Sökning: "Text embedding"

Visar resultat 1 - 5 av 53 uppsatser innehållade orden Text embedding.

  1. 1. Initial Development and Validation of Language-Based Assessments for Meaningful Change

    Kandidat-uppsats, Lunds universitet/Institutionen för psykologi

    Författare :Ulrika Söderström; [2024]
    Nyckelord :meaningful change; depression; Large Language Models; AI; Social Sciences;

    Sammanfattning : Meaningful change has been discussed in multiple studies, with the recurring question of how it could be conceptualized and assessed to identify what determines meaningful change and where it occurs. Previous studies have conducted statistical analyses based on traditional rating scales (i.e., the PHQ-9) to assess meaningful change. LÄS MER

  3. 2. Deep Learning Based Sentiment Analysis

    Master-uppsats, Blekinge Tekniska Högskola/Institutionen för datavetenskap

    Författare :Shashank Kalluri; [2023]
    Nyckelord :Sentiment Analysis; Word Embedding; Deep Learning;

    Sammanfattning : Background: Text data includes things like customer reviews and complaints,tweets from social media platforms. When analyzing text-based data, the SentimentModel is used. Understanding news headlines, blogs, the stock market, politicaldebates, and film reviews some of the areas where sentiment analysis is used. LÄS MER

  4. 3. A lightweight deep learning architecture for text embedding : Comparison between the usage of Transformers and Mixers for textual embedding

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

    Författare :Corentin Royer; [2023]
    Nyckelord :Deep Learning; Entity Retrieval; Mixer; Transformer;

    Sammanfattning : Text embedding is a widely used method for comparing pieces of text together by mapping them to a compact vector space. One such application is deduplication which consists in finding textual records that refer to the same underlying idea in order to merge them or delete one of them. LÄS MER

  5. 4. Speech Classification using Acoustic embedding and Large Language Models Applied on Alzheimer’s Disease Prediction Task

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

    Författare :Maryam Kheirkhahzadeh; [2023]
    Nyckelord :Speech classification; Alzheimer’s disease detection; GPT-3; BERT; Text embedding; Dementia; wav2vec2.0; Klassificering av tal; detektion av Alzheimer’s sjukdom; GPT-3; BERT; textinbäddning; demens; wav2vec2.0;

    Sammanfattning : Alzheimer’s sjukdom är en neurodegenerativ sjukdom som leder till demens. Den kan börja tyst i de tidiga stadierna och fortsätta under åren till en allvarlig och obotlig fas. Språkstörningar uppstår ofta som ett av de tidiga symptomen och kan till slut leda till fullständig mutism i de avancerade stadierna av sjukdomen. LÄS MER

  7. 5. Constructing and representing a knowledge graph(KG) for Positive Energy Districts (PEDs)

    Master-uppsats, Högskolan Dalarna/Institutionen för information och teknik

    Författare :Mahtab Davari; [2023]
    Nyckelord :Knowledge graph; Positive Energy Districts PEDs ; longest path; Questions and Answers; Community Detection; Node Embedding; t-SNE plots; Edge Prediction;

    Sammanfattning : In recent years, knowledge graphs(KGs) have become essential tools for visualizing concepts and retrieving contextual information. However, constructing KGs for new and specialized domains like Positive Energy Districts (PEDs) presents unique challenges, particularly when dealing with unstructured texts and ambiguous concepts from academic articles. LÄS MER