我正在尝试识别和聚合给定数据集的同义词。请参阅下面的示例数据。
library(tm)
library(SnowballC)
dataset <- c("dad glad accept large admit large accept dad big large big accept big accept dad dad Happy dad accept glad papa dad Happy dad glad dad dad papa admit Happy big accept accept big accept dad Happy admit Happy Happy glad Happy dad accept accept large daddy large accept large large large big daddy accept admit dad admit daddy dad admit dad admit Happy accept accept Happy daddy accept admit")
docs <- Corpus(VectorSource(dataset))
dtm <- TermDocumentMatrix(docs)
m <- as.matrix(dtm)
sort(rowSums(m),decreasing=TRUE)
结果:
accept dad happy admit large big daddy glad papa
15 14 9 8 8 6 4 4 2
我想使用我下载并安装的 wordnet 包为上述每个词查找同义词。例如,要获得“接受”的同义词,我可以这样做:
library(wordnet)
setDict("C:/Program Files (x86)/WordNet/2.1/dict")
filter <- getTermFilter("ExactMatchFilter", "accept", TRUE)
terms <- getIndexTerms("VERB", 1, filter)
getSynonyms(terms[[1]])
结果:
[1] "accept" "admit" "assume" "bear" "consent" "go for" "have" "live with"
[9] "swallow" "take" "take on" "take over"
现在,我想合并这两个结果集,以便按以下方式对同义词进行分组。 为给定的组标记最常用的词(排名 1),稍后按这些词进行分组,类似于此:
id word word_count syn_group rank
1 accept 15 1 1
5 admit 8 1 2
2 dad 14 2 1
8 daddy 4 2 2
9 papa 2 2 3
3 happy 9 3 1
7 glad 4 3 2
4 large 8 4 1
6 big 6 4 2
然后可以这样聚合
id word word_count
1 accept 15+8
2 dad 14+4+2
3 happy 9+4
4 large 8+6
那么最后的结果就是
id word word_count
1 accept 23
2 dad 20
3 large 14
4 happy 13
我遇到了几个问题,包括让 GetIndexTerms 循环遍历单词,无论它们是名词、动词等。希望这一切都有意义吗?任何帮助将非常感激。谢谢。
最佳答案
我们可以使用 dplyr
library(dplyr)
df %>%
group_by(syn_group) %>%
mutate(sum_word_count = sum(word_count)) %>%
filter(rank == 1)
数据:
df <- read.table(text = "id word word_count syn_group rank
1 accept 15 1 1
5 admit 8 1 2
2 dad 14 2 1
8 daddy 4 2 2
9 papa 2 2 3
3 happy 9 3 1
7 glad 4 3 2
4 large 8 4 1
6 big 6 4 2", header = T)
请下次发布dput
的输出。
编辑:这里有一些代码可以帮助您开始循环处理单词和词性,并存储同义词。剩下的就是确定当前术语是否是前一个术语的同义词,在这种情况下,您已经有了同义词,并且可以分配一个唯一的同义词组。接下来,您需要存储一些结果。最后,您需要计算排名,这只是 seq_along
同义词和一个 grep
来确定排名位置。这些注释提示您可能希望在何处包含这些提示的代码。
d <- data.frame(Term = row.names(m), word_count = m[,1])
all_pos <- c("ADJECTIVE", "ADVERB", "NOUN","VERB")
syns <- vector("list", length(all_pos))
for(w in seq(nrow(d))){
# if sysns of (d$Term[w]) has been calculated skip over current w
emf <- getTermFilter("ExactMatchFilter", d$Term[w], TRUE)
for(i in seq_along(syns)){
terms <- getIndexTerms(all_pos[i], 1, emf)
if(is.null(terms)){
syns[i] <- NA
} else{
syns[[i]] <- getSynonyms(terms[[1]])
}
}
# store the results of syns for current w
}
关于r - 在 R 中识别和分组同义词,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/42401359/