Daniela Martorana
Mining user reviews on public transport systems using machine learning techniques.
Rel. Silvia Anna Chiusano, Luca Cagliero, Elena Daraio. Politecnico di Torino, Corso di laurea magistrale in Data Science And Engineering, 2022
|
Preview |
PDF (Tesi_di_laurea)
- Tesi
Licenza: Creative Commons Attribution Non-commercial No Derivatives. Download (4MB) | Preview |
Abstract
Nowadays, with the increasingly pervasive advent of the digital world, we are inundated with large amounts of data in text format relating to many everyday contexts. One important part of this data concerns user reviews of products and services. Analysing this large information content with machine learning algorithms can provide very useful information for companies and vendors to make improvements. This type of text analysis with machine learning belongs to the branch of Natural Language Processing (NLP) and more specifically to the branch of Sentiment Analysis. As far as sentiment analysis is concerned, there are many methods to carry out this kind of analysis in literature.
Roughly speaking, there are mainly two ways to address the problem of sentiment analysis: rule or lexicon-based approaches and machine learning algorithms, which are then divided into classical machine learning algorithms (e.g
Relatori
Anno Accademico
Tipo di pubblicazione
Numero di pagine
Corso di laurea
Classe di laurea
URI
![]() |
Modifica (riservato agli operatori) |
