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Text-matching software (TMS), which is also referred to as "plagiarism detection software" or "anti-plagiarism" software, has become widely available, in the form of both commercially available products as well as open-source [examples needed] software. TMS does not actually detect plagiarism per se, but instead finds specific passages of text ...
In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references).
Some of these words occur in a context where duplication is intended, such as for emphasis: please please, blah blah, yadda yadda, very very; where the scientific name of an animal coincides with the common name: Gorilla gorilla, Homo sapiens sapiens; where the genus and subgenus have the same name: Octopus Octopus; or even part of the name ...
Voyant "was conceived to enhance reading through lightweight text analytics such as word frequency lists, frequency distribution plots, and KWIC displays." [3] Its interface is composed of panels which perform these varied analytical tasks. These panels can also be embedded in external web texts (e.g. a web article could include a Voyant panel ...
This means that, among other things, a pattern can match strings of repeated words like "papa" or "WikiWiki", called squares in formal language theory. The pattern for these strings is (.+)\1. The language of squares is not regular, nor is it context-free, due to the pumping lemma.
The bag-of-words model (BoW) is a model of text which uses 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 .
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IWE combines Word2vec with a semantic dictionary mapping technique to tackle the major challenges of information extraction from clinical texts, which include ambiguity of free text narrative style, lexical variations, use of ungrammatical and telegraphic phases, arbitrary ordering of words, and frequent appearance of abbreviations and acronyms ...