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Text mining, text data mining (TDM) or text analytics is the process of deriving high-quality information from text. It involves "the discovery by computer of new, previously unknown information, by automatically extracting information from different written resources." [1] Written resources may include websites, books, emails, reviews, and ...
Some examples: replacing "the taxi driver" with the pronoun "he" or "two girls" with "they". Another example can be found in formulaic sequences such as "as stated previously" or "the aforementioned". Cataphoric reference is the opposite of anaphora: a reference forward as opposed to backward in the discourse. Something is introduced in the ...
The bag-of-words model (BoW) is a model of text which uses a representation of text that is based on an unordered collection (a "bag") of words. It is used in natural language processing and information retrieval (IR). It disregards word order (and thus most of syntax or grammar) but captures multiplicity.
A more complex example is the lexer hack in C, where the token class of a sequence of characters cannot be determined until the semantic analysis phase since typedef names and variable names are lexically identical but constitute different token classes. Thus in the hack, the lexer calls the semantic analyzer (say, symbol table) and checks if ...
Sentiment analysis (also known as opinion mining or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information.
An analysis is usually built by reading the text and constructing a tree using the relations. The following example is a title and summary, appearing at the top of an article in Scientific American magazine (Ramachandran and Anstis, 1986). The original text, broken into numbered units, is: [3] Diagram of RST analysis
To exploit a parallel text, some kind of text alignment identifying equivalent text segments (phrases or sentences) is a prerequisite for analysis. Machine translation algorithms for translating between two languages are often trained using parallel fragments comprising a first-language corpus and a second-language corpus, which is an element ...
Content analysis is research using the categorization and classification of speech, written text, interviews, images, or other forms of communication. In its beginnings, using the first newspapers at the end of the 19th century, analysis was done manually by measuring the number of columns given a subject.