Unsupervised Topic Discovery and Text With the emergence of neural networks and representation learning, embedding techniquesrevolutionized textual analysis. Word2Vec [Mikolov et al., 2013] introduced dense wordembeddings that preserved semantic relationships, enabling wordsRead More…
End-to-End Information Extraction End-to-End Information Extraction In today’s data-driven world, the proliferation of unstructured textual data presents bothtremendous opportunities and significant challenges. Vast amounts of text are continuouslygenerated from diverse sources suchRead More…
Semantic-Aware Text Extraction Semantic-Aware Text Extraction with the exponential growth of digital text data generated daily—from social media posts andnews articles to academic papers and corporate documents—there is an increasing need forautomatedRead More…
Context-Aware Topic Modeling Context-Aware Topic ModelingThe introduction of transformer-based architectures, particularly with the development ofmodels such as BERT, RoBERTa, and GPT, has fundamentally transformed the landscape of NLP.These models utilize self-attention mechanismsRead More…
Fine-Grained Aspect Sentiment Fine-Grained Aspect Sentiment Over the years, machine learning techniques such as Support Vector Machines (SVM) andRandom Forests have been employed for ABSA. However, these methods often require extensivefeature engineeringRead More…
Efficient Continuous Connectivity Broadcast The rapid growth of intelligent transportation systems has brought about significantadvancements in vehicular communication technologies, particularly through the developmentof Vehicular Ad Hoc Networks (VANETs). These networks enable vehicle-to-vehicleRead More…
Advanced Scalable Learning Algorithm One of the core challenges in CQA systems is the lack of real-time, scalable methods forpredicting which answers are most likely to be useful or upvoted by theRead More…
A key issue in HSI classification is the curse of dimensionality, wherein each hyperspectralimage contains hundreds of spectral bands. This high dimensionality leads to redundancy,increased computational complexity, and the risk of overfitting,Read More…
INTRODUCTIONAs a result, advanced technologies like AI and IoMT accelerate healthcare systems’ evolution.Meanwhile, efficient healthcare services are essential in remote and underserved regions.In this regard, intelligent systems offer continuous care beyond traditionalRead More…
Introduction Traditionally, emotion recognition systems have relied on a single modality—most commonly,facial expressions, speech, or physiological signals. While these unimodal systems can performadequately under controlled conditions, they often suffer in real-world scenariosRead More…
