Glossary - Revision history

BGreatley-Hirsch at 14:15, 6 April 2023

2023-04-06T14:15:20Z

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	=== word-type ===		=== word-type ===
	See [[#type\|type]].		See [[#type\|type]].


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			Page created and maintained by Brett Greatley-Hirsch; updated 29 August 2021.
			[[Category:Greatley-Hirsch, Brett]]
			__NOTOC__

BGreatley-Hirsch at 17:14, 29 August 2021

2021-08-29T17:14:14Z

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	~~= About the Glossary =~~

	Attribution scholarship, especially so-called "non-traditional" studies, typically relies on technical vocabulary. This page will provide glosses in plain language to demystify these unfamiliar terms and concepts.		Attribution scholarship, especially so-called "non-traditional" studies, typically relies on technical vocabulary. This page will provide glosses in plain language to demystify these unfamiliar terms and concepts.

	~~= Entries =~~

	== A ==		== A ==

BGreatley-Hirsch: /* About the Glossary */

2021-08-27T10:57:36Z

About the Glossary

← Older revision		Revision as of 10:57, 27 August 2021
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	= About the Glossary =		= About the Glossary =

	~~Placeholder text about how attribution~~ scholarship ~~often uses highly~~ technical language.		Attribution scholarship, especially so-called "non-traditional" studies, typically relies on technical vocabulary. This page will provide glosses in plain language to demystify these unfamiliar terms and concepts.

	= Entries =		= Entries =

BGreatley-Hirsch at 21:48, 7 July 2021

2021-07-07T21:48:37Z

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	=== content words ===		=== content words ===
	~~(Also~~ ''lexical words'') A term for a group of [[#open-class_words\|open-class words]] that supply the lexical content of a sentence, as opposed to words whose purpose is primarily or exclusively grammatical (i.e., [[#function_words\|function words]]). Content words include adjectives and nouns, as well as most verbs and adverbs.		'''also lexical words''' A term for a group of [[#open-class_words\|open-class words]] that supply the lexical content of a sentence, as opposed to words whose purpose is primarily or exclusively grammatical (i.e., [[#function_words\|function words]]). Content words include adjectives and nouns, as well as most verbs and adverbs.

	== F ==		== F ==

	=== function words ===		=== function words ===
	~~(Also~~ ''grammatical words'') A term for a group of [[#closed-class_words\|closed-class words]] that carry little, no, or ambiguous lexical meaning but otherwise express grammatical relationships among other words in a sentence. Function words in English typically include auxiliary verbs, conjunctions, determiners (e.g. the definite and indefinite articles), particles, prepositions, pronouns, and some adverbs. Since they are essential to the structuring of sentences, function words are among the most frequently used words in written and spoken English. (Cf. [[#content_words\|content words]].)		'''also grammatical words''' A term for a group of [[#closed-class_words\|closed-class words]] that carry little, no, or ambiguous lexical meaning but otherwise express grammatical relationships among other words in a sentence. Function words in English typically include auxiliary verbs, conjunctions, determiners (e.g. the definite and indefinite articles), particles, prepositions, pronouns, and some adverbs. Since they are essential to the structuring of sentences, function words are among the most frequently used words in written and spoken English. (Cf. [[#content_words\|content words]].)

	== G ==		== G ==

BGreatley-Hirsch: added more entries

2021-07-07T21:47:31Z

added more entries

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 === algorithm ===
 A set of logical instructions or mathematical rules used to perform calculations and problem-solving operations, typically by a computer.
 == M ==
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 === machine learning ===
 A class of [[#algorithm|algorithm]] that analyse patterns and relationships in data to make determinations and predictions, using the outcomes of these operations to ''learn'' by iterations and improve future accuracy. Machine learning procedures may be [[#supervised|supervised]], requiring human intervention to provide pre-defined examples with which to ''train'' the algorithm, or [[#unsupervised|unsupervised]], where no human pre-processing of the data is required.
 == S ==

BGreatley-Hirsch at 17:16, 3 July 2021

2021-07-03T17:16:47Z

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	=== machine learning ===		=== machine learning ===
	A class of algorithm that analyse patterns and relationships in data to make determinations and predictions, using the outcomes of these operations to ''learn'' by iterations and improve future accuracy. Machine learning procedures may be ''supervised'', requiring human intervention to provide pre-defined examples with which to ''train'' the algorithm, or ''unsupervised'', where no human pre-processing of the data is required.		A class of [[#algorithm\|algorithm]] that analyse patterns and relationships in data to make determinations and predictions, using the outcomes of these operations to ''learn'' by iterations and improve future accuracy. Machine learning procedures may be [[#supervised\|supervised]], requiring human intervention to provide pre-defined examples with which to ''train'' the algorithm, or [[#unsupervised\|unsupervised]], where no human pre-processing of the data is required.

