word-frequency

问题 Given a string consists of words separated by a single white space, print out the words in descending order sorted by the number of times they appear in the string. For example an input string of “ab bc bc” would generate the following output: bc : 2 ab : 1 The problem would be easily resolved if C++ data structures, like a map, is used. But if the problem could only be solved in plain old C, it looks much harder. What kind of data structures and algorithms shall I use here? Please be as

问题 Say I have a list of words called words i.e. words = ["hello", "test", "string", "people", "hello", "hello"] and I want to create a dictionary in order to get word frequency. Let's say the dictionary is called 'counts' counts = {} for w in words: counts[w] = counts.get(w,0) + 1 The only part of this I don't really understand is the counts.get(w.0). The book says, normally you would use counts[w] = counts[w] + 1 but the first time you encounter a new word, it won't be in counts and so it would

问题 Say I have a list of words called words i.e. words = ["hello", "test", "string", "people", "hello", "hello"] and I want to create a dictionary in order to get word frequency. Let's say the dictionary is called 'counts' counts = {} for w in words: counts[w] = counts.get(w,0) + 1 The only part of this I don't really understand is the counts.get(w.0). The book says, normally you would use counts[w] = counts[w] + 1 but the first time you encounter a new word, it won't be in counts and so it would

问题 Seems like a simple command, but i cannot seem to find a good way generate this in R. Basically, I just want to count the frequency of each word in a dictionary, dict, within another dataframe's column, wordsgov: dict = "apple", "pineapple","pear" df$wordsgov = "i hate apple", "i hate apple", "i love pear", "i don't like pear", "pear is okay", "i eat pineapple sometimes" desired output: new frequency ranking, showing all words in dict according to their frequency within df$wordsgov dict freq

问题 Seems like a simple command, but i cannot seem to find a good way generate this in R. Basically, I just want to count the frequency of each word in a dictionary, dict, within another dataframe's column, wordsgov: dict = "apple", "pineapple","pear" df$wordsgov = "i hate apple", "i hate apple", "i love pear", "i don't like pear", "pear is okay", "i eat pineapple sometimes" desired output: new frequency ranking, showing all words in dict according to their frequency within df$wordsgov dict freq

问题 I need to count the frequency of each word in word2vec 's training model. I want to have output that looks like this: term count apple 123004 country 4432180 runs 620102 ... Is it possible to do that? How would I get that data out of word2vec? 回答1: Which word2vec implementation are you using? In the popular gensim library, after a Word2Vec model has its vocabulary established (either by doing its full training, or after build_vocab() has been called), the model's wv property contains a

问题 I have a python script that reads the text and applies preprocess functions in order to do the analysis. The problem is that I want to count the frequency of words but the system crash and displays the below error. File "F:\AIenv\textAnalysis\setup.py", line 208, in tag_and_save file.write(word+"/"+tag+" (frequency="+str(freq_tagged_data[word])+")\n") TypeError: tuple indices must be integers or slices, not str I am trying to count the frequency and then write to a text file . def get_freq

问题 I have a list of phrases and a corpus of documents.There are 100k+ phrases and 60k+ documents in the corpus. The phrases are might/might not present in the corpus. I'm looking forward to find the term frequency of each phrase present in the corpus. An example dataset: Phrases <- c("just starting", "several kilometers", "brief stroll", "gradually boost", "5 miles", "dark night", "cold morning") Doc1 <- "If you're just starting with workout, begin slow." Doc2 <- "Don't jump in brain initial and

问题 I have a corpus of 39 text files named by the year - 1945.txt, 1978.txt.... 2013.txt. I've imported them into R and created a Document Term Matrix using TM package. I'm trying to investigate how words associated with term'fraud' have changed over years from 1945 to 2013. The desired output would be a 39 by 10/5 matrix with years as row titles and top 10 or 5 terms as columns. Any help would be greatly appreciated. Thanks in advance. Structure of my TDM: > str(ytdm) List of 6 $ i : int [1:6791

问题 I turned about 50,000 rows of varchar data into a corpus, and then proceeded to clean said corpus using the TM package, getting ride of stopwords, punctuation, and numbers. I then turned it into a TermDocumentMatrix and used the functions findFreqTerms and findMostFreqTerms to run text analysis. findMostFreqTerms return the common words, and the number of times it shows up in the data. However, I want to use a function that says search for "word" and return how many times "word" appears in