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diff --git a/Untitled.R b/Untitled.R
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--- a/Untitled.R
+++ b/Untitled.R
@@ -1,98 +1,614 @@
-install.packages("tm")
-install.packages("ggplot2")
-install.packages("wordcloud")
-
-library(tm)
-library(ggplot2)
-
-## corpus of 50 documents
-DocData<-data("acq")
-
-########################################
-## Q(a) try function in lecture
-inspect(acq)
-## the length of specific document
-test11<-acq[[1]]
-test11
-## sparsity/ Max length term
-ACQdtm<-DocumentTermMatrix(acq)
-ACQdtm
-## inspect term
-inspect(ACQdtm[1:15, 1:6])
-## frequency of term
-test1tf <- termFreq(test11)
-test1tf
-## convert to a dataFrame
-test1df <- as.data.frame(test1tf)
-test1df
-## Convert the corpus to lower case
-ACQlow<- tm_map(acq, content_transformer(tolower))
-ACQlow
-## remove anything other than English letters or spaces
-removeNumPunct <- function(x) gsub("[^[:alpha:][:space:]]*", "", x)
-ACQcl <- tm_map(ACQlow, content_transformer(removeNumPunct))
-## remove stop words from the corpus
-myStopword <- c(stopwords('english'))
-ACQstop <- tm_map(ACQcl, removeWords, myStopword)
-inspect(ACQstop[1:2])
-## find terms with a frequency of 5 or more
-ACQtdm2 <- TermDocumentMatrix(ACQstop, control = list(wordLengths = c(1, Inf)))
-ACQtdm2
-freq.terms <- findFreqTerms(ACQtdm2, lowfreq = 5)
-freq.terms
-## find words associated with "states"
-findAssocs(ACQtdm2, "states", 0.25)
-## term frequency
-term.freq <- rowSums(as.matrix(ACQtdm2))
-term.freq <- subset(term.freq, term.freq >= 5)
-df <- data.frame(term = names(term.freq), freq = term.freq)
-term.freq
-df
-
-
-###########################################
-## Q(b) use inspect
-## 15 largest document
-## 20:2457 7:3635 4:2308 1:1287 21:1009 23:1873 26:3516 30:3109 36:1465 .......
-inspect(acq)
-
-############################################
-## Q(c) 
-## dendrogram
-tdm2 <- removeSparseTerms(ACQtdm2, sparse = 0.50)
-tdm2
-dd <- dist(scale(tdm2), method = "euclidean")
-hc <- hclust(dd, method = "ward.D2")
-plot(hc)
-## WordCloud
-m1 <- as.matrix(tdm2)
-word.freq <- sort(rowSums(m1), decreasing = T)
-word.freq
-library(wordcloud)
-pal <- brewer.pal(9, "BuGn")
-pal <- pal[-(1:4)]
-wordcloud(words = names(word.freq), freq = word.freq, min.freq = 3, random.order = F, colors = pal)
-
-######################################################
-install.packages("textreuse")
-install.packages("wordnet")
-install.packages("zipfR")
-## see the content of document
-as.character(acq[[7]])
-## Q(d)
-library(textreuse)
-## get one of 15 largest documents
-docI <- acq[[7]]
-charDoc <- as.character(docI)
-# print every word find the longest one
-tokenize_words(charDoc)
-# print every sentences find the longest one
-tokenize_sentences(charDoc)
-
-## Q(e)
-## draw a table show the length of longest sentence
-length_array <- c(15, 16)    ## change length here
-length_data <- data.frame(len = length_array[1:2])
-mytable <- cbind(sites = c("file 1", "file 2"), length_data[1:2,])   ## change file name here
-rownames(mytable) <- c("No1", "No2")
-
+install.packages("tm")
+install.packages("ggplot2")
+install.packages("wordcloud")
+install.packages("hash")
+
+library(tm)
+library(ggplot2)
+
+## corpus of 50 documents
+DocData<-data("acq")
+
+########################################
+## Q(a) try function in lecture
+inspect(acq)
+## the length of specific document
+test11<-acq[[1]]
+test11
+## sparsity/ Max length term
+ACQdtm<-DocumentTermMatrix(acq)
+ACQdtm
+## inspect term
+inspect(ACQdtm[1:15, 1:6])
+## frequency of term
+test1tf <- termFreq(test11)
+test1tf
+## convert to a dataFrame
+test1df <- as.data.frame(test1tf)