			== S ==

			=== supervised ===
			In the context of machine learning and statistical analysis, an [[#algorithm\|algorithm]] that requires human intervention to provide pre-defined examples with which to [[#training\|train]] is said to be ''supervised''. In attribution study, a typical supervised procedure may [[#training\|train]] an [[#algorithm\|algorithm]] on a corpus comprising texts of known authorship to identify [[#feature\|features]] with which to test others.


	== T ==		== T ==
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	=== text encoding ===		=== text encoding ===

	A set of explicit instructions for the computational representation of text. Whereas a human reader of the text of Othello, for example, is familiar with the conventions distinguishing the word ''Othello'' as it functions as a title, a running header, a speech prefix, or as a reference to the character in stage directions and dialogue, a computer generally requires these distinctions to be made explicit. Textual encoding or "markup" involves annotating or "tagging" to define units of text (from individual letters to entire documents) into categories. Linguistic features (e.g. grammatical part of speech, syntactic function, and so on) are commonly tagged to support natural language processing, and structural features are used to distinguish elements of text and paratext (e.g. title, dialogue, speech prefix, stage direction, prologue). Other kinds of analysis may require additional categories, such as tagging gender or social status.		A set of explicit instructions for the computational representation of text. Whereas a human reader of the text of ''Othello'', for example, is familiar with the conventions distinguishing the word "Othello" as it functions as a title, a running header, a speech prefix, or as a reference to the character in stage directions and dialogue, a computer generally requires these distinctions to be made explicit. Textual encoding or "markup" involves annotating or "tagging" to define units of text (from individual letters to entire documents) into categories. Linguistic features (e.g. grammatical part of speech, syntactic function, and so on) are commonly tagged to support natural language processing, and structural features are used to distinguish elements of text and paratext (e.g. title, dialogue, speech prefix, stage direction, prologue). Other kinds of analysis may require additional categories, such as tagging gender or social status.

	=== token ===		=== token ===

	A concrete instance of a ''type''. "I came, I saw, I conquered", for example, contains six word-tokens (excluding punctuation): "came", "saw", "conquered", and three instances of "I".		A concrete instance of a [[#type\|type]]. "I came, I saw, I conquered", for example, contains six word-tokens (excluding punctuation): "came", "saw", "conquered", and three instances of "I".

	=== type ===		=== type ===

	A unique form; cf. ''token''. "I came, I saw, I conquered", for example, contains four word-types (excluding punctuation): "I", "came", "saw", and "conquered".		A unique form; cf. [[#token\|token]]. "I came, I saw, I conquered", for example, contains four word-types (excluding punctuation): "I", "came", "saw", and "conquered".

			== U ==

			=== unsupervised ===

			In the context of machine learning and statistical analysis, an [[#algorithm\|algorithm]] that requires no human intervention or pre-processing of the data is said to be ''unsupervised''. This way, the [[#algorithm\|algorithm]] processes the data without bias. Principal Components Analysis is an example of a widely used unsupervised method.

	== W ==		== W ==

BGreatley-Hirsch at 17:02, 3 July 2021

2021-07-03T17:02:51Z

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	=== word-token ===		=== word-token ===
	See [[#token]].		See [[#token\|token]].

	=== word-type ===		=== word-type ===
	See ''type''.		See [[#type\|type]].

BGreatley-Hirsch at 17:02, 3 July 2021

2021-07-03T17:02:03Z

← Older revision		Revision as of 17:02, 3 July 2021
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	=== word-token ===		=== word-token ===
	See ''token''.		See [[#token]].

	=== word-type ===		=== word-type ===
	See ''type''.		See ''type''.

BGreatley-Hirsch at 17:01, 3 July 2021

2021-07-03T17:01:25Z

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	~~{{tocright}}~~

	= About the Glossary =		= About the Glossary =

BGreatley-Hirsch at 17:01, 3 July 2021

2021-07-03T17:01:10Z

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			{{tocright}}

	= About the Glossary =		= About the Glossary =

	Placeholder text about how attribution scholarship often uses highly technical language.		Placeholder text about how attribution scholarship often uses highly technical language.

	= Entries = ~~{{tocright}}~~		= Entries =

	== A ==		== A ==