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AI Glossary

The complete dictionary of Artificial Intelligence

162
categories
2,032
subcategories
23,060
terms
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Sentiment Inference

Process of deducing an emotion or opinion from contextual and non-explicit clues when polarity words are absent from the text.

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Implicit Polarity

Positive or negative orientation of a text that is not directly expressed by adjectives or emotional keywords, but inferred from the described situation.

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Contextual Inference Model

Machine learning architecture, often based on transformers, designed to understand long-term relationships and global context to reveal hidden sentiments.

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Connotation Analysis

Examination of word associations and secondary meanings of neutral words to reveal emotional charge or indirect opinion in discourse.

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Abductive Reasoning

Logical inference method for determining the best possible explanation for a set of observations, used to guess the most likely sentiment of an ambiguous text.

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Computational Sarcasm

Branch of natural language processing that develops algorithms to detect sarcasm, a form of implicitness where positive statements mask negative criticism.

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World Knowledge Model

System integrating factual databases and commonsense schemas to enable AI to make logical deductions about indirectly described emotional states.

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Inter-sentence Analysis

Technique that goes beyond isolated sentences to analyze relationships and contrasts between multiple sentences to infer overall opinion or sentiment changes.

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Detection of veiled opinion

Identification of opinions expressed through facts, neutral descriptions, or rhetorical questions, where the value judgment is implied rather than stated.

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Entity-based inference

Method that deduces sentiment by analyzing the relationships between named entities (people, products, brands) and the actions or states associated with them in the text.

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Reasoning graph model

Approach that structures text information in the form of a graph (nodes and edges) to model the logical inferences necessary for detecting implicit sentiments.

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Modality analysis

Examination of markers of certainty, possibility, or obligation (e.g., 'could', 'seems', 'must') to assess the speaker's degree of commitment and nuance the inferred sentiment.

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Prompt engineering for implicit content

Design of sophisticated instructions for large language models, guiding them to perform multi-step reasoning to detect non-explicit opinions.

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Implicit quadrant

Classification framework for texts with implicit sentiment along two axes: the level of ambiguity (low/high) and the source of inference (local context/world knowledge).

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Metaphor analysis

Process of interpreting metaphorical expressions to extract their emotional charge or value judgment, which are often masked by figurative meaning.

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Euphemism detection

Identification of the use of softened or indirect expressions to replace a potentially negative or unpleasant term, in order to reveal the concealed real sentiment.

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