A robust sentiment analysis method based on sequential combination of convolutional and recursive neural networks

H Sadr, MM Pedram, M Teshnehlab - Neural processing letters, 2019 - Springer
With explosive development of the World Wide Web, an enormous amount of text
information containing users' feeling, emotions and opinions has been generated and is …

CMTSNN: A deep learning model for multiclassification of abnormal and encrypted traffic of Internet of Things

S Zhu, X Xu, H Gao, F Xiao - IEEE Internet of Things Journal, 2023 - ieeexplore.ieee.org
With the increasing types and number of Internet of Things (IoT) devices and malicious
programs and the popularization of encryption technology in the communication process …

CSCNN: cost-sensitive convolutional neural network for encrypted traffic classification

S Soleymanpour, H Sadr… - Neural Processing …, 2021 - Springer
By the rapid development of the Internet and online applications, traffic classification not only
has changed to an interesting topic in the field of computer networks but also plays a key …

Unified topic-based semantic models: a study in computing the semantic relatedness of geographic terms

H Sadr, MN Soleimandarabi… - … Conference on Web …, 2019 - ieeexplore.ieee.org
Over the last decades, a multitude of semantic relatedness measures have been proposed.
Despite an extensive amount of work dedicated to this area of research, the understanding …

An efficient deep learning method for encrypted traffic classification on the web

S Soleymanpour, H Sadr… - 2020 6th International …, 2020 - ieeexplore.ieee.org
Traffic classification plays an important role in network management and cyber-security. With
the development of the Internet, online applications and in the following encrypted …

Presentation of an efficient automatic short answer grading model based on combination of pseudo relevance feedback and semantic relatedness measures

H Sadr, M Nazari Solimandarabi - Journal of Advances in Computer …, 2019 - jacr.sari.iau.ir
Automatic short answer grading (ASAG) is the automated process of assessing answers
based on natural language using computation methods and machine learning algorithms …

Exploring the efficiency of topic-based models in computing semantic relatedness of geographic terms

H Sadr, M Nazari, MM Pedram… - International journal of …, 2019 - ijwr.usc.ac.ir
Large number of semantic relatedness measures have been presented since the last
decades. In spite of an extensive number of studies that have been conducted in this field …

Combination of convolutional neural network and gated recurrent unit for energy aware resource allocation

Z Khodaverdian, H Sadr, SA Edalatpanah… - arXiv preprint arXiv …, 2021 - arxiv.org
Cloud computing service models have experienced rapid growth and inefficient resource
usage is known as one of the greatest causes of high energy consumption in cloud data …

Structure and design of multimodal dataset for automatic regex synthesis methods in Roman Urdu

S Tariq, TA Rana - International Journal of Data Science and Analytics, 2024 - Springer
Automatic regex synthesis involves generation of regular expressions from user-written
natural language descriptions, example strings or both. Daily, countless regex generation …

A deep learning approach to predicting vehicle trajectories in complex road networks

K Sundari, AS Thilak - International Journal of Data Science and Analytics, 2024 - Springer
Accurate prediction of vehicle trajectories is essential for safe and efficient navigation in
urban environments, particularly with the increasing prevalence of autonomous vehicles and …