想做个层次聚类，转置后设置行名时提示Error in `rownames<-`(`*tmp*`, value = c(271L, 247L, 342L, 1158L, 1338L,  :
  length of 'dimnames' [1] not equal to array extent
plot的时候又提示
Error in graphics:::plotHclust(n1, merge, height, order(x$order), hang,  :
  谱系图输入不对

以下是代码和数据，望各位大神帮忙看看，在下新手，多谢多谢！
> csv <- read.table("body1.txt",header=T)
> mystopwords<- unlist (read.table("StopWords.txt",stringsAsFactors=F))
> library(tm)
> #移除数字
> removeNumbers = function(x) { ret = gsub("[0-9０１２３４５６７８９]","",x) }
> #中文分词，也可以考虑使用rmmseg4j、rsmartcn
> wordsegment<- function(x) {
+     library(Rwordseg)
+     segmentCN(x)
+ }
> #去除停止词，效果比较差，可以进一步完善
> removeStopWords = function(x,words) {
+     ret = character(0)
+     index <- 1
+     it_max <- length(x)
+     while (index <= it_max) {
+         if (length(words[words==x[index]]) <1) ret <- c(ret,x[index])
+         index <- index +1
+     }
+     ret
+ }
> Sys.setenv(JAVA_HOME='C:/Program Files/Java/jdk1.6.0_43/jre')
> sample.words <- lapply(csv, removeNumbers)
> sample.words <- lapply(sample.words, wordsegment)
> #先处理中文分词，再处理stopwords，防止全局替换丢失信息
> sample.words <- lapply(sample.words, removeStopWords, mystopwords)
> #构建语料库
> corpus = Corpus(VectorSource(sample.words))
>
> sample.dtm <- DocumentTermMatrix(corpus, control = list(wordLengths = c(2, Inf)))
> sample_matrix =as.matrix(sample.dtm)
> rownames(sample_matrix)<- csv$newsid
Error in `rownames<-`(`*tmp*`, value = c(271L, 247L, 342L, 1158L, 1338L,  :
  length of 'dimnames' [1] not equal to array extent
>
> dtm2 = removeSparseTerms(sample.dtm, sparse=0.99)
> d <- dist(dtm2, method = "euclidean")
> fit <- hclust(d, method="ward.D")
> plot(fit)
Error in graphics:::plotHclust(n1, merge, height, order(x$order), hang,  :
  谱系图输入不对


还想问问大家，由于我的数据量比较大，做层次聚类的谱系图会太密集，看不清，有什么更好的文本聚类方法吗？我后续还想进行如用cutree提取出每条新闻属于哪一类的操作，不知道有没有别的方法或函数能做到的，多谢大家了！