Sökning: "movie score"

Visar resultat 1 - 5 av 12 uppsatser innehållade orden movie score.

  1. 1. 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

  3. 2. Developing Machine Learning-based Recommender System on Movie Genres Using KNN

    Master-uppsats, Stockholms universitet/Institutionen för data- och systemvetenskap

    Författare :Anthony Ezeh; [2023]
    Nyckelord :: Movie Recommender System; Machine Learning; Content-based Filtering; Collaborative Filtering; KNN Algorithms; Classification Algorithm;

    Sammanfattning : With an overwhelming number of movies available globally, it can be a daunting task for users to find movies that cater to their individual preferences. The vast selection can often leave people feeling overwhelmed, making it challenging to pick a suitable movie. LÄS MER

  4. 3. 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

  5. 4. Generative Adversarial Networks in Lip-Synchronized Deepfakes for Personalized Video Messages

    Master-uppsats, Lunds universitet/Matematik LTH

    Författare :Johan Liljegren; Pontus Nordqvist; [2021]
    Nyckelord :Generative Adversarial Networks; GAN; Lip-Synchronization; Deepfake; Deep Learning; Autoencoder; WGAN; WGAN-GP; L1WGAN-GP; Skip-Connections; FID-Score; Mathematics and Statistics; Technology and Engineering;

    Sammanfattning : The recent progress of deep learning has enabled more powerful frameworks to create good-quality deepfakes. Deepfakes, which are mostly known for malicious purposes, have great potential to be useful in areas such as the movie industry, education, and personalized messaging. LÄS MER

  7. 5. Text Content Features for Hybrid Recommendations : Pre-trained Language Models for Better Recommendations

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

    Författare :Mariya Lazarova; [2021]
    Nyckelord :Recommendation Systems; Natural Language Processing; Pre-trained language models; BERT; Two-tower networks; Rekommendationssystem; Naturlig språkbehandling; Förtränande språkmodeller; BERT; Två-tornnätverk.;

    Sammanfattning : Nowadays, with the ever growing availability of options in many areas of our lives, it is crucial to have good ways to navigate your choices. This is why recommendation engines’ role is growing more important. Recommenders are often based on user-item interaction. LÄS MER