polito.it
Politecnico di Torino (logo)

TOPOLOGICAL DATA ANALYSIS AND FREQUENT ITEMSETS MINING: POTENTIAL SYNERGIES AND CURRENT CHALLENGES

Rocco Elia

TOPOLOGICAL DATA ANALYSIS AND FREQUENT ITEMSETS MINING: POTENTIAL SYNERGIES AND CURRENT CHALLENGES.

Rel. Francesco Vaccarino, Luca Cagliero. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Matematica, 2022

[img]
Preview
PDF (Tesi_di_laurea) - Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives.

Download (2MB) | Preview
Abstract:

Frequent itemset mining is an established data mining technique focused on discovering recurrent item combinations from transactional data. The extraction process can be modelled as an exploration of a lattice representing high-order item relations and is typically driven by ad hoc quality metrics (e.g., the support index). The exploration of the candidate item relations can be addressed using established graph generalization, called simplicial complexes. This thesis work analyzes the similarities between simplicial complexes and frequent itemsets, discusses the formal relations between them, and prospects for new and more advanced synergies between topological analyses and pattern mining techniques.

Relatori: Francesco Vaccarino, Luca Cagliero
Anno accademico: 2022/23
Tipo di pubblicazione: Elettronica
Numero di pagine: 75
Soggetti:
Corso di laurea: Corso di laurea magistrale in Ingegneria Matematica
Classe di laurea: Nuovo ordinamento > Laurea magistrale > LM-44 - MODELLISTICA MATEMATICO-FISICA PER L'INGEGNERIA
Aziende collaboratrici: NON SPECIFICATO
URI: http://webthesis.biblio.polito.it/id/eprint/24052
Modifica (riservato agli operatori) Modifica (riservato agli operatori)