Tipo di tesi
Tesi di laurea magistrale
Titolo
Approximate Retrieval over Learned Sparse Representations: An Investigation of the Scalability on Massive Datasets
Corso di studi
INFORMATICA
Parole chiave
- approximate sparse retrieval
- large-scale retrieval
- learned sparse representation
Data inizio appello
28/02/2025
Consultabilità
Non consultabile
Data di rilascio
28/02/2028
Riassunto (Italiano)
Approximate sparse retrieval over learned sparse representations has emerged as a promising approach for efficient document retrieval. However, scaling these techniques to massive datasets introduces significant challenges related to indexing efficiency, query latency, and memory consumption.
This thesis investigates the scalability of state-of-the-art approximate sparse retrieval methods, with a particular focus on Seismic, a recently proposed retrieval algorithm.
