similar to: using package tm to find phrases

I am using code that previously worked to remove stopwords using package "tm". Even manually adding "the" to the list does not work to remove "the". This package has undergone extensive redevelopment with changes to the function syntax, so perhaps I am just missing something. Please see my simple example, output, and sessionInfo() below. Thanks! Mark require(tm)

I am familiar with packages that read and write Excel files on both Windows and Linux platforms. Do any packages provide similar functionality for MS Word files? I have a lot of text processing to do and the text is embedded in ~200 different Word files (.doc format Office 2003). All I need to do is read, not write. Thanks, Mark ------------------------------------------------------------ Mark

I tried making a wordcloud of Obama's State of the Union address using the tm package to process the text sotu <- scan(file="c:/R/data/sotu2012.txt", what="character") sotu <- tolower(sotu) corp <-Corpus(VectorSource(paste(sotu, collapse=" "))) corp <- tm_map(corp, removePunctuation) corp <- tm_map(corp, stemDocument) corp <- tm_map(corp,

When I use any function of RWeka Package in Rstudio I get an error, "Error in .jnew (name): java.lang.ClassFormatError." can anyone guide me in this? [[alternative HTML version deleted]]

Hello, I am hoping for some advice regarding how I can install the XML package which I require to run package tm. Normally I would use the install package option, however, I have to install the packages to a laptop running XP. The laptop does not have an internet connection. Firstly I tried the file - XML_1.99-0.tar.gz . Below is the error I received Error in gzfile(file, "r") :

Hi, sorry for the dumb question and please ignore this post if you think it's far beyond; i know it's not the way to go, but for reasons ... Has anyone running a self compiled recent dovecot (2.2.36.4) on Debian-7 and does it work? Or thinks it should work. Surprisingly it actually compiles flawlessly on Debian-7, but i wonder wether it will become a complete mess replacingthe existing

Dear useRs, a first version of tm has just been released on CRAN. tm provides a sophisticated framework for text mining applications within R. It offers functionality for managing text documents, abstracts the process of document manipulation and eases the usage of heterogeneous text formats in R. An advanced metadata management is implemented for collections of text documents to alleviate the

Dear useRs, a first version of tm has just been released on CRAN. tm provides a sophisticated framework for text mining applications within R. It offers functionality for managing text documents, abstracts the process of document manipulation and eases the usage of heterogeneous text formats in R. An advanced metadata management is implemented for collections of text documents to alleviate the

I have recently started using "tm" package by Feinerer, K. Hornik, and D. Meyer. While trying to create a term-document matrix from a corpus (approxly 440 docs) I get the following error: tdm <- TermDocumentMatrix(tmp, control=list(weighting=weightTfIdf, minDocFreq=2, minWordLength=3)) *Error in rowSums(m > 0) : 'x' must be an array of at least two dimensions* This error

Dear R-user, Could anybody tell me of the key difference between data mining and text mining? Please make a list for packages about data/text mining. And give me an example of text mining with R (any relating materials will be highly appreciated), because a vignette written by Ingo Feinerer seems too concise for me. Thanks _____________________________________________ Dr.Ruixin ZHU Shanghai

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Hi all, I have tried to create a DocumentTermMatrix with a tm package, but i get this error : Error in tolower(txt) : invalid input 'PROD Z LAHKO GNETNO MELJNO GLINO, ... in 'utf8towcs' I tried doing this as it is showed in : http://www.r-project.org/doc/Rnews/Rnews_2008-2.pdf (An Introduction to Text Mining), with this R code :

Hello, We would like to create Google or Firefox like "search hints". If someone types "abc", the search system should name some possible hints. I think, Firefox does it by indexing 3-characters of the domain name. If you enter parts, you get some hints. Thank you very much Marcus

Hello Sir, I am a third-year student at the Department of mathematics at IIT Kharagpur. I have good experience in Information Retrieval and Machine Learning. I have read many chapters of the book Introduction to Information Retrieval. Recently I am doing a project on tagging a question on a Q&A Forum using ranking the tags and probabilistic inference. I also have software development

Hi Y'all, I am using the text mining package (tm). I am trying to filter out all of the words in a Term Document Matrix that are not in a list of words that I am interested in. I am using the following code: z<-tm_intersect(txt.dtm, c("communications", "safety", "climate", "blood", "surface", "cleanliness",

Hello, First I wanted to say thanks for a great piece of software, thanks Olly and others who've contributed! I know that Xapian supports right-truncating, if that's the proper name for wildcard support, as in a search for "xapia*". I don't believe Xapian supports wildcards on both sides of a term, correct? Is this something that is technically unfeasable, unpalatable

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi all, this is probably simple and I'm just doing something stupid, sorry about that :-) I'm trying to convert words (strings of letters) into a fairly small dimensional space (say 10, but anything between about 5 and 50 would be ok), which I will call a feature vector. The the distance between two words represents the similarity of the

Hi: I try to construct a Document-Term Meatrix from a corpus. The commands I used are: > library(parallel)> library(tm)> library(RWeka)> library(topicmodels)> library(RTextTools)> cl=makeCluster(detectCores())> invisible(clusterEvalQ(cl, library(tm)))> invisible(clusterEvalQ(cl, library(RWeka))) > invisible(clusterEvalQ(cl, library(topicmodels)))>

Hi, I bumped into a serious issue while trying to analyse some texts in Bulgarian language (with the tm package). I import a tab-separated csv file, which holds a total of 22 variables, most of which are text cells (not factors), using the read.delim function: data<-read.delim("bigcompanies_ascii.csv", header=TRUE, quote="'",

Hi, I bumped into a serious issue while trying to analyse some texts in Bulgarian language (with the tm package). I import a tab-separated csv file, which holds a total of 22 variables, most of which are text cells (not factors), using the read.delim function: data<-read.delim("bigcompanies_ascii.csv", header=TRUE, quote="'",