POLIMENOCAMASTRA-THESIS-2019.pdf (1.63 MB)
Download fileOpinion Mining for Decision Making
thesis
posted on 2019-08-06, 00:00 authored by Paolo Polimeno CamastraThis work is concerned with Text Clustering, Sentiment Classification and Transfer Learning
in Sentiment Classification. We choose to work in the domain of online reviews because they
are suitable for our purposes: the dataset comprises reviews’ texts and labels as well as various
categories of products. Labels are needed in order to perform the Supervised Learning part
of our work, i.e. Sentiment Classification, while the presence of different product categories
enable us to have different domains, such as Electronics, Movies, Clothing, etc., which is a
requirement for Transfer Learning. Our main contribution in Text Clustering is in terms of
comparison between clusterings obtained after different text vectorizations: tf-idf+Singular
Value Decomposition (SVD), LDA and word2vec.
History
Advisor
Di Eugenio, BarbaraChair
Di Eugenio, BarbaraDepartment
Computer ScienceDegree Grantor
University of Illinois at ChicagoDegree Level
- Masters