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Language technology, natural language processing, computational linguistics The analysis and processing of various types of corpora are also the subject of much work in computational linguistics , speech recognition and machine translation , where they are often used to create hidden Markov models for part of speech tagging and other purposes.
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. The bag-of-words model is commonly used in methods of document classification where, for example, the (frequency of) occurrence of each word is used as a feature for training a ...
Markup can control the display of a document or enrich its content to facilitate automated processing. A markup language is a set of rules governing what markup information may be included in a document and how it is combined with the content of the document in a way to facilitate use by humans and computer programs.
Document processing is a field of research and a set of production processes aimed at making an analog document digital. Document processing does not simply aim to photograph or scan a document to obtain a digital image, but also to make it digitally intelligible.
Processing this file through the Scribe compiler to generate an associated document file, which can be printed. The Scribe markup language defined the words, lines, pages, spacing, headings, footings, footnotes, numbering, tables of contents, etc. in a way similar to HTML. The Scribe compiler used a database of Styles (containing document ...
Natural-language programming (NLP) is an ontology-assisted way of programming in terms of natural-language sentences, e.g. English. [1] A structured document with Content, sections and subsections for explanations of sentences forms a NLP document, which is actually a computer program.
In computer science, the syntax of a computer language is the rules that define the combinations of symbols that are considered to be correctly structured statements or expressions in that language. This applies both to programming languages, where the document represents source code, and to markup languages, where the document represents data.
Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.