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Showing 1 to 3 of 3 for “"fastText"”.

  1. Neural geolocation prediction in Twitter

    … that Convolutional Neural Networks (CNNs) and fastText best encode the the textual and geoloca- tional properties of tweets respectively. fastText emerges as the best model for low resource settings, providing very little degradation with reduction in embedding size.

    uiuc Repository record for Neural geolocation prediction in Twitter (opens in a new tab)

  2. Software Requirements Classification Using Word Embeddings and Convolutional Neural Networks

    … and word embedding models such as word2vec and fastText, we build a Python system that trains and validates configurations of Naïve Bayes and CNN requirements classifiers. Applying our system to a suite of experiments on two well-studied requirements datasets, we recreate or establish the Naïve …

    calpoly Repository record for Software Requirements Classification Using Word Embeddings and Convolutional Neural Networks (opens in a new tab)

  3. Towards new material discovery from CdTe solar cell literature with machine learning

    … The Language models include word2vec, GloVe, fastText and BERT, which are trained on a dataset of more than 22,500 paper abstracts. The performance of these language models is evaluated using a custom test dataset. The test dataset consists of 62-word pairs, which are conceptually related in …

    middlesex Repository record for Towards new material discovery from CdTe solar cell literature with machine learning (opens in a new tab)