Sentence examples for based on continuous bag-of-words from inspiring English sources

Particularly, high-quality word similarity vectors can be learned from billions of words based on continuous bag-of-words or skip-gram model.

It contains two models, continuous bag-of-words (CBOW) and skip gram (SG).

Word2vec is implemented in two different model architectures, continuous bag-of-words and skip-gram.

In the continuous bag-of-words architecture, we have a sequence of words and we need to predict which word is more likely to be the next word in this sequence.

Many studies for this kind of task have been based on the bag-of-words (BoW) framework [6 9].

We used logistic regression, which works based on a bag-of-words, as a baseline and compared the result of applying Deep Learning to logistic regression.

Methods based on the Bag-Of-Words (BoW) model have made a remarkable success in image classification, but many of which do not consider the structure underlying in the dictionary itself in the feature coding procedure.

Two particularly important aspects not widely recognized in the literature are discussed: the difficulties in updating a classifier based on the bag-of-words representation and a major difference between two early naive Bayes models.

With the result of logistic regression based on the bag-of-words model used as a baseline, we investigate whether Deep Learning methods can improve the accuracy of this logistic regression in Big Data.

Briefly, LDA is a probabilistic model based on a "bag-of-words" approach, i.e. it treats a document as an unordered collection of words.

The ECMT contains 2 types of query response modules: the default response module (descriptor), based on a bag-of-words algorithm, and an extended response module (expansion), based on textual indexing, with Oracle Text® [ 21].