node

→ Irish: nód

From Middle English node, borrowed from Latin nōdus. Doublet of knot, knout, and nodus.

computational linguistics
computational linguistics

(computational linguistics) The word of interest in a KWIC, surrounded by left and right cotexts.


concordance

en-noun

concordance (countable and uncountable, plural concordances)

concordances (plural)
concordaunce (alternative)

From Old French concordance, from Late Latin concordantia.

(computational linguistics) A list of occurrences of a word or phrase from a corpus, with the immediate context.


shingle

From Middle English shyngel, from Old English sċingul, a late variant of sċindel, from Proto-West Germanic *skindulā, borrowed from Late Latin scindula, from Latin scandula, from Proto-Indo-European *sked- (“to split, scatter”), from *sek- (“to cut”). Doublet of shindle.

der

In the second phase, we produce a list of all the shingles and the documents they appear in, sorted by shingle value.

1997 September 1, Andrei Z. Broder, Steven C. Glassman, Mark S. Manasse, Geoffrey Zweig, “Syntactic clustering of the Web”, in Computer Networks and ISDN Systems (Papers from the Sixth International World Wide Web Conference), volume 29, number 8, →DOI, →ISSN, pages 1157–1166:

(computational linguistics) A word-based n-gram.


OOV

Rather, the n-grams are calculated as usual only for the most common k words, and all other words are regarded as Out-Of-Vocabulary (OOV) items and mapped to a single token such as .

1991, Christopher D. Manning, Hinrich Schütze, Foundations of Statistical Natural Language Processing, Cambridge, Mass.: MIT Press, →ISBN, page 199:

(computational linguistics) Initialism of out of vocabulary: describing a term encountered in the input which is not present in a system's dictionary or database of known terms.


pertainym

(computational linguistics) A word, usually an adjective, which can be defined as "of or pertaining to" another word.


trigram

From tri- + -gram, literally “three marks”.

In fact, half of all such words for this corpus are initiated by only 39 different trigrams!

1974, Edward C. Carterette, Margaret Hubbard Jones, Informal Speech: Alphabetic & Phonemic Texts with Statistical Analyses and Tables, University of California Press, →ISBN, page 44:

(computational linguistics) An n-gram consisting of three items from a sequence.

þrístæða

linguistics: n-gram consisting of three items


bag of words

You can then use the bag of words to train classifiers, a special kind of algorithm used to break words down into categories.

2023, John Paul Mueller, Luca Massaron, Python for Data Science For Dummies, John Wiley & Sons, →ISBN, page 132:

(computational linguistics) The collection of words from an unprocessed text without regard to grammar; a collection of word unigrams.


statistical semantics

(computational linguistics) The study of estimation of the meanings of words by looking at patterns of words in huge collections of texts, using statistical methods.


treebank

treebanks (plural)
tree bank (alternative)

If one wants to use a treebank for linguistic investigation, […]

2003, Diana Santos, “Timber! Issues in treebank building and use” in Computational Processing of the Portuguese Language, eds. Nuno J. Mamede, Jorge Baptista, Isabel Trancoso, Maria das Gracas Volpe Nunes, p. 152

(linguistics, computational linguistics) A database of sentences which are annotated with syntactic information, often in the form of a tree.


treebank

en-verb

treebank (third-person singular simple present treebanks, present participle treebanking, simple past and past participle treebanked)

treebanks (present singular third-person)
treebanking (participle present)
treebanked (participle past)
treebanked (past)
tree bank (alternative)

(linguistics, computational linguistics) To parse and annotate sentences according to a treebank.


keyness

This was one of the weakest keywords that was found, with a keyness of 24.9.

2005, Paul Baker, Public Discourse of Gay Men, →ISBN, page 160:

(computational linguistics) The statistical significance of a keyword's frequency in a given corpus, relative to a reference corpus.


BON

en-noun

BON (countable and uncountable, plural BONs)

Note that the BoW scheme is a special case of the BoN scheme, with n=1.

2020, Sowmya Vajjala, Bodhisattwa Majumder, Anuj Gupta, Harshit Surana, Practical Natural Language Processing […] , First edition, Beijing Boston Farnham Sebastopol Tokyo: O'Reilly, →ISBN:

(computational linguistics) Initialism of bag of n-grams.


antidictionary

From anti- (“opposite of, reverse”, prefix) + dictionary.

prefix

An antidictionary method is based on an inverse kind of knowledge. Such a method maintains an antidictionary with strings that do not appear in the input. Using the antidictionary, the encoder can often predict the next data symbol […]

2010, David Salomon, Giovanni Motta, Handbook of Data Compression, Springer Science & Business Media, →ISBN, page 430:

(computational linguistics) The set of all words of minimal length that never appear in a particular string.


chunker

From chunk (“divide into chunks”) + -er.

(computational linguistics) A software tool for dividing text into chunks.


n-gram

Hyland's study demonstrates how n-grams can reveal similarities and differences both between genres and between different sets of writers.

