Analysis of community question‐answering issues via machine learning and deep learning: State‐of‐the‐art review
Over the last couple of decades, community question‐answering sites (CQAs) have been a
topic of much academic interest. Scholars have often leveraged traditional machine learning …
topic of much academic interest. Scholars have often leveraged traditional machine learning …
Deep learning-based question answering: a survey
Question Answering is a crucial natural language processing task. This field of research has
attracted a sudden amount of interest lately due mainly to the integration of the deep …
attracted a sudden amount of interest lately due mainly to the integration of the deep …
Web traffic anomaly detection using C-LSTM neural networks
Web traffic refers to the amount of data that is sent and received by people visiting online
websites. Web traffic anomalies represent abnormal changes in time series traffic, and it is …
websites. Web traffic anomalies represent abnormal changes in time series traffic, and it is …
[HTML][HTML] Real-time detection of cracks on concrete bridge decks using deep learning in the frequency domain
This paper presents a vision-based crack detection approach for concrete bridge decks
using an integrated one-dimensional convolutional neural network (1D-CNN) and long short …
using an integrated one-dimensional convolutional neural network (1D-CNN) and long short …
A Hybrid CNN–LSTM Algorithm for Online Defect Recognition of CO2 Welding
At present, realizing high-quality automatic welding through online monitoring is a research
focus in engineering applications. In this paper, a CNN–LSTM algorithm is proposed, which …
focus in engineering applications. In this paper, a CNN–LSTM algorithm is proposed, which …
Identifying relations of medications with adverse drug events using recurrent convolutional neural networks and gradient boosting
Objective To develop a natural language processing system that identifies relations of
medications with adverse drug events from clinical narratives. This project is part of the 2018 …
medications with adverse drug events from clinical narratives. This project is part of the 2018 …
The state-of-the-art in expert recommendation systems
N Nikzad–Khasmakhi, MA Balafar… - … Applications of Artificial …, 2019 - Elsevier
The recent rapid growth of the Internet content has led to building recommendation systems
that guide users to their needs through an information retrieving process. An expert …
that guide users to their needs through an information retrieving process. An expert …
[PDF][PDF] Convolutional Neural Networks with LSTM for Intrusion Detection.
M Ahsan, KE Nygard - CATA, 2020 - academia.edu
A variety of attacks are regularly attempted at network infrastructure. With the increasing
development of artificial intelligence algorithms, it has become effective to prevent network …
development of artificial intelligence algorithms, it has become effective to prevent network …
Multiple level hierarchical network-based clause selection for emotion cause extraction
X Yu, W Rong, Z Zhang, Y Ouyang, Z **ong - IEEE Access, 2019 - ieeexplore.ieee.org
Emotion cause extraction is one of the most important applications in natural language
processing tasks. It is a difficult challenge due to the complex semantic information between …
processing tasks. It is a difficult challenge due to the complex semantic information between …
Aspect-level sentiment analysis using context and aspect memory network
With the popularity of social networks, sentiment analysis has become one of the hottest
topics in natural language processing (NLP). As the development of research on the fine …
topics in natural language processing (NLP). As the development of research on the fine …