Gender bias in Word Embeddings: toward a gender score analysis in textual documents. [PDF]
, 2022 openIl seguente elaborato proporne uno studio dei principali esperimenti condotti sui Word Embeddings, con un’attenzione particolare a quelli relativi ai WE nella lingua italiana e una seguente analisi del gender score nei documenti testuali.
FRISO, LUCA
core
Word Embeddings for Domain Specific Semantic Relatedness [PDF]
, 2018 Word embeddings are becoming pervasive in natural language processing (NLP), with one of their main strengths being their ability to capture semantic relationships between words.
Tilbury, Kyle
core +2 more sources
Morphological Skip-Gram: Replacing FastText characters n-gram with morphological knowledge
Inteligencia Artificial, 2021 Natural language processing systems have attracted much interest of the industry. This branch of study is composed of some applications such as machine translation, sentiment analysis, named entity recognition, question and answer, and others.
Thiago Dias Bispo +3 more
doaj +1 more source
Activation of embedded words in spoken word recognition. [PDF]
Journal of Experimental Psychology: Human Perception and Performance, 1997 info:eu-repo/semantics ...
Vroomen, Jean, De Gelder, Béatrice
openaire +3 more sources
Benchmark for Evaluation of Danish Clinical Word Embeddings
Northern European Journal of Language Technology, 2023 In natural language processing, benchmarks are used to track progress and identify useful models. Currently, no benchmark for Danish clinical word embeddings exists.
Martin Sundahl Laursen +4 more
doaj +1 more source
On the Dimensionality of Word Embedding
CoRR, 2018 In this paper, we provide a theoretical understanding of word embedding and its dimensionality. Motivated by the unitary-invariance of word embedding, we propose the Pairwise Inner Product (PIP) loss, a novel metric on the dissimilarity between word embeddings.
Zi Yin, Yuanyuan Shen
openaire +3 more sources
Analysis of Italian Word Embeddings [PDF]
, 2017 In this work we analyze the performances of two of the most used word embeddings algorithms, skip-gram and continuous bag of words on Italian language. These algorithms have many hyper-parameter that have to be carefully tuned in order to obtain accurate word representation in vectorial space. We provide an extensive analysis and an evaluation, showing
Tripodi, Rocco, Pira, Stefano Li
openaire +5 more sources
Uno studio sui Word Embeddings per documenti di ambito medico: Il caso di studio della collezione PubMed [PDF]
, 2022 Questo elaborato ha come obbiettivo quello di studiare i Word Embeddings, in relazione alla loro applicazione alla collezione biomedicale di PubMed. L'interesse è quello di sviluppare una versione del modello SkipGram con la quale addestrare i Word ...
Beschi, Andrea
core
Efficient estimation of Hindi WSD with distributed word representation in vector space
Journal of King Saud University: Computer and Information Sciences, 2022 Word Sense Disambiguation (WSD) is significant for improving the accuracy of the interpretation of a Natural language text. Various supervised learning-based models and knowledge-based models have been developed in the literature for WSD of the language ...
Archana Kumari, D.K. Lobiyal
doaj +1 more source
When FastText Pays Attention: Efficient Estimation of Word Representations using Constrained Positional Weighting [PDF]
Journal of Universal Computer Science, 2022 In 2018, Mikolov et al. introduced the positional language model, which has characteristics of attention-based neural machine translation models and which achieved state-of-the-art performance on the intrinsic word analogy task.
Vít Novotný +4 more
doaj +3 more sources