[英]Unable to tweak the findAssocs() in tm package in R
I was trying to find associations between top 10 frequent words with the rest of the frequent words int the input text. 我试图在输入文本中查找前10个常用词与其余常用词之间的关联。
When I look at the individual output of findAssocs()
: 当我查看
findAssocs()
的单个输出时:
findAssocs(dtm, "good", corlimit=0.4)
It gives the output clearly by printing the word 'good' with which associations have been sought. 通过打印已寻求关联的“好”一词,可以清楚地给出输出。
$good
better got hook next content fit person
0.44 0.44 0.44 0.44 0.43 0.43 0.43
But when I try to automate this process for a character vector having top 10 words: 但是,当我尝试对具有前10个字的字符向量进行自动化处理时:
t10 <- c("busi", "entertain", "topic", "interact", "track", "content", "paper", "media", "game", "good")
the output is a list of correlations for each of those elements BUT WITHOUT THE WORD WITH WHICH THE ASSOCIATIONS HAVE BEEN SOUGHT. 输出是这些元素中每一个元素的相关性列表,但是没有单词,并且已经关联了。 The sample output is as below (plz notice that the word at t10[i] is not printed, unlike the above individual output where 'good' was clearly printed):
示例输出如下(请注意,t10 [i]处的单词未打印,不像上面的单独输出中清楚地打印了“ good”一样):
for(i in 1:10) {
t10_words[i] <- as.list(findAssocs(dtm, t10[i], corlimit=0.4))
}
> t10_words
[[1]]
littl descript disrupt enter model
0.50 0.48 0.48 0.48 0.48
[[2]]
immers anyth effect full holodeck iot problem say startrek such suspect wow
0.68 0.48 0.48 0.48 0.48 0.48 0.48 0.48 0.48 0.48 0.48 0.48
[[3]]
area captur give overal like alon avid begin
0.51 0.47 0.47 0.47 0.44 0.43 0.43 0.43
circuit cloud collaboration communic communiti concis confus defin
0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43
discord doesnt drop enablesupport esport event everi everyon
0.43 0.43 0.43 0.43 0.43 0.43 0.43 0.43
How do I print the output along with the actual association word? 如何打印输出以及实际的关联词?
Can somebody please help me with this?? 有人可以帮我吗?
Thanks. 谢谢。
After running your for loop, add the following piece of code: 运行for循环后,添加以下代码:
names(t10_words) <- t10
This will name the lists with the words specified in t10. 这将使用t10中指定的单词命名列表。
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