tm

问题 I'm looking for specific n-grams in a corpus. Let's say I want to find 'asset management' and 'historical yield' in a collection of documents. This is how I loaded the corpus my_corpus <- VCorpus(DirSource(directory, pattern = ".pdf"), readerControl = list(reader = readPDF) I cleaned the corpus and did some basic calculations using document term matrices. Now I want to look for particular expressions and put them in a dataframe. This is what I use (thanks to phiver): ngrams <- c('asset

问题 Another potential title for this post could be "When parallel processing in r, does the ratio between number of cores, loop chunk size and object size matter?" I have a corpus I am running some transformations on using tm package. Since the corpus is large I'm using parallel processing with doparallel package. Sometimes the transformations do the task, but sometimes they do not. For example, tm::removeNumbers() . The very first document in the corpus has a content value of "n417". So if

问题 I am trying to work with the tm package in R, and have a CSV file of customer feedback with each line being a different instance of feedback. I want to import all the content of this feedback into a corpus but I want each line to be a different document within the corpus, so that I can compare the feedback in a DocTerms Matrix. There are over 10,000 rows in my data set. Originally I did the following: fdbk_corpus <-Corpus(VectorSource(fdbk), readerControl = list(language="eng"), sep="\t")

问题 I am trying to run this code (Ubuntu 12.04, R 3.1.1) # Load requisite packages library(tm) library(ggplot2) library(lsa) # Place Enron email snippets into a single vector. text <- c( "To Mr. Ken Lay, I’m writing to urge you to donate the millions of dollars you made from selling Enron stock before the company declared bankruptcy.", "while you netted well over a $100 million, many of Enron's employees were financially devastated when the company declared bankruptcy and their retirement plans

问题 I am trying to run this code (Ubuntu 12.04, R 3.1.1) # Load requisite packages library(tm) library(ggplot2) library(lsa) # Place Enron email snippets into a single vector. text <- c( "To Mr. Ken Lay, I’m writing to urge you to donate the millions of dollars you made from selling Enron stock before the company declared bankruptcy.", "while you netted well over a $100 million, many of Enron's employees were financially devastated when the company declared bankruptcy and their retirement plans

问题 I am trying to run this code (Ubuntu 12.04, R 3.1.1) # Load requisite packages library(tm) library(ggplot2) library(lsa) # Place Enron email snippets into a single vector. text <- c( "To Mr. Ken Lay, I’m writing to urge you to donate the millions of dollars you made from selling Enron stock before the company declared bankruptcy.", "while you netted well over a $100 million, many of Enron's employees were financially devastated when the company declared bankruptcy and their retirement plans

问题 i'm sorry for new question , but i newbie in text mining, and need in advices of profy. Now, after long torments with content_transformer i have clean corpus The next question 1. How select from `dtm` the words with small frequencies , so that the amount of frequencies was not more than 1% For example i need this format x 0,5% of all words in the dataset y 0,2% z 0,3% so here total frequencies sum =1% How do this? 回答1: You can take a look into the termDocumentMatrix function of the tm package

问题 I'm using the tm package, and looking to get the Flesch-Kincaid scores for a document using R. I found the koRpus package has some a lot of metrics including reading-level, and started using that. However, the object returned seems to be a very complicated s4 object I don't understand how to parse. So, I apply this to my corpus: txt <- system.file("texts", "txt", package = "tm") (d <- Corpus(DirSource(txt, encoding = "UTF-8"), readerControl = list(language = "lat"))) f <- function(x) tokenize

问题 I'm using the tm package to clean up a Twitter Corpus. However, the package is unable to clean up emoticons. Here's a replicated code: July4th_clean <- tm_map(July4th_clean, content_transformer(tolower)) Error in FUN(content(x), ...) : invalid input 'RT ElleJohnson Love of country is encircling the globes ������������������ july4thweekend July4th FourthOfJuly IndependenceDay NotAvailableOnIn' in 'utf8towcs' Can someone point me in the right direction to remove the emoticons using the tm

问题 I installed the tm package in R to do some text mining analysis. After creating a corpus I wanted to use the tm_map() function, which throws the following error message: The process has forked and you cannot use this CoreFoundation functionality safely. You MUST exec().Break on Anybody an idea why this message turns up? Here's more code for clarification: > require(tm) Lade nötiges Paket: tm > a <-Corpus(VectorSource(chi2014_df$text)) > a A corpus with 70 text documents > a <-tm_map(a,tolower