Word embeddings form the foundation of many AI systems, learning relationships between words from their co-occurrence in large text corpora. However, these representations can also absorb human biases ...

Contemporary cognitive-linguistic research often seeks to consolidate metaphorical expressions into systematic mappings between source and target domains. However, the formulation of such mappings in ...

In this tutorial, we present a complete end-to-end Natural Language Processing (NLP) pipeline built with Gensim and supporting libraries, designed to run seamlessly in Google Colab. It integrates ...

In this video, we will about training word embeddings by writing a python code. So we will write a python code to train word embeddings. To train word embeddings, we need to solve a fake problem. This ...

"Gender ideology" is a nonsense term, meant to obscure meaning and frighten people. His lies also depend on people not reading his various anti-trans executive orders. It's not just that these orders ...

Abstract: Query by example spoken term detection (QbE-STD) is a popular keyword detection method in the absence of speech resources. It can build a keyword query system with decent performance when ...

I'm trying to run word2vec using your tutorial (https://blogs.rstudio.com/ai/posts/2017-12-22-word-embeddings-with-keras/) with RStudio (version 4.0.2). When I run ...