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The analysis of text categorization represented with word embeddings using homogeneous classifiers
(Institute of Electrical and Electronics Engineers Inc., 2019)
Text data mining is the process of extracting and analyzing valuable information from text. A text data mining process generally consists of lexical and syntax analysis of input text data, the removal of non-informative ...
The evaluation of word embedding models and deep learning algorithms for Turkish text classification
(IEEE (Institute of Electrical and Electronics Engineers), 2019)
The use of word embedding models and deep learning algorithms are currently the most common and popular trends to enhance the overall performance of a text classification/categorization system. Word embedding models are ...
An improved demand forecasting model using deep learning approach and proposed decision integration strategy for supply chain
(Wiley-Hindawi, 2019)
Demand forecasting is one of the main issues of supply chains. It aimed to optimize stocks, reduce costs, and increase sales, profit, and customer loyalty. For this purpose, historical data can be analyzed to improve demand ...
Mood detection from physical and neurophysical data using deep learning models
(Wiley, 2019)
Nowadays, smart devices as a part of daily life collect data about their users with the help of sensors placed on them. Sensor data are usually physical data but mobile applications collect more than physical data like ...