4 papers · 1 filter
GrIT: Group Informed Transformer for Sequential Recommendation
Adamya Shyam, Venkateswara Rao Kagita, Bharti Rana +1
Sequential recommender systems aim to predict a user's future interests by extracting temporal patterns from their behavioral history. Existing approaches typically employ transfor…
DReX: An Explainable Deep Learning-based Multimodal Recommendation Framework
Adamya Shyam, Venkateswara Rao Kagita, Bharti Rana +1
Multimodal recommender systems leverage diverse data sources, such as user interactions, content features, and contextual information, to address challenges like cold-start and dat…
UniRecSys: A Unified Framework for Personalized, Group, Package, and Package-to-Group Recommendations
Adamya Shyam, Vikas Kumar, Venkateswara Rao Kagita +1
Recommender systems aim to enhance the overall user experience by providing tailored recommendations for a variety of products and services. These systems help users make more info…
Cross-domain Recommender Systems via Multimodal Domain Adaptation
Adamya Shyam, Ramya Kamani, Venkateswara Rao Kagita +1
Collaborative Filtering (CF) has emerged as one of the most prominent implementation strategies for building recommender systems. The key idea is to exploit the usage patterns of i…