Long short-term memory (LSTM) has transformed both machine learning and
neurocomputing fields. According to several online sources, this model has improved …

Sentiment analysis has been a popular field in natural language processing. Sentiments can
be expressed explicitly or implicitly. Most current studies on sentiment analysis focus on the …

Clustering large and high-dimensional document data has got a great interest. However,
current clustering algorithms lack efficient representation learning. Implementing deep …

Today according to social media, the internet, Etc. Data is rapidly produced and occupies a
large space in systems that have resulted in enormous data warehouses; the progress in …

Water quality data cleaning is important for the management of water environments. A
framework for water quality time series cleaning is proposed in this paper. Considering the …

Most of the existing news-based market prediction techniques disregard conceptual and
emotional relations in the news stream. In this work, we consider the conceptual relationship …

Think tanks have been proved helpful for decision-making in various communities. However,
collecting information manually for think tank construction implies too much time and labor …

Abstract The Densely Connected Network (DenseNet) has been widely recognized as a
highly competitive architecture in Deep Neural Networks. And its most outstanding property …

Deep neural networks have been shown to excel in understanding multimedia by using
latent representations to learn complex and useful abstractions. However, they remain …

Social networking websites such as Twitter and WeChat provide services for microblogging
to its users; they post millions of short messages on it every day. Creating a dataset of these …