weightTfIdf: Weight by Term Frequency - Inverse Document Frequency
In tm: Text Mining Package

Description Usage Arguments Details Value References

Weight a term-document matrix by term frequency - inverse document frequency.

1	weightTfIdf(m, normalize = TRUE)

`m`	A `TermDocumentMatrix` in term frequency format.
`normalize`	A Boolean value indicating whether the term frequencies should be normalized.

Formally this function is of class WeightingFunction with the additional attributes name and acronym.

Term frequency \mathit{tf}_{i,j} counts the number of occurrences n_{i,j} of a term t_i in a document d_j. In the case of normalization, the term frequency \mathit{tf}_{i,j} is divided by ∑_k n_{k,j}.

Inverse document frequency for a term t_i is defined as

\mathit{idf}_i = \log_2 \frac{|D|}{|\{d \mid t_i \in d\}|}

where |D| denotes the total number of documents and where |\{d \mid t_i \in d\}| is the number of documents where the term t_i appears.

Term frequency - inverse document frequency is now defined as \mathit{tf}_{i,j} \cdot \mathit{idf}_i.

The weighted matrix.

Gerard Salton and Christopher Buckley (1988). Term-weighting approaches in automatic text retrieval. Information Processing and Management, 24/5, 513–523.

tm documentation built on April 7, 2021, 3:01 a.m.