The Atticus Project was recently announced as an initiative to, among other things, build a world-class corpus of labelled legal contracts which could be used to train and/or benchmark text ...
Abstract: Despite the high performance of the existing embedding approaches for Aspect-Based Sentiment Analysis (ABSA), such as Word2Vec and GloVe, they still have several limitations, mainly in ...
Using a word2vec model built on all tweets, we identified hashtags relevant to COVID-19 and performed hashtag clustering to obtain related topics. We then ran an inference analysis for urban and rural ...
Learn With Jay on MSNOpinion
Word2Vec from scratch: Training word embeddings explained part 1
In this video, we will learn about training word embeddings. To train word embeddings, we need to solve a fake problem. This ...
We will discuss word embeddings this week. Word embeddings represent a fundamental shift in natural language processing (NLP), transforming words into dense vector representations that capture ...
Abstract: To solve the problems of polysemy and feature extraction in the text sentiment analysis process, a BERT-CNN-BiLSTM-Att hybrid model has been proposed for text sentiment analysis. The BERT ...
This project is a movie recommendation system based on IMDB data, developed using Word2Vec and deep learning techniques. The goal is to embed movie features into a vector space and use these ...
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