GitHub

A text similarity analysis project using Word2Vec embeddings and multiple similarity measures (Cosine, Jaccard, Euclidean) to compare document contents and visualize their ...

Long Description (for README): This project demonstrates text similarity analysis using Word2Vec embeddings for document representation. It processes a set of documents, tokenizes and lemmatizes the ...
GitHub

Rushikeshkadam1/Spam-Ham-Classification-using-Word2Vec-and-Random-Forest

The goal of this project is to classify text messages as either "spam" or "ham" (non-spam) using a combination of Word2Vec word embeddings and a Random Forest classifier. The process involves ...
IEEE

Comparative Study of Word2Vec, FastText, and Glove Embeddings for Synonym Identification in Bugis Language

Abstract: This research aims to analyze the performance of word vectors generated by three pre-trained word embedding models, namely Word2Vec, Fast'Text, and Glove, to detect synonyms at the word ...
IEEE

Evaluating Word2Vec and WordNet for Semantic Similarity at Myanmar Word and Sentence Levels

Abstract: One of the most important NLP processes is word embedding, which converts words into numerical vectors for various NLP tasks. Although Word2Vec has been widely used for word embeddings in ...
Óstáilte ar MSN

Train Word Embeddings with Word2Vec in Python from Scratch

Discover a smarter way to grow with Learn with Jay, your trusted source for mastering valuable skills and unlocking your full potential. Whether you're aiming to advance your career, build better ...
Frontiers

Optimizing clustering of CDR3 sequences using natural language processing, Word2Vec, and KMeans

1 University of Dallas, Computer Science Department, Irving, TX, United States 2 University of Dallas, Biology Department, Irving, TX, United States T-cell receptor (TCR) sequencing has emerged as a ...