Sökning: "Movie reviews"

Visar resultat 1 - 5 av 21 uppsatser innehållade orden Movie reviews.

1. 1. Messages from the deep: A reception study of Denis Villeneuve's Dune

   Magister-uppsats, Göteborgs universitet/Institutionen för kulturvetenskaper

   Författare :Sarah R. Kern; [2024-02-06]
   Nyckelord :Hegemony; Production Reception; Discourse; Dominant Negotiated Oppositional; Dune; Representation; Reception study; convergence culture; science fiction; participation culture; fandom;

   Sammanfattning : This essay uses Pierre Bourdieus habitus, symbolic capital, Social fields, Stuart Halls representation theory and Encoding/Decoding system, as well as Henry Jenkins concept of convergence culture and media convergence, to conduct a reception study of Denis Villeneuves 2021 adaption of the science fiction movie Dune. The material collected for the reception study is collected in the form of reviews and features from experts in cinema, juxtaposed against material collected from YouTube in the form of reviews, reaction videos and video essays from social groups sectioned around cinephiles and science fiction fandom. LÄS MER

3. 2. Efficient Sentiment Analysis and Topic Modeling in NLP using Knowledge Distillation and Transfer Learning

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :George Malki; [2023]
   Nyckelord :Large Language Model; RoBERTa; Knowledge distillation; Transfer learning; Sentiment analysis; Topic modeling; Stor språkmodell; RoBERTa; Kunskapsdestillation; överföringsinlärning; Sentimentanalys; Ämnesmodellering;

   Sammanfattning : This abstract presents a study in which knowledge distillation techniques were applied to a Large Language Model (LLM) to create smaller, more efficient models without sacrificing performance. Three configurations of the RoBERTa model were selected as ”student” models to gain knowledge from a pre-trained ”teacher” model. LÄS MER

4. 3. Sentiment Analysis Of IMDB Movie Reviews : A comparative study of Lexicon based approach and BERT Neural Network model

   Kandidat-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

   Författare :Prashuna Sai Surya Vishwitha Domadula; Sai Sumanwita Sayyaparaju; [2023]
   Nyckelord :Bag of Words BoW ; Deep Learning; IMDb Movie Reviews; Machine Learning; Natural Language Processing NLP ; Sentiment Analysis; Term Frequency- Inverse Document Frequency TF-IDF .;

   Sammanfattning : Background: Movies have become an important marketing and advertising tool that can influence consumer behaviour and trends. Reading film reviews is an im- important part of watching a movie, as it can help viewers gain a general under- standing of the film. And also, provide filmmakers with feedback on how their work is being received. LÄS MER

5. 4. Using Semi-Supervised Learning for Email Classification

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Anders Inde; [2022]
   Nyckelord :applied mathematics; semi-supervised learning; self-training; doc2vec; classification; tillämpad matematik; semi-vägledd inlärning; self-training; doc2vec; klassificering;

   Sammanfattning : In this thesis, we investigate the use of self-training, a semi-supervised learning method, to improve binary classification of text documents. This means making use of unlabeled samples, since labeled samples can be expensive to generate. More specifically, we want to classify emails that are retrieved by Skandinaviska Enskilda Banken (SEB). LÄS MER

7. 5. Style Transfer Paraphrasing for Consistency Training in Sentiment Classification

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Núria Casals; [2021]
   Nyckelord :Semi-Supervised Learning; Data Augmentation; Sentiment Classification; Neural Paraphrasing; Semi-övervakad inlärning; Data förändring; Sentimentklassificering; Neural parafrasering;

   Sammanfattning : Text data is easy to retrieve but often expensive to classify, which is why labeled textual data is a resource often lacking in quantity. However, the use of labeled data is crucial in supervised tasks such as text classification, but semi-supervised learning algorithms have shown that the use of unlabeled data during training has the potential to improve model performance, even in comparison to a fully supervised setting. LÄS MER