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University of Crete

Academic institutioneurope · gr
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Research library81linked papers
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Selected work

Representative Papers

slang.gr as a Large-Scale Crowdsourced Resource for Non-Standard Greek

Jul 23, 2026

This study addresses the scarcity of structured computational resources for non-standard Greek slang—a linguistic variety hindered by its dynamic and unregulated nature, which impedes both linguistic inquiry and NLP applications. To bridge this gap, the authors present slang.gr, the first large-scale computational resource for Greek slang, integrating lexical entries, user-generated tags, and interaction data. They introduce a novel multi-layer taxonomy that uniquely combines semantic and sociolinguistic metadata. Through folksonomy-based tag cleaning, ontology mapping, community behavior modeling, and a credibility-weighted scoring algorithm, the work reveals that Greek slang is highly oriented toward person- and evaluation-related expressions and exhibits strong morphological innovativeness. The proposed taxonomy significantly enhances analytical interpretability and establishes a foundational framework for computational modeling of non-standard language varieties.

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Non--negative matrix factorization using the \textit{R} package \textsf{nnmf}

Jul 22, 2026

This study addresses the lack of systematic, real-data-based evaluation among existing Non-negative Matrix Factorization (NMF) implementations in R, which hinders informed package selection by users. To resolve this gap, we introduce nnmf, a new R package for NMF, and present the first comprehensive benchmark comparing nnmf against two widely used NMF packages within a unified experimental framework. The evaluation leverages real-world datasets and assesses performance across multiple dimensions—including computational efficiency, convergence behavior, reconstruction accuracy, memory consumption, and numerical stability. Our results clearly delineate the relative strengths and weaknesses of each implementation and demonstrate that nnmf achieves superior overall performance, thereby offering practitioners a reliable basis for selecting an appropriate NMF tool for real-world applications.

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Recent publications

Latest Papers

slang.gr as a Large-Scale Crowdsourced Resource for Non-Standard Greek

Jul 23, 2026

This study addresses the scarcity of structured computational resources for non-standard Greek slang—a linguistic variety hindered by its dynamic and unregulated nature, which impedes both linguistic inquiry and NLP applications. To bridge this gap, the authors present slang.gr, the first large-scale computational resource for Greek slang, integrating lexical entries, user-generated tags, and interaction data. They introduce a novel multi-layer taxonomy that uniquely combines semantic and sociolinguistic metadata. Through folksonomy-based tag cleaning, ontology mapping, community behavior modeling, and a credibility-weighted scoring algorithm, the work reveals that Greek slang is highly oriented toward person- and evaluation-related expressions and exhibits strong morphological innovativeness. The proposed taxonomy significantly enhances analytical interpretability and establishes a foundational framework for computational modeling of non-standard language varieties.

0 citationsRead paper

Non--negative matrix factorization using the \textit{R} package \textsf{nnmf}

Jul 22, 2026

This study addresses the lack of systematic, real-data-based evaluation among existing Non-negative Matrix Factorization (NMF) implementations in R, which hinders informed package selection by users. To resolve this gap, we introduce nnmf, a new R package for NMF, and present the first comprehensive benchmark comparing nnmf against two widely used NMF packages within a unified experimental framework. The evaluation leverages real-world datasets and assesses performance across multiple dimensions—including computational efficiency, convergence behavior, reconstruction accuracy, memory consumption, and numerical stability. Our results clearly delineate the relative strengths and weaknesses of each implementation and demonstrate that nnmf achieves superior overall performance, thereby offering practitioners a reliable basis for selecting an appropriate NMF tool for real-world applications.

0 citationsRead paper