Quanteda - 提取已识别的字典单词 [英] Quanteda - Extracting identified dictionary words

问题描述

我正在尝试从 Quanteda dfm 中提取已识别的字典单词，但一直无法找到解决方案.

I am trying to extract the identified dictionary words from a Quanteda dfm, but have been unable to find a solution.

有人对此有解决方案吗?

Does someone have a solution for this?

样本输入:

dict <- dictionary(list(season = c("spring", "summer", "fall", "winter")))
dfm  <- dfm("summer is great", dictionary  = dict)

输出:

 > dfm
 Document-feature matrix of: 1 document, 1 feature.
 1 x 1 sparse Matrix of class "dfmSparse"

   features
docs    season
text1      1

我现在知道在句子中确定了一个季节性字典词，但我也想知道它是哪个词.

I now know that a seasonality dict word has been identified in the sentence, but I would also like to know which word it was.

最好以表格格式提取:

docs    dict     dictWord
text1   season   summer

推荐答案

您可以使用 keptFeatures 参数创建第二个 dfm，然后 cbind() 将其添加到首先，字典dfm.

You can create a second dfm using the keptFeatures argument, and then cbind() it to the first, dictionaried dfm.

dict <- dictionary(list(season = c("spring", "summer", "fall", "winter")))
txt <- "summer is great"
season_dfm  <- dfm(txt, dictionary  = dict, verbose = FALSE)
dict_dfm <- dfm(txt, select = dict, verbose = FALSE)

cbind(season_dfm, dict_dfm)
## Document-feature matrix of: 1 document, 2 features.
## 1 x 2 sparse Matrix of class "dfmSparse"
##       season summer
## text1      1      1

如果您希望输出为表格，则为:

If you want the output as a table, it would be:

dict_df <- as.data.frame(combined_dfm)
names(dict_df)[2] <- "dictWord"
dict_df
##       season dictWord
## text1      1        1

但这只适用于每个文本只有一个字典值的情况——否则 dict_dfm 将有多个特征列.

but that only works if you have a single dictionary value per text -- otherwise the dict_dfm will have multiple feature columns.

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