Sökning: "Bidirectional Encoder Representations from Transformers"

Visar resultat 1 - 5 av 31 uppsatser innehållade orden Bidirectional Encoder Representations from Transformers.

  1. 1. Fine-tuning a BERT-based NER Model for Positive Energy Districts

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

    Författare :Karen Ortega; Fei Sun; [2023]
    Nyckelord :Positive Energy District PED ; Named Entity Recognition NER ; Bidirectional Encoder Representations from Transformers BERT ; Pipeline; Fine-tune;

    Sammanfattning : This research presents an innovative approach to extracting information from Positive Energy Districts (PEDs), urban areas generating surplus energy. PEDs are integral to the European Commission's SET Plan, tackling housing challenges arising from population growth. LÄS MER

  3. 2. Classifying personal data on contextual information

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

    Författare :Carl Dath; [2023]
    Nyckelord :Natural Language Processing; Machine Learning; Word2Vec; GloVe; BERT; Personal Data classification; Språkteknologi; Maskininlärning; Personlig Data Klassificering;

    Sammanfattning : In this thesis, a novel approach to classifying personal data is tested. Previous personal data classification models read the personal data before classifying it. However, this thesis instead investigates an approach to classify personal data by looking at contextual information frequently available in data sets. LÄS MER

  4. 3. Annotating Job Titles in Job Ads using Swedish Language Models

    Master-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Markus Ridhagen; [2023]
    Nyckelord :Natural language processing; NLP; Named-entity recognition; NER; Bidirectional Encoder Representations from Transformers; BERT; Active Learning;

    Sammanfattning : This thesis investigates automated annotation approaches to assist public authorities in Sweden in optimizing resource allocation and gaining valuable insights to enhance the preservation of high-quality welfare. The study uses pre-trained Swedish language models for the named entity recognition (NER) task of finding job titles in job advertisements from The Swedish Public Employment Service, Arbetsförmedlingen. LÄS MER

  5. 4. Predicting Political Party Affiliation in the Swedish Parliament using Natural Language Processing

    Master-uppsats, Uppsala universitet/Statistiska institutionen

    Författare :Johannes Zetterberg; [2022]
    Nyckelord :Machine learning; support vector machines; naive Bayes; transformer; BERT; text classification; NLP;

    Sammanfattning : Text classification is a fundamental part of natural language processing. In this thesis, methods for text classification are used in an attempt to predict the political party affiliation of members of parliament (MPs). LÄS MER

  7. 5. Exploring Machine Learning Solutions in the Context of OCR Post-Processing of Invoices

    Uppsats för yrkesexamina på grundnivå, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Jacob Dwyer; Sara Bertse; [2022]
    Nyckelord :Machine learning; Optical character recognition; BERT; Error detection; Invoice; Maskininläsning; Optisk teckenläsning; BERT; Feldetektering; Faktura;

    Sammanfattning : Large corporations receive and send large volumes of invoices containing various fields detailing a transaction. Such fields include VAT, due date, total amount, etc. One common way to automatize invoice processing is optical character recognition (OCR). This technology entails automatic reading of characters from scanned images. LÄS MER