Text Data Preparation

Import text data into MATLAB^® and preprocess it for analysis

Text Analytics Toolbox™ includes tools for processing raw text from sources such as equipment logs, news feeds, surveys, operator reports, and social media. Use these tools to extract text from popular file formats, preprocess raw text, extract individual words or multiword phrases (n-grams), convert text into numerical representations, and build statistical models. For an example showing how to get started, see Prepare Text Data for Analysis.

Text Analytics Toolbox supports the languages English, Japanese, German, and Korean. Most Text Analytics Toolbox functions work with text from other languages. For more information, see Language Considerations.

Functions

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Import and Export

`extractFileText`	Read text from PDF, Microsoft Word, HTML, and plain text files
`extractHTMLText`	Extract text from HTML
`readPDFFormData`	Read data from PDF forms
`writeTextDocument`	Write documents to text file

HTML Parsing

`htmlTree`	Parsed HTML tree
`findElement`	Find elements in HTML tree
`getAttribute`	Read HTML attribute of root node of HTML tree
`ismissing`	Find HTML trees without values

Document Preprocessing

`tokenizedDocument`	Array of tokenized documents for text analysis
`erasePunctuation`	Erase punctuation from text and documents
`eraseTags`	Erase HTML and XML tags from text
`eraseURLs`	Erase HTTP and HTTPS URLs from text
`removeStopWords`	Remove stop words from documents
`removeShortWords`	Remove short words from documents or bag-of-words model
`removeLongWords`	Remove long words from documents or bag-of-words model
`removeWords`	Remove selected words from documents or bag-of-words model
`normalizeWords`	Stem or lemmatize words
`replaceWords`	Replace words in documents
`replaceNgrams`	Replace n-grams in documents
`stopWords`	List of stop words
`decodeHTMLEntities`	Convert HTML and XML entities into characters
`lower`	Convert documents to lowercase
`upper`	Convert documents to uppercase

Token Details

`context`	Search documents for word or n-gram occurrences in context
`tokenDetails`	Details of tokens in tokenized document array
`addSentenceDetails`	Add sentence numbers to documents
`addPartOfSpeechDetails`	Add part-of-speech tags to documents
`addLemmaDetails`	Add lemma forms of tokens to documents
`addLanguageDetails`	Add language identifiers to documents
`addEntityDetails`	Add entity tags to documents
`addTypeDetails`	Add token type details to documents
`splitSentences`	Split text into sentences
`corpusLanguage`	Detect language of text
`abbreviations`	Table of common abbreviations
`topLevelDomains`	List of top-level domains

Word and N-Gram Counting

`bagOfWords`	Bag-of-words model
`bagOfNgrams`	Bag-of-n-grams model
`addDocument`	Add documents to bag-of-words or bag-of-n-grams model
`removeDocument`	Remove documents from bag-of-words or bag-of-n-grams model
`removeInfrequentWords`	Remove words with low counts from bag-of-words model
`removeInfrequentNgrams`	Remove infrequently seen n-grams from bag-of-n-grams model
`removeNgrams`	Remove n-grams from bag-of-n-grams model
`removeEmptyDocuments`	Remove empty documents from tokenized document array, bag-of-words model, or bag-of-n-grams model
`topkwords`	Most important words in bag-of-words model or LDA topic
`topkngrams`	Most frequent n-grams
`encode`	Encode documents as matrix of word or n-gram counts
`tfidf`	Term Frequency–Inverse Document Frequency (tf-idf) matrix
`join`	Combine multiple bag-of-words or bag-of-n-grams models

Spelling Correction and Edit Distance

`correctSpelling`	Correct spelling of words
`editDistance`	Find edit distance between two strings or documents
`editDistanceSearcher`	Edit distance nearest neighbor searcher
`knnsearch`	Find nearest neighbors by edit distance
`rangesearch`	Find nearest neighbors by edit distance range
`splitGraphemes`	Split string into graphemes

Document Manipulation and Conversion

`docfun`	Apply function to words in documents
`plus`	Append documents
`replace`	Replace substrings in documents
`regexprep`	Replace text in words of documents using regular expression
`doclength`	Length of documents in document array
`doc2cell`	Convert documents to cell array of string vectors
`joinWords`	Convert documents to string by joining words
`string`	Convert scalar document to string vector

Topics

Import

Extract Text Data from Files

This example shows how to extract the text data from text, HTML, Microsoft® Word, PDF, CSV, and Microsoft Excel® files and import it into MATLAB® for analysis.

Parse HTML and Extract Text Content

This example shows how to parse HTML code and extract the text content from particular elements.

Data Sets for Text Analytics

Discover data sets for various text analytics tasks.