我有一个关于污染物归宿和运输主题的文本文件语料库。我做了术语文档矩阵和术语关联。但是，我想在术语之间找到我们的“趋势关联”。例如，我想知道更多的环境光是否会增加化学物质的水解。我已经在 termdomumentmatrix 中有“光”、“水解”、“增加”和“化学 X”，什么是回答我提出的上述问题的好方法？请注意，我已经在这些术语中完成了 findAssocs，它们在一定程度上正相关（均高于 0.5）。
请指教。谢谢
以下是我使用的粗略 tm 流程，请注意我还有许多其他文档，我只是摘录了一小段文字，例如：
> require(tm)
> my.docs <- c("These experiments showed that the ordinary and the polarized
+ lights had a stimulating effect on the hydrolytic process, and
+ both of about the same magnitude. When hydrolysis goes on
+ (Curves I and II in Figs. 3 and 4) in the presence of light, a larger
+ amount of the starch substrate is hydrolyzed. The differences
+ between the two curves (ordinary light and polarized light) are
+ quite insignificant; they are of the magnitude of twice the probable
+ error of the mean and so far as it is consistent it can be attributed
+ to the slight differences existing in the spectral composition of the
+ lights.
+
+ The situation regarding the effect of radiation on the starch-
+ diastase system is, in brief:
+ 1. Ordinary light and polarized light, of the same intensity and
+ as closely as possible similar in spectral composition, have the
+ same effect.
+ 2. Light falling on the starch-diastase system as described, increases
+ the rate of hydrolysis over that of the same reaction in the
+ dark.
+ ")
> funcs <- list(tolower, removePunctuation, stripWhitespace, removeNumbers)
> lightC <- Corpus(VectorSource(my.docs))
> lightCC <- tm_map(lightC, FUN=tm_reduce, tmFuns=funcs)
> my.dictionary.terms <- tolower(c("light","hydrolysis","increases","decreases","reduce","starch"))
> my.dictionary <- Dictionary(my.dictionary.terms)
> tdmLight <- TermDocumentMatrix(lightCC, control=list(weight=weightTfIdf, stopwords=stopwords("english"), dictionary=my.dictionary))
> findAssocs(tdmLight, "light", 0.5)