Essays about: "Ordvektormodeller"

Found 3 essays containing the word Ordvektormodeller.

  1. 1. Automatic fingerprinting of websites

    University essay from KTH/Hälsoinformatik och logistik

    Author : Alfred Berg; Norton Lamberg; [2020]
    Keywords : ;

    Abstract : Abstract Fingerprinting a website is the process of identifying what technologies a websiteuses, such as their used web applications and JavaScript frameworks. Currentfingerprinting methods use manually created fingerprints for each technology itlooks for. READ MORE

  2. 2. Text feature mining using pre-trained word embeddings

    University essay from KTH/Matematisk statistik

    Author : Henrik Sjökvist; [2018]
    Keywords : Word embeddings; Feature engineering; Unsupervised learning; Deep learning; fast Text; Operational risk; Ordvektorer; Attributgenerering; Oövervakat lärande; Djupinlärning; fastText; Operativ risk;

    Abstract : This thesis explores a machine learning task where the data contains not only numerical features but also free-text features. In order to employ a supervised classifier and make predictions, the free-text features must be converted into numerical features.  In this thesis, an algorithm is developed to perform that conversion. READ MORE

  3. 3. The Effect of Data Quantity on Dialog System Input Classification Models

    University essay from KTH/Hälsoinformatik och logistik

    Author : Johan Lipecki; Viggo Lundén; [2018]
    Keywords : Chatbot; Chatterbot; Virtual Assistant; Dialog System; Natural Language Understanding; Word Embedding; Word Vector Models; Text Classification; Chattbot; Virtuell Assistent; Dialogsystem; Naturlig språkbehandling; Ordinbäddning; Ordvektormodeller; Textklassificering;

    Abstract : This paper researches how different amounts of data affect different word vector models for classification of dialog system user input. A hypothesis is tested that there is a data threshold for dense vector models to reach the state-of-the-art performance that have been shown with recent research, and that character-level n-gram word-vector classifiers are especially suited for Swedish classifiers–because of compounding and the character-level n-gram model ability to vectorize out-of-vocabulary words. READ MORE