Deep learning (DL) models for natural language processing (NLP) tasks often handle
private data, demanding protection against breaches and disclosures. Data protection laws …

With the rapid adoption of online shopping, academic research in the eCommerce domain
has gained traction. However, significant research challenges remain, spanning from classic …

Sentiment analysis is the computational study of people's opinions, sentiments, emotions,
moods, and attitudes. This fascinating problem offers numerous research challenges, but …

Purpose: We propose a patient‐specific algorithm for seizure prediction using multiple
features of spectral power from electroencephalogram (EEG) and support vector machine …

Relevance is the most important factor to assure users' satisfaction in search and the
success of a search engine heavily depends on its performance on relevance. It has been …

Understanding the intent behind a user's query can help search engine to automatically
route the query to some corresponding vertical search engines to obtain particularly relevant …

Pre-trained models (PTMs) have become a fundamental backbone for downstream tasks in
natural language processing and computer vision. Despite initial gains that were obtained …

Most existing approaches for text classification represent texts as vectors of words,
namely``Bag-of-Words.''This text representation results in a very high dimensionality of …

Understanding users' search intent expressed through their search queries is crucial to Web
search and online advertisement. Web query classification (QC) has been widely studied for …

Federated learning has sparkled new interests in the deep learning society to make use of
isolated data sources from independent institutes. With the development of novel training …