Multi-year digital forensic backlogs have become commonplace in law enforcement
agencies throughout the globe. Digital forensic investigators are overloaded with the volume …

As one of the most advanced techniques in AI, Retrieval-Augmented Generation (RAG) can
offer reliable and up-to-date external knowledge, providing huge convenience for numerous …

Search Ranking and Recommendations are fundamental problems of crucial interest to
major Internet companies, including web search engines, content publishing websites and …

Digital photographs and visual data have become increasingly available, especially on the
Web considered as the largest image database to date. However, the value of multimedia …

The core of information retrieval (IR) is to identify relevant information from large-scale
resources and return it as a ranked list to respond to user's information need. In recent years …

Ranking is a core task in recommender systems, which aims at providing an ordered list of
items to users. Typically, a ranking function is learned from the labeled dataset to optimize …

Combining Large Language Models (LLMs) with search engine services marks a significant
shift in the field of services computing, opening up new possibilities to enhance how we …

Recommender Systems have been playing essential roles in e-commerce portals. Existing
recommendation algorithms usually learn the ranking scores of items by optimizing a single …

The exponential rise of social media websites like Twitter, Facebook and Reddit in
linguistically diverse geographical regions has led to hybridization of popular native …

As the heart of a search engine, the ranking system plays a crucial role in satisfying users'
information demands. More recently, neural rankers fine-tuned from pre-trained language …