DyGCN-LSTM: A dynamic GCN-LSTM based encoder-decoder framework for multistep traffic prediction
Intelligent transportation systems (ITS) are gaining attraction in large cities for better traffic
management. Traffic forecasting is an important part of ITS, but a difficult one due to the …
management. Traffic forecasting is an important part of ITS, but a difficult one due to the …
gdart: Improving rumor verification in social media with discrete attention representations
Due to the harmful impact of fabricated information on social media, many rumor verification
techniques have been introduced in recent years. Advanced techniques like multi-task …
techniques have been introduced in recent years. Advanced techniques like multi-task …
Rationale aware contrastive learning based approach to classify and summarize crisis-related microblogs
Recent fashion of information propagation on Twitter makes the platform a crucial conduit for
tactical data and emergency responses during disasters. However, the real-time information …
tactical data and emergency responses during disasters. However, the real-time information …
Toxicity, morality, and speech act guided stance detection
In this work, we focus on the task of determining the public attitude toward various social
issues discussed on social media platforms. Platforms such as Twitter, however, are often …
issues discussed on social media platforms. Platforms such as Twitter, however, are often …
Towards sentiment and temporal aided stance detection of climate change tweets
Climate change has become one of the most significant crises of our time. Public opinion on
climate change is influenced by social media platforms such as Twitter, often divided into …
climate change is influenced by social media platforms such as Twitter, often divided into …
Towards an orthogonality constraint-based feature partitioning approach to classify veracity and identify stance overlapping of rumors on twitter
The consequences of fake news and rumors have adversely affected social and political
stability worldwide. Many such incidents have been reported, which resulted in mass chaos …
stability worldwide. Many such incidents have been reported, which resulted in mass chaos …
Let's explain crisis: deep multi-scale hierarchical attention framework for crisis-task identification
Emergency services rely heavily on Twitter for early detection of crisis tasks to enhance
crisis management systems. However, employing state-of-the-art models often face data …
crisis management systems. However, employing state-of-the-art models often face data …
[PDF][PDF] Ontorealsumm: Ontology based real-time tweet summarization
arXiv:2201.06545v1 [cs.SI] 17 Jan 2022 Page 1 arXiv:2201.06545v1 [cs.SI] 17 Jan 2022
OntoRealSumm : Ontology based Real-Time Tweet Summarization PIYUSH KUMAR GARG …
OntoRealSumm : Ontology based Real-Time Tweet Summarization PIYUSH KUMAR GARG …
GES: A New Building Damage Data Augmentation and Detection Method Based on Extremely Imbalanced Data and Unique Spatial Distribution of Satellite Images
X Sha, Z Guo, X Sang, S Wang… - IEEE Journal of Selected …, 2024 - ieeexplore.ieee.org
The statistics of damaged buildings after natural disasters are crucial for rescue operations,
especially for damaged buildings that are extremely challenging for object detection. There …
especially for damaged buildings that are extremely challenging for object detection. There …
ST-AGP: Spatio-Temporal aggregator predictor model for multi-step taxi-demand prediction in cities
Taxi demand prediction in a city is a highly demanded smart city research application for
better traffic strategies formulation. It is essential for the interest of the commuters and the …
better traffic strategies formulation. It is essential for the interest of the commuters and the …