Tesi etd-03182024-135622 |
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Tipo di tesi
Tesi di laurea magistrale
Autore
GARGIULO, FRANCESCO
URN
etd-03182024-135622
Titolo
Efficient indexing of dense and sparse attributes
Dipartimento
INFORMATICA
Corso di studi
INFORMATICA
Relatori
relatore Venturini, Rossano
correlatore Gog, Simon
correlatore Dahlmann, Leonard
correlatore Gog, Simon
correlatore Dahlmann, Leonard
Parole chiave
- algorithms
- information retrieval
- succinct data structures
- forward index
- indexing
Data inizio appello
12/04/2024
Consultabilità
Non consultabile
Data di rilascio
12/04/2094
Riassunto
This thesis explores various methodologies to represent the forward index of a dataset, emphasizing the utilization of succinct data structures to achieve enhancements in both space utilization and access times.
The work begins by implementing a baseline index, which serves as a benchmark for evaluating the efficacy of the proposed solutions. Through a gradual refinement process, the proposed indices progressively enhance resource utilization until culminating in a substantial improvement with the final index solution.
This process highlights the tangible benefits of adopting succinct data structures in data indexing systems.
The work begins by implementing a baseline index, which serves as a benchmark for evaluating the efficacy of the proposed solutions. Through a gradual refinement process, the proposed indices progressively enhance resource utilization until culminating in a substantial improvement with the final index solution.
This process highlights the tangible benefits of adopting succinct data structures in data indexing systems.
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