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A paper generator is computer software that composes scholarly papers in the style of those that appear in academic journals or conference proceedings. Typically, the generator uses technical jargon from the field to compose sentences that are grammatically correct and seem erudite but are actually nonsensical. [ 1 ]
SCIgen is a paper generator that uses context-free grammar to randomly generate nonsense in the form of computer science research papers. Its original data source was a collection of computer science papers downloaded from CiteSeer. All elements of the papers are formed, including graphs, diagrams, and citations.
Regular languages are a category of languages (sometimes termed Chomsky Type 3) which can be matched by a state machine (more specifically, by a deterministic finite automaton or a nondeterministic finite automaton) constructed from a regular expression.
This ontology will define the data structures the NLP can use in sentences. Definition of one or more top-level sentences in terms of concepts from the ontology. These sentences are later used to invoke the most important activities in the topic. Defining of each of the top-level sentences in terms of a sequence of sentences.
On Wikipedia and other sites running on MediaWiki, Special:Random can be used to access a random article in the main namespace; this feature is useful as a tool to generate a random article. Depending on your browser, it's also possible to load a random page using a keyboard shortcut (in Firefox , Edge , and Chrome Alt-Shift + X ).
In this context, parsing refers to the way that human beings analyze a sentence or phrase (in spoken language or text) "in terms of grammatical constituents, identifying the parts of speech, syntactic relations, etc." [1] This term is especially common when discussing which linguistic cues help speakers interpret garden-path sentences. Within ...
Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
At the time when biologist Carl Linnaeus (1707–1778) published the books that are now accepted as the starting point of binomial nomenclature, Latin was used in Western Europe as the common language of science, and scientific names were in Latin or Greek: Linnaeus continued this practice.
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