2012, Winnie Cheng, Exploring Corpus Linguistics: Language in Action, Routledge, →ISBN:

(computational linguistics) A contiguous sequence of n items (usually characters or words) from a given sequence of text or speech, used in analysis.

N-Gramm

linguistics: contiguous sequence of n items


proplet

From proposition + -let, coined by Roland Hausser.

(computational linguistics) A basic element of a proposition.


sentiment analysis

en-noun

sentiment analysis (countable and uncountable, plural sentiment analyses)

(computational linguistics, text analysis) The use of computers to process natural language in an attempt to identify and extract information about the writer's affective state.

tunneanalyysi

the analysis of text to identify subjective information about the writer


antidicionário

pt-noun

antidicionário m (plural antidicionários)

(computational linguistics) antidictionary (the set of all words of minimal length that never appear in a particular string)


análise de sentimentos

análise de sentimentos f (plural análises de sentimentos)

análises de sentimentos (plural)
análise de sentimento (alternative)

(computational linguistics, text analysis) sentiment analysis (the analysis of text to identify subjective information about the writer)


coreset

This coreset based learning approach can be applied for both real-time learning of small, varied data and fast learning of big data..

2015, Abhimanyu Dubey, Nikhil Naik, Dan Raviv, Rahul Sukthankar, Ramesh Raskar, “Coreset-Based Adaptive Tracking”, in arXiv:

(computational geometry) A small set of points that approximates the shape of a larger point set, in the sense that applying some geometric measure to the two sets (such as their minimum bounding box volume) results in approximately equal numbers.


string substitution

en-noun

string substitution (plural string substitutions)

(computational linguistics) A mapping of letters to sets of strings, which creates a closed operation for regular and context-free languages.


epsilon-machine

epsilon-machines (plural)
ϵ-machine (alternative)
ε-machine (alternative)

From epsilon + machine. Coined by James Crutchfield and Karl Young in their 1989 paper “Inferring Statistical Complexity”.

With a direct measure of an ε'''-machine’s complexity, the theory gives a computation-theoretic foundation to the notions of model optimality and, most importantly, a measure of the computational complexity of estimated models.

1989, James Crutchfield, Karl Young, Inferring Statistical Complexity:

The ϵ'''-machine is the organization of the process, or at least of the part of it which is relevant to our measurements. It leads to a natural measure of the statistical complexity of processes, namely the amount of information needed to specify the state of the ϵ'''-machine. […] Using the ϵ'''-machine, we see that the causal states always form a Markov process. This is satisfying ideologically, and has interesting information-theoretic and ergodic consequences.

2001, Cosma Rohilla Shalizi, Causal Architecture, Complexity and Self-Organization in Time Series and Cellular Automata:

These predictors, called ε-machines, are a subset of a well known statistical model class called the Hidden Markov Model (HMM). Despite being a subset, ε-machines have several important advantages over traditional HMMs. This dissertation illustrates these advantages by applying ε-machines to several problems in computer security: anomaly-based intrusion detection in High Performance Computing (HPC) environments, automated protocol reverse engineering, and structural drift.

2010, Sean Harrison Whalen, Security applications of the epsilon-machine, abstract:

This article introduces both a new algorithm for reconstructing epsilon-machines from data, as well as the decisional states. These are defined as the internal states of a system that lead to the same decision, based on a user-provided utility or pay-off function. […] The intrinsic underlying structure of the system is modeled by an epsilon-machine and its causal states.

2011, Nicolas Brodu, “Reconstruction of epsilon-machines in predictive frameworks and decisional states”, in Advances in Complex Systems, volume 14, number 05:

(computational mechanics) A deterministic automaton consisting of a system of causal states and the transitions between them, functioning as the smallest possible maximally predictive model of a stochastic process


word vector

(computational linguistics) A vector of weights that represents a word in numerical form.


CBOW

continuous bag of words
continuous bag of words#English

(computational linguistics) Initialism of continuous bag of words.


skip-gram

(computational linguistics) An n-gram in which component words need not be adjacent.


continuous bag of words

continuous bag of words (plural continuous bags of words)

(computational linguistics) A bag of words comprised of the words in the vicinity of a specific target.


rejection sampling

rejection sampling (usually uncountable, plural rejection samplings)

(computational statistics, numerical analysis) A technique used to generate observations from a distribution by repeatedly sampling an approximation function that bounds the distribution everywhere from above and rejecting the samples based on the quotient of the two functions at the sample's location.


concordança

(computational linguistics, bible studies) concordance


BOW

However, despite these shortcomings, due to its simplicity and ease of implementation, BoW is a commonly used text representation scheme, especially for text classification among other NLP problems.

(computational linguistics) Initialism of bag of words.


BoW

(computational linguistics) Alternative letter-case form of BOW.


