[HTML][HTML] AlexNet architecture based convolutional neural network for toxic comments classification
I Singh, G Goyal, A Chandel - Journal of King Saud University-Computer …, 2022 - Elsevier
Today online networking has become an indispensable part of life for people all over the
world. It is difficult for users to reduce their internet/online communications, as the flow of …
world. It is difficult for users to reduce their internet/online communications, as the flow of …
Application of machine learning algorithms in wind power: a review
YC Deng, XH Tang, ZY Zhou, Y Yang… - Energy Sources, Part A …, 2021 - Taylor & Francis
Literature review is an overview of existing research, it can also be used to understand
research trends and directions. In recent years, the literature associated with wind power …
research trends and directions. In recent years, the literature associated with wind power …
Generating word embeddings from an extreme learning machine for sentiment analysis and sequence labeling tasks
Word Embeddings are low-dimensional distributed representations that encompass a set of
language modeling and feature learning techniques from Natural Language Processing …
language modeling and feature learning techniques from Natural Language Processing …
Vector representation of words for sentiment analysis using GloVe
Y Sharma, G Agrawal, P Jain… - … conference on intelligent …, 2017 - ieeexplore.ieee.org
Sentiment Analysis is one of the application of Natural Language Processing (NLP)
methodology. The NLP enables to understand the common day to day language of the …
methodology. The NLP enables to understand the common day to day language of the …
Deep convolution neural networks for drug-drug interaction extraction
When a patient takes two or more drugs within a certain time, the efficacy of one drug may
be influenced by the other. This phenomenon is called drug-drug interactions (DDIs). DDIs …
be influenced by the other. This phenomenon is called drug-drug interactions (DDIs). DDIs …
Bi-directional long short term memory using recurrent neural network for biological entity recognition
R Siddalingappa, K Sekar - IAES International Journal of Artificial …, 2022 - eprints.iisc.ac.in
Biomedical named entity recognition (NER) aims at identifying medical entities from
unstructured data. A quintessential task in the supervision of biological databases is …
unstructured data. A quintessential task in the supervision of biological databases is …
GL-LSTM Model For Multi-label Text Classification Of Cardiovascular Disease Reports
In recent years, the rapid growth of electronic data and information has gotten a lot of
attention to find relevant knowledge such as textual information. The goal of automatic text …
attention to find relevant knowledge such as textual information. The goal of automatic text …
Vergleichende Analyse der Word-Embedding-Verfahren Word2Vec und GloVe am Beispiel von Kundenbewertungen eines Online-Versandhändlers
N Horn, MS Erhardt, M Di Stefano, F Bosten… - Künstliche Intelligenz in …, 2020 - Springer
Um eine zielgerichtete Aussage zu Inhalten in Texten zu liefern, werden Bedeutungen von
Wörtern als Vektoren dargestellt. Zur Vektorisierung, welche auch als „Word-Embedding …
Wörtern als Vektoren dargestellt. Zur Vektorisierung, welche auch als „Word-Embedding …
[PDF][PDF] POST-PROCESSING AND DIMENSIONALITY REDUCTION FOR EXTREME LEARNING MACHINE IN TEXT CLASSIFICATION.
Text classification is one of the core technologies of textual analysis, with interesting
applications varying from sentiment classification, language identification to online abuse …
applications varying from sentiment classification, language identification to online abuse …
Convolutional neural network for clinical narrative categorization
Stacked or sequential convolutional layers in a Convolutional Neural Network (CNN) have
shown state-of-the-art results in Image and Pattern Recognition. Recently, CNN's have …
shown state-of-the-art results in Image and Pattern Recognition. Recently, CNN's have …