+test1df
+## Convert the corpus to lower case
+ACQlow<- tm_map(acq, content_transformer(tolower))
+ACQlow
+## remove anything other than English letters or spaces
+removeNumPunct <- function(x) gsub("[^[:alpha:][:space:]]*", "", x)
+ACQcl <- tm_map(ACQlow, content_transformer(removeNumPunct))
+## remove stop words from the corpus
+myStopword <- c(stopwords('english'))
+ACQstop <- tm_map(ACQcl, removeWords, myStopword)
+inspect(ACQstop[1:2])
+## find terms with a frequency of 5 or more
+ACQtdm2 <- TermDocumentMatrix(ACQstop, control = list(wordLengths = c(1, Inf)))
+ACQtdm2
+freq.terms <- findFreqTerms(ACQtdm2, lowfreq = 5)
+freq.terms
+## find words associated with "states"
+findAssocs(ACQtdm2, "states", 0.25)
+## term frequency
+term.freq <- rowSums(as.matrix(ACQtdm2))
+term.freq <- subset(term.freq, term.freq >= 5)
+df <- data.frame(term = names(term.freq), freq = term.freq)
+term.freq
+df
+
+
+###########################################
+## Q(b) use inspect
+## 15 largest document
+## 50:1068, 47:3013, 44:1022, 42:1607, 36:1043, 34:1465, 29:3109, 25:3516, 22:1873, 20:1009, 19:2457
+## 18:871, 7:3635, 4:2308, 1:1287
+inspect(acq)
+
+############################################
+## Q(c) 
+## dendrogram
+tdm2 <- removeSparseTerms(ACQtdm2, sparse = 0.50)
+tdm2
+dd <- dist(scale(tdm2), method = "euclidean")
+hc <- hclust(dd, method = "ward.D2")
+plot(hc)
+## WordCloud
+m1 <- as.matrix(tdm2)
+word.freq <- sort(rowSums(m1), decreasing = T)
+word.freq
+library(wordcloud)
+pal <- brewer.pal(9, "BuGn")
+pal <- pal[-(1:4)]
+wordcloud(words = names(word.freq), freq = word.freq, min.freq = 3, random.order = F, colors = pal)
+
+######################################################
+install.packages("textreuse")
+install.packages("wordnet")
+install.packages("zipfR")
+install.packages("tidyverse")
+install.packages("tokenizers")
+## see the content of document
+as.character(acq[[7]])
+## Q(d)
+library(textreuse)
+library(tidyverse)
+library(tokenizers)
+## get one of 15 largest documents
+docI <- acq[[7]]
+charDoc <- as.character(docI)
+max_word1 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word1)){
+    max_word1 = word
+   }
+}
+docI <- acq[[50]]
+charDoc <- as.character(docI)
+max_word2 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word2)){
+    max_word2 = word
+  }
+}
+docI <- acq[[47]]
+charDoc <- as.character(docI)
+max_word3 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word3)){
+    max_word3 = word
+  }
+}
+
+
+docI <- acq[[44]]
+charDoc <- as.character(docI)
+max_word4 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word4)){
+    max_word4 = word
+  }
+}
+
+docI <- acq[[42]]
+charDoc <- as.character(docI)
+max_word5 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word5)){
+    max_word5 = word
+  }
+}
+
+
+docI <- acq[[36]]
+charDoc <- as.character(docI)
+max_word6 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word6)){
+    max_word6 = word
+  }
+}
+
+
+docI <- acq[[34]]
+charDoc <- as.character(docI)
+max_word7 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word7)){
+    max_word7 = word
+  }
+}
+
+
+docI <- acq[[29]]
+charDoc <- as.character(docI)
+max_word8 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word8)){
+    max_word8 = word
+  }
+}
+
+
+docI <- acq[[25]]
+charDoc <- as.character(docI)
+max_word9 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word9)){
+    max_word9 = word
+  }
+}
+
+
+docI <- acq[[22]]
+charDoc <- as.character(docI)
+max_word10 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word10)){
+    max_word10 = word
+  }
+}
+
+
+docI <- acq[[20]]
+charDoc <- as.character(docI)
+max_word11 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word11)){