BoN

(computational linguistics) Alternative letter-case form of BON (“bag of n-grams”).


audio-visual speech recognition

audio-visual speech recognition (uncountable)

(computational linguistics) A technique that uses lip reading through image processing to enhance speech recognition systems.


automated essay scoring

natural language processing
natural language processing

(computational linguistics) The use of specialized computer programs and natural language processing to evaluate and assign grades to essays in educational settings.


automatic summarization

(computational linguistics) The process of using AI algorithms to computationally condense a set of data.


Bradford's law

Named after Samuel C. Bradford (1878–1948).

named-after

(computational linguistics) A pattern that observes the diminishing returns in the search for references within science journals.


Brown clustering

Named after Peter Fitzhugh Brown (1955–).

(computational linguistics) An approach in natural language processing that involves grouping words into clusters based on distributional information and shared contexts within bigram language models.


cache language model

en-noun

cache language model (plural cache language models)

(computational linguistics) A type of statistical language model that assigns probabilities to word sequences based on a probability distribution.


co-occurrence network

co-occurrence network (plural co-occurrence networks)

(computational linguistics) A text analysis method that visually represents relationships among entities based on their co-occurrence in electronic text.


collocation extraction

(computational linguistics) The automated process of identifying and extracting word combinations that frequently appear together in a given corpus.


computational humor

artificial intelligence
artificial intelligence

(computational linguistics) A field within computational linguistics and artificial intelligence that leverages computers for research on humor.


computational lexicology

(computational linguistics) The use of computers to analyze lexicons, especially machine-readable dictionaries.


computational semantics

(computational linguistics) The study of automating the creation and interpretation of meaning representations in natural language expressions.


content determination

(computational linguistics) The process of selecting and organizing information within a generated text.


deep learning speech synthesis

deep learning speech synthesis (uncountable)

(computational linguistics) The use of sophisticated neural networks to generate lifelike human speech from written text or spectrum data.


distributional semantics

(computational linguistics) A field of research focused on quantifying and categorizing the semantic similarities between linguistic items.


distributional–relational database

distributional–relational database (plural distributional–relational databases)

database management system
database management system

(computational linguistics) A type of database management system that enhances the semantics of structured data by using distributional word-vector representations.


filtered-popping recursive transition network (plural filtered-popping recursive transition networks)

(computational linguistics) An extension of recursive transition networks.


foundation model

foundation model (plural foundation models)

(computational linguistics) An AI model trained on comprehensive data, enabling its application across various use cases such as chatbots and generative AI.


Gale–Church algorithm

Named after William A. Gale and Kenneth W. Church.

(computational linguistics) A method that aligns corresponding sentences in a parallel corpus.


generative lexicon

(computational linguistics) A linguistic semantics theory that challenges purely verb-centric approaches to compositionality.


grammar induction

(computational linguistics) The process of constructing a model that captures the characteristics of observed objects by learning a formal grammar.


inside–outside–beginning

(computational linguistics) A tagging scheme commonly employed in tasks such as named-entity recognition within computational linguistics.


intelligent character recognition

intelligent character recognition (uncountable)

(computational linguistics) An advanced technology specialized in extracting handwritten text from images.


interlingual machine translation

interlingual machine translation (uncountable)

(computational linguistics) A classic method where the source language is converted into an abstract, language-independent representation called interlingua.


language resource

language resource (plural language resources)

(computational linguistics) Linguistic material used for developing, enhancing, or assessing language processing applications.


Lesk algorithm

Named after American computer scientist Mike Lesk (1945–).

named-after

(computational linguistics) A classical algorithm that disambiguates word senses by comparing dictionary definitions of an ambiguous word with its surrounding context.


document structuring

(computational linguistics) The systematic arrangement and grouping of sentences within a generated text.


lexical choice

(computational linguistics) The selection of content words in a generated text.


lexical resource

en-noun

lexical resource (plural lexical resources)

(computational linguistics) A linguistic asset comprising information about the words and their meanings within one or more languages.


lexical simplification

(computational linguistics) A subtask of text simplification that swaps words or phrases in a text to make it simpler and easier to understand, reducing its complexity.


lexical substitution

(computational linguistics) The task of replacing a word with another word while maintaining the meaning and context of the original sentence or phrase.


logic form

(computational linguistics) The representation of natural language sentences in first-order logic, where concept predicates are combined through shared arguments.


minimal recursion semantics

minimal recursion semantics (uncountable)

(computational linguistics) A computational semantic framework employed in typed feature structure formalisms.


morphological dictionary

morphological dictionary (plural morphological dictionaries)

(computational linguistics) A resource that documents the relationship between surface forms and their corresponding lexical forms.


morphological pattern

morphological pattern (plural morphological patterns)

(computational linguistics) A systematic set of associations or operations used to construct the different forms of a lexeme.


multilingual notation

multilingual notation (plural multilingual notations)

(computational linguistics) A system used in lexical resources to denote words or phrases in multiple languages.


樹庫

/ʂu⁵¹⁻⁵³ kʰu⁵¹/

/ʂu⁵¹⁻⁵³ kʰu⁵¹/

(linguistics, computational linguistics) treebank