Ever found yourself helplessly drawn to an irresistibly intriguing headline, only to be met with disappointment? If so, you might have been a victim of clickbait, the irresistible rogue of the ...

Abstract: NLP or Natural Language Processing in Machine Learning forms a subarea with linguistic roots that has applications in analyzing and predicting natural language data, namely speech and text.

Abstract: This paper presents a method to calculate the semantic similarity with TongyiciCiLin and Word2vec. In the part of CiLin, the semantic similarity of words is calculated by using the distance ...

word embedding term is used for the representation of words for text analysis. There are different models used for word embedding tasks.

Ion channels are pore-forming membrane proteins that mediate the transport of ions in all living cells (Green, 1999) by controlling cell signaling during the change of the cellular physiology in ...

Note that in this case the most similar words are also variants of the word 'runnnnning' which if different from when using Word2vec which resulted in complety different results. The word 'runnnnnin' ...

Because Keras blog says: An Embedding layer should be fed sequences of integers, i.e. a 2D input of shape (samples, indices) And this Example of How to Construct 1D Convolutional Net on Text #233 ...

Back in 2013, a handful of researchers at Google set loose a neural network on a corpus of three million words taken from Google News texts. The neural net’s goal was to look for patterns in the way ...