket\", and the like. It may be a euphemism, a saying or proverb, a fixed expression, a figure of speech, etc. In grammatical analysis, particularly in theories of syntax, a phrase is any group of words, or sometimes a single word, which plays a particular role within the grammatical structure of a sentence. It does not have to have any special meaning or significance, or even exist anywhere outside of the sentence being analyzed, but it must function there as a complete grammatical unit. For example, in the sentence Yesterday I saw an orange bird with a white neck, the words an orange bird with a white neck form what is called a noun phrase, or a determiner phrase in some theories, which functions as the object of the sentence. Theorists of syntax differ in exactly what they regard as a phrase; however, it is usually required to be a constituent of a sentence, in that it must include all the dependents of the units that it contains. This means that some expressions that may be called phrases in everyday language are not phrases in the technical sense. For example, in the sentence I can't put up with Alex, the words put up with (meaning \'tolerate\') may be referred to in common language as a phrase (English expressions like this are frequently called phrasal verbs\ but technically they do not form a complete phrase, since they do not include Alex, which is the complement of the preposition with.")
该tidytext包使这种事情变得非常简单：
library(tidytext)
library(dplyr)
data_frame(text = text) %>%
unnest_tokens(word, text) %>% # split words
anti_join(stop_words) %>% # take out "a", "an", "the", etc.
count(word, sort = TRUE) # count occurrences
# Source: local data frame [73 x 2]
#
# word n
# (chr) (int)
# 1 phrase 8
# 2 sentence 6
# 3 words 4
# 4 called 3
# 5 common 3
# 6 grammatical 3
# 7 meaning 3
# 8 alex 2
# 9 bird 2
# 10 complete 2
# .. ... ...
如果问题是要求二元组和三元组的计数，tokenizers::tokenize_ngrams则很有用：
library(tokenizers)
tokenize_ngrams(text, n = 3L, n_min = 2L, simplify = TRUE) %>% # tokenize bigrams and trigrams
as_data_frame() %>% # structure
count(value, sort = TRUE) # count
# Source: local data frame [531 x 2]
#
# value n
# (fctr) (int)
# 1 of the 5
# 2 a phrase 4
# 3 the sentence 4
# 4 as a 3
# 5 in the 3
# 6 may be 3
# 7 a complete 2
# 8 a phrase is 2
# 9 a sentence 2
# 10 a white 2
# .. ... ...
你的文字是:
text <- c("There is a difference between the common use of the term phrase and its technical use in linguistics. In common usage, a phrase is usually a group of words with some special idiomatic meaning or other significance, such as \"all rights reserved\", \"economical with the truth\", \"kick the bucket\", and the like. It may be a euphemism, a saying or proverb, a fixed expression, a figure of speech, etc. In grammatical analysis, particularly in theories of syntax, a phrase is any group of words, or sometimes a single word, which plays a particular role within the grammatical structure of a sentence. It does not have to have any special meaning or significance, or even exist anywhere outside of the sentence being analyzed, but it must function there as a complete grammatical unit. For example, in the sentence Yesterday I saw an orange bird with a white neck, the words an orange bird with a white neck form what is called a noun phrase, or a determiner phrase in some theories, which functions as the object of the sentence. Theorists of syntax differ in exactly what they regard as a phrase; however, it is usually required to be a constituent of a sentence, in that it must include all the dependents of the units that it contains. This means that some expressions that may be called phrases in everyday language are not phrases in the technical sense. For example, in the sentence I can't put up with Alex, the words put up with (meaning \'tolerate\') may be referred to in common language as a phrase (English expressions like this are frequently called phrasal verbs\ but technically they do not form a complete phrase, since they do not include Alex, which is the complement of the preposition with.")
在自然语言处理中,2个词的短语被称为" bi-gram ",3个词的短语被称为" tri-gram ",依此类推.通常,给定的n字组合称为" n-gram ".
首先,我们安装ngram包(可在CRAN上使用)
# Install package "ngram"
install.packages("ngram")
然后,我们将找到最常见的双字和三字短语
library(ngram)
# To find all two-word phrases in the test "text":
ng2 <- ngram(text, n = 2)
# To find all three-word phrases in the test "text":
ng3 <- ngram(text, n = 3)
最后,我们将使用以下各种方法打印对象(ngrams):
print(ng, output="truncated")
print(ngram(x), output="full")
get.phrasetable(ng)
ngram::ngram_asweka(text, min=2, max=3)
我们也可以使用马尔可夫链来哄骗新的序列:
# if we are using ng2 (bi-gram)
lnth = 2
babble(ng = ng2, genlen = lnth)
# if we are using ng3 (tri-gram)
lnth = 3
babble(ng = ng3, genlen = lnth)
以下是针对 5 个最常见单词的简单基本 R 方法：
head(sort(table(strsplit(gsub("[[:punct:]]", "", text), " ")), decreasing = TRUE), 5)
# a the of in phrase
# 21 18 12 10 8
它返回的是一个带有频率计数的整数向量，向量的名称对应于所计数的单词。
gsub("[[:punct:]]", "", text)删除标点符号，因为你不想计算它，我猜strsplit(gsub("[[:punct:]]", "", text), " ")按空格分割字符串table()计算独特元素的频率sort(..., decreasing = TRUE)以降序对它们进行排序head(..., 5)仅选择最常见的 5 个单词