这是一个对于一种我已经能够低效地完成的操作提出改进的呼吁：使用“停用词”过滤一系列n-gram标记，使得任何停用词出现在n-gram中都会触发移除。
我非常希望有一个解决方案可以同时适用于unigrams和n-grams，虽然有一个“固定”的标志和一个“正则表达式”的标志也可以。我把问题的两个方面放在一起，因为有人可能会尝试不同的方法来解决包括固定和正则表达式停用词模式的问题。
格式：
tokens 是一个字符向量列表，可能是unigrams，也可能是由
_（下划线）字符连接的n-grams。stopwords 是一个字符向量。现在，我满足于让它成为一个固定的字符串，但使用以正则表达式格式化的停用词也将是一个不错的奖励。
期望输出：与输入tokens 匹配但其中任何组成部分匹配到停用词的都要被删除。(这意味着一个unigram匹配，或者匹配到n-gram中的一个术语。)
示例，测试数据，以及可供建立的工作代码和基准：
tokens1 <- list(text1 = c("this", "is", "a", "test", "text", "with", "a", "few", "words"),
text2 = c("some", "more", "words", "in", "this", "test", "text"))
tokens2 <- list(text1 = c("this_is", "is_a", "a_test", "test_text", "text_with", "with_a", "a_few", "few_words"),
text2 = c("some_more", "more_words", "words_in", "in_this", "this_text", "text_text"))
tokens3 <- list(text1 = c("this_is_a", "is_a_test", "a_test_text", "test_text_with", "text_with_a", "with_a_few", "a_few_words"),
text2 = c("some_more_words", "more_words_in", "words_in_this", "in_this_text", "this_text_text"))
stopwords <- c("is", "a", "in", "this")
# remove any single token that matches a stopword
removeTokensOP1 <- function(w, stopwords) {
lapply(w, function(x) x[-which(x %in% stopwords)])
}
# remove any word pair where a single word contains a stopword
removeTokensOP2 <- function(w, stopwords) {
matchPattern <- paste0("(^|_)", paste(stopwords, collapse = "(_|$)|(^|_)"), "(_|$)")
lapply(w, function(x) x[-grep(matchPattern, x)])
}
removeTokensOP1(tokens1, stopwords)
## $text1
## [1] "test" "text" "with" "few" "words"
##
## $text2
## [1] "some" "more" "words" "test" "text"
removeTokensOP2(tokens1, stopwords)
## $text1
## [1] "test" "text" "with" "few" "words"
##
## $text2
## [1] "some" "more" "words" "test" "text"
removeTokensOP2(tokens2, stopwords)
## $text1
## [1] "test_text" "text_with" "few_words"
##
## $text2
## [1] "some_more" "more_words" "text_text"
removeTokensOP2(tokens3, stopwords)
## $text1
## [1] "test_text_with"
##
## $text2
## [1] "some_more_words"
# performance benchmarks for answers to build on
require(microbenchmark)
microbenchmark(OP1_1 = removeTokensOP1(tokens1, stopwords),
OP2_1 = removeTokensOP2(tokens1, stopwords),
OP2_2 = removeTokensOP2(tokens2, stopwords),
OP2_3 = removeTokensOP2(tokens3, stopwords),
unit = "relative")
## Unit: relative
## expr min lq mean median uq max neval
## OP1_1 1.000000 1.000000 1.000000 1.000000 1.000000 1.000000 100
## OP2_1 5.119066 3.812845 3.438076 3.714492 3.547187 2.838351 100
## OP2_2 5.230429 3.903135 3.509935 3.790143 3.631305 2.510629 100
## OP2_3 5.204924 3.884746 3.578178 3.753979 3.553729 8.240244 100
grepl的向量化版本，用 c 语言编写，适用于长向量。是的，我也希望有人能写出来 :} @Rcore - rawr