R: Compute Score for Matching Terms

tm_term_score {tm} | R Documentation

## Compute Score for Matching Terms

### Description

Compute a score based on the number of matching terms.

### Usage

    ## S3 method for class 'DocumentTermMatrix'
    tm_term_score(x, terms, FUN = row_sums)
    ## S3 method for class 'PlainTextDocument'
    tm_term_score(x, terms, FUN = function(x) sum(x, na.rm = TRUE))
    ## S3 method for class 'term_frequency'
    tm_term_score(x, terms, FUN = function(x) sum(x, na.rm = TRUE))
    ## S3 method for class 'TermDocumentMatrix'
    tm_term_score(x, terms, FUN = col_sums)

### Arguments

`x` | Either a `PlainTextDocument`, a term frequency as returned by `termFreq`, or a `TermDocumentMatrix`.
`terms` | A character vector of terms to be matched.
`FUN` | A function computing a score from the number of terms matching in `x`.

### Value

A score as computed by `FUN` from the number of matching `terms` in `x`.

### Examples

    data("acq")
    tm_term_score(acq[[1]], c("company", "change"))
    ## Not run: ## Test for positive and negative sentiments
    ## install.packages("tm.lexicon.GeneralInquirer", repos="http://datacube.wu.ac.at", type="source")
    require("tm.lexicon.GeneralInquirer")
    sapply(acq[1:10], tm_term_score, terms_in_General_Inquirer_categories("Positiv"))
    sapply(acq[1:10], tm_term_score, terms_in_General_Inquirer_categories("Negativ"))
    tm_term_score(TermDocumentMatrix(acq[1:10],
                                    control = list(removePunctuation = TRUE)),
                 terms_in_General_Inquirer_categories("Positiv"))
    ## End(Not run)

[Package tm version 0.7-5 Index]