Information Retrieval
Source:
https://bit.ly/30AnGQG
Information management solutions such as Information retrieval systems and Web search engines are fundamental tools for accessing information in today’s world. These systems continue to rapidly evolve, with larger data collections, more complex retrieval strategies and growing query volumes. In satisfying the information needs of millions of users, the quality of the search results and the speed at which the results are returned to the users are two goals that form a natural trade-off, as techniques that improve the former can also reduce the latter. This research investigates the development of efficient query processing infrastructures that make appropriate sacrifices in effectiveness in order to make gains in efficiency, focusing on:
- the design, implementation and deployment of scalable and interactive information systems that can provide answers to complex queries by satisfying strict latency constraints;
- new query processing strategies, for improving the throughput and reduce the latency of search systems;
- new solutions for the efficient deployment and use of innovative search components such as learning to rank algorithms and neural re-ranking systems.
Nicola Tonellotto
Assistant Professor of Computer Engineering
Nicola Tonellotto is Assistant Professor of Computer Engineering at the Information Engineering Department of the University of Pisa, Italy. His research interests include cloud computing, distributed systems, and Web information retrieval.
Publications
Efficient Document Re-Ranking for Transformers by Precomputing Term Representations
Expansion via Prediction of Importance with Contextualization
Training Curricula for Open Domain Answer Re-Ranking