+    max_word11 = word
+  }
+}
+
+
+docI <- acq[[19]]
+charDoc <- as.character(docI)
+max_word12 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word12)){
+    max_word12 = word
+  }
+}
+
+
+docI <- acq[[18]]
+charDoc <- as.character(docI)
+max_word13 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word13)){
+    max_word13 = word
+  }
+}
+
+docI <- acq[[4]]
+charDoc <- as.character(docI)
+max_word14 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word14)){
+    max_word14 = word
+  }
+}
+
+docI <- acq[[1]]
+charDoc <- as.character(docI)
+max_word15 = ""
+for (word in tokenize_words(charDoc)){
+  if(nchar(word) > nchar(max_word15)){
+    max_word15 = word
+  }
+}
+
+
+
+
+print(max_word1)
+print(max_word2)
+print(max_word3)
+print(max_word4)
+print(max_word5)
+print(max_word6)
+print(max_word7)
+print(max_word8)
+print(max_word9)
+print(max_word10)
+print(max_word11)
+print(max_word12)
+print(max_word13)
+print(max_word14)
+print(max_word15)
+
+
+
+
+
+# print the longest sentence in every file
+docI <- acq[[7]]
+charDoc <- as.character(docI)
+max_sentence_len1 = 0
+max_sentence1 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len1){
+    max_sentence1 = line
+    max_sentence_len1 = count
+  }
+}
+
+
+
+docI <- acq[[50]]
+charDoc <- as.character(docI)
+max_sentence_len2 = 0
+max_sentence2 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len2){
+    max_sentence2 = line
+    max_sentence_len2 = count
+  }
+}
+
+
+
+docI <- acq[[47]]
+charDoc <- as.character(docI)
+max_sentence_len3 = 0
+max_sentence3 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len3){
+    max_sentence3 = line
+    max_sentence_len3 = count
+  }
+}
+
+
+
+
+docI <- acq[[44]]
+charDoc <- as.character(docI)
+max_sentence_len4 = 0
+max_sentence4 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len4){
+    max_sentence4 = line
+    max_sentence_len4 = count
+  }
+}
+
+
+
+docI <- acq[[42]]
+charDoc <- as.character(docI)
+max_sentence_len5 = 0
+max_sentence5 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len5){
+    max_sentence5 = line
+    max_sentence_len5 = count
+  }
+}
+
+
+
+docI <- acq[[36]]
+charDoc <- as.character(docI)
+max_sentence_len6 = 0
+max_sentence6 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len6){
+    max_sentence6 = line
+    max_sentence_len6 = count
+  }
+}
+
+
+
+docI <- acq[[34]]
+charDoc <- as.character(docI)
+max_sentence_len7 = 0
+max_sentence7 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len7){
+    max_sentence7 = line
+    max_sentence_len7 = count
+  }
+}
+
+
+
+docI <- acq[[29]]
+charDoc <- as.character(docI)
+max_sentence_len8 = 0
+max_sentence8 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len8){
+    max_sentence8 = line
+    max_sentence_len8 = count
+  }
+}
+
+
+
+docI <- acq[[25]]
+charDoc <- as.character(docI)
+max_sentence_len9 = 0
+max_sentence9 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len9){
+    max_sentence9 = line
+    max_sentence_len9 = count
+  }
+}
+
+
+
+docI <- acq[[22]]
+charDoc <- as.character(docI)
+max_sentence_len10 = 0
+max_sentence10 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len10){
+    max_sentence10 = line
+    max_sentence_len10 = count
+  }
+}
+
+
+
+docI <- acq[[20]]
+charDoc <- as.character(docI)
+max_sentence_len11 = 0
+max_sentence11 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len11){
+    max_sentence11 = line
+    max_sentence_len11 = count
+  }
+}
+
+docI <- acq[[19]]
+charDoc <- as.character(docI)
+max_sentence_len12 = 0
+max_sentence12 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len12){
+    max_sentence12 = line
+    max_sentence_len12 = count
+  }
