I have been breaking my head over this one over the last few days. I searched all the SO archives and tried the suggested solutions but just can't seem to get this to work. I have sets of txt documents in folders such as 2000 06, 1995 -99 etc, and want to run some basic text mining operations such as creating document term matrix and term document matrix and doing some operations based co-locations of words. My script works on a smaller corpus, however, when I try it with the bigger corpus, it fails me. I have pasted in the code for one such folder operation.
library(tm) # Framework for text mining.
library(SnowballC) # Provides wordStem() for stemming.
library(RColorBrewer) # Generate palette of colours for plots.
library(ggplot2) # Plot word frequencies.
library(magrittr)
library(Rgraphviz)
library(directlabels)
setwd("/ConvertedText")
txt <- file.path("2000 -06")
docs<-VCorpus(DirSource(txt, encoding = "UTF-8"),readerControl = list(language = "UTF-8"))
docs <- tm_map(docs, content_transformer(tolower), mc.cores=1)
docs <- tm_map(docs, removeNumbers, mc.cores=1)
docs <- tm_map(docs, removePunctuation, mc.cores=1)
docs <- tm_map(docs, stripWhitespace, mc.cores=1)
docs <- tm_map(docs, removeWords, stopwords("SMART"), mc.cores=1)
docs <- tm_map(docs, removeWords, stopwords("en"), mc.cores=1)
#corpus creation complete
setwd("/ConvertedText/output")
dtm<-DocumentTermMatrix(docs)
tdm<-TermDocumentMatrix(docs)
m<-as.matrix(dtm)
write.csv(m, file="dtm.csv")
dtms<-removeSparseTerms(dtm, 0.2)
m1<-as.matrix(dtms)
write.csv(m1, file="dtms.csv")
# matrix creation/storage complete
freq <- sort(colSums(as.matrix(dtm)), decreasing=TRUE)
wf <- data.frame(word=names(freq), freq=freq)
freq[1:50]
#adjust freq score in next line
p <- ggplot(subset(wf, freq>100), aes(word, freq))+ geom_bar(stat="identity")+ theme(axis.text.x=element_text(angle=45, hjust=1))
ggsave("frequency2000-06.png", height=12,width=17, dpi=72)
# frequency graph generated
x<-as.matrix(findFreqTerms(dtm, lowfreq=1000))
write.csv(x, file="freqterms00-06.csv")
png("correlation2000-06.png", width=12, height=12, units="in", res=900)
graph.par(list(edges=list(col="lightblue", lty="solid", lwd=0.3)))
graph.par(list(nodes=list(col="darkgreen", lty="dotted", lwd=2, fontsize=50)))
plot(dtm, terms=findFreqTerms(dtm, lowfreq=1000)[1:50],corThreshold=0.7)
dev.off()
When I use the mc.cores=1 argument in tm_map, the operation continues indefinitely. However, if I use the lazy=TRUE argument in tm_map, it seemingly goes well, but subsequent operations give this error.
Error in UseMethod("meta", x) :
no applicable method for 'meta' applied to an object of class "try-error"
In addition: Warning messages:
1: In mclapply(x$content[i], function(d) tm_reduce(d, x$lazy$maps)) :
all scheduled cores encountered errors in user code
2: In mclapply(unname(content(x)), termFreq, control) :
all scheduled cores encountered errors in user code
I have been looking all over for a solution but have failed consistently. Any help would be greatly appreciated!
Best! k
I found a solution that works.
Background/Debugging Steps
I tried several things that did not work:
- Adding "content_transformer" to some tm_map, to all, to one(totower)
- Adding "lazy = T" to tm_map
- Tried some parallel computing packages
While it isn't working for 2 of my scripts, it works every time for a third script. But the code of all three scripts is the same only the size of the .rda file I am loading is different. The data structure is also identical for all three.
- Dataset 1: Size - 493.3KB = error
- Dataset 2: Size - 630.6KB = error
- Dataset 3: Size - 300.2KB = works!
Just weird.
My sessionInfo() output:
R version 3.1.2 (2014-10-31)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
locale:
[1] de_DE.UTF-8/de_DE.UTF-8/de_DE.UTF-8/C/de_DE.UTF-8/de_DE.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] snowfall_1.84-6 snow_0.3-13 Snowball_0.0-11 RWekajars_3.7.11-1 rJava_0.9-6 RWeka_0.4-23
[7] slam_0.1-32 SnowballC_0.5.1 tm_0.6 NLP_0.1-5 twitteR_1.1.8 devtools_1.6
loaded via a namespace (and not attached):
[1] bit_1.1-12 bit64_0.9-4 grid_3.1.2 httr_0.5 parallel_3.1.2 RCurl_1.95-4.3 rjson_0.2.14 stringr_0.6.2
[9] tools_3.1.2
Solution
I just added this line after loading the data and everything works now:
MyCorpus <- tm_map(MyCorpus,
content_transformer(function(x) iconv(x, to='UTF-8-MAC', sub='byte')),
mc.cores=1)
Found the hint here: http://davetang.org/muse/2013/04/06/using-the-r_twitter-package/ (The author has updated his code due to the error on November 26, 2014.)
来源：https://stackoverflow.com/questions/26834576/big-text-corpus-breaks-tm-map