Set-Word Embeddings and Semantic Indices: A New Contextual Model for Empirical Language Analysis

Set-Word Embeddings and Semantic Indices: A New Contextual Model for Empirical Language Analysis

We present a new word embedding technique in a (non-linear) metric space based on the shared membership of terms in a corpus of textual documents, where the metric is naturally defined by the Boolean algebra of all subsets of the corpus and a measure <inline-formula><math xmlns="http:/...

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Bibliographic Details
Main Authors: Pedro Fernández de Córdoba, Carlos A. Reyes Pérez, Claudia Sánchez Arnau, Enrique A. Sánchez Pérez
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:Computers
Subjects:
word embedding
semantic projection
set metric
Lipschitz function
semantic index
Online Access:https://www.mdpi.com/2073-431X/14/1/30
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