+}
+
+
+
+
+docI <- acq[[18]]
+charDoc <- as.character(docI)
+max_sentence_len13 = 0
+max_sentence13 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len13){
+    max_sentence13 = line
+    max_sentence_len13 = count
+  }
+}
+
+
+docI <- acq[[4]]
+charDoc <- as.character(docI)
+max_sentence_len14 = 0
+max_sentence14 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len14){
+    max_sentence14 = line
+    max_sentence_len14 = count
+  }
+}
+
+
+
+docI <- acq[[1]]
+charDoc <- as.character(docI)
+max_sentence_len15 = 0
+max_sentence15 = ""
+for (line in tokenize_sentences(charDoc)){
+  count = 0
+  for (words in tokenize_words(line)){
+    count=count+1
+  }
+  #print(line)
+  if(count > max_sentence_len15){
+    max_sentence15 = line
+    max_sentence_len15 = count
+  }
+}
+
+
+
+print(max_sentence1)
+print(max_sentence2)
+print(max_sentence3)
+print(max_sentence4)
+print(max_sentence5)
+print(max_sentence6)
+print(max_sentence7)
+print(max_sentence8)
+print(max_sentence9)
+print(max_sentence10)
+print(max_sentence11)
+print(max_sentence12)
+print(max_sentence13)
+print(max_sentence14)
+print(max_sentence15)
+#######################################################
+## Q(e)
+## draw a table show the length of longest sentence
+length_array <- c(max_sentence_len1,max_sentence_len2,max_sentence_len3,max_sentence_len4,max_sentence_len5,max_sentence_len6,max_sentence_len7,max_sentence_len8,max_sentence_len9,max_sentence_len10,max_sentence_len11,max_sentence_len12,max_sentence_len13,max_sentence_len14,max_sentence_len15)    ## change length here
+length_data <- data.frame(len = length_array[1:2])
+mytable <- cbind(sites = c("file 7", "file 50", "file 47", "file 44", "file 42", "file 36", "file 34", "file 29", "file 25", "file 22", "file 20", "file 19", "file 18", "file 4", "file 1"), length_data[1:2,])   ## change file name here
+rownames(mytable) <- c("No1", "No2", "No3", "No4", "No5", "No6", "No7", "No8", "No9", "No10", "No11", "No12", "No13", "No14", "No15")
+
+#############################################################
+## Q(f)
+## remove punctuation
+fileNoPun <- tm_map(acq, content_transformer(removeNumPunct))
+DocINoPun <- fileNoPun[[7]]
+tokenize_sentences(as.character(DocINoPun))
+
+
+#############################################################
+## Q(g)
+## print part of speech of every word
+library(wordnet)
+docI <- acq[[7]]
+charDoc <- as.character(docI)
+sentences <- tokenize_sentences(charDoc)
+sentences_words <- sapply(sentences, tokenize_words)
+sentences
+
+
+##############################################################
+## Q(h)
+## print word frequency
+library(zipfR)
+testFre <- termFreq(acq[[7]])
+rt_pos = as.data.frame(testFre)
+Vm = rt_pos[1]
+testFre
+
+###############################################################
+library(tm)
+library(textreuse)
+
+target = "current"
+file_index = 1
+find = 0
+result_index = 1
+for(i in 1:50){
+  File <- acq[[file_index]]
+  charFile <- as.character(File)
+  line_index = 1
+  for(line in tokenize_sentences(charFile)){
+    
+    word_index = 1
+    for(word in tokenize_words(line)){
+      if(word == target){
+        print(paste(paste("No.", as.character(result_index)), "result"))
+        print(paste(paste("No.", as.character(file_index)), "file"))
+        print(paste(paste("No.", as.character(line_index)), "line"))
+        print(paste(paste("No.", as.character(word_index)), "word"))
+        find = 1
+        result_index = result_index + 1
+        print('---------------')
+      }
+      word_index = word_index + 1
+    }
+    line_index = line_index + 1
+  }
+  file_index = file_index + 1
+}
+
+if(find == 0){
+  print("no such word!") 
+}
+
+
+