Banyak aplikasi natural language processing (NLP) mempelajari penyematan kata dengan melatih koleksi dokumen yang besar. Representasi vektor yang telah dilatih sebelumnya ini memberikan informasi tentang semantik dan distribusi kata yang biasanya meningkatkan generalisasi model lain yang kemudian dilatih pada...
A large number of studies have been conducted in the literature on the formation of languages and natural language processing processes. It has been observed that these studies contain differences in terms of analysis, approach and method. In the study, a model has been propos...
NATURAL language processingEffort to answer, how to computationally process text data from patient consultations into an input that can be understood into accurate results to be able to provide recommendations from the consultations that patients complain about. Building and developing Artif...
In this study, metadata extraction and classification from the contents of learning objects were made automatically by using deep learning methods such as Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and Natural Language Processing (NLP). The success and accu...
Bag of Words (BoW), TF-IDF, FastText and Word2Vec text representation methods were used to represent the data set that was cleaned using Natural Language Processing methods. During the training and testing of the data set, the k-fold cross validation method was used, ...
In the first step of the study, basic natural language processing techniques were applied on the selected data set. Then, feature extraction techniques such as bag of words (BoW), term frequency (TF) and term-document matrix (t-DM) were performed to represent the data set...