addDocument
Add documents to bag-of-words or bag-of-n-grams model
Description
Examples
Add Documents to Bag-of-Words Model
Create a bag-of-words model from an array of tokenized documents.
documents = tokenizedDocument([ "an example of a short sentence" "a second short sentence"]); bag = bagOfWords(documents)
bag = bagOfWords with properties: Counts: [2x7 double] Vocabulary: ["an" "example" "of" "a" "short" "sentence" "second"] NumWords: 7 NumDocuments: 2
Create another array of tokenized documents and add it to the same bag-of-words model.
documents = tokenizedDocument([ "a third example of a short sentence" "another short sentence"]); newBag = addDocument(bag,documents)
newBag = bagOfWords with properties: Counts: [4x9 double] Vocabulary: ["an" "example" "of" "a" "short" "sentence" "second" "third" "another"] NumWords: 9 NumDocuments: 4
Import Text from Multiple Files Using a File Datastore
If your text data is contained in multiple files in a folder, then you can import the text data into MATLAB using a file datastore.
Create a file datastore for the example sonnet text files. The examples sonnets have file names "exampleSonnetN.txt
", where N
is the number of the sonnet. Specify the read function to be extractFileText
.
readFcn = @extractFileText; fds = fileDatastore('exampleSonnet*.txt','ReadFcn',readFcn);
Create an empty bag-of-words model.
bag = bagOfWords
bag = bagOfWords with properties: Counts: [] Vocabulary: [1x0 string] NumWords: 0 NumDocuments: 0
Loop over the files in the datastore and read each file. Tokenize the text in each file and add the document to bag
.
while hasdata(fds) str = read(fds); document = tokenizedDocument(str); bag = addDocument(bag,document); end
View the updated bag-of-words model.
bag
bag = bagOfWords with properties: Counts: [4x276 double] Vocabulary: ["From" "fairest" "creatures" "we" "desire" "increase" "," "That" "thereby" "beauty's" "rose" "might" "never" "die" "But" "as" "the" "riper" "should" ... ] (1x276 string) NumWords: 276 NumDocuments: 4
Input Arguments
bag
— Input bag-of-words or bag-of-n-grams model
bagOfWords
object | bagOfNgrams
object
Input bag-of-words or bag-of-n-grams model, specified as a bagOfWords
object or a bagOfNgrams
object.
documents
— Input documents
tokenizedDocument
array | string array | cell array of character vectors
Input documents, specified as a tokenizedDocument
array, a string array of words, or a cell array of
character vectors. If documents
is not a
tokenizedDocument
array, then it must be a row vector representing
a single document, where each element is a word. To specify multiple documents, use a
tokenizedDocument
array.
Output Arguments
newBag
— Output model
bagOfWords
object | bagOfNgrams
object
Output model, returned as a bagOfWords
object or a bagOfNgrams
object. The type of
newBag
is the same as the type of
bag
.
Version History
Introduced in R2017b
See Also
bagOfWords
| bagOfNgrams
| removeDocument
| removeEmptyDocuments
| tokenizedDocument
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