Sökning: "Named Entity Recognition"

Visar resultat 11 - 15 av 62 uppsatser innehållade orden Named Entity Recognition.

1. 11. 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

3. 12. Exploring Cross-Lingual Transfer Learning for Swedish Named Entity Recognition : Fine-tuning of English and Multilingual Pre-trained Models

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

   Författare :Daniel Lai Wikström; Axel Sparr; [2023]
   Nyckelord :NER; Cross-lingual transfer; Transformer; BERT; Deep Learning; namnigenkänning; NER; multilingvistisk överföring; Transformer; BERT; deep learning;

   Sammanfattning : Named Entity Recognition (NER) is a critical task in Natural Language Processing (NLP), and recent advancements in language model pre-training have significantly improved its performance. However, this improvement is not universally applicable due to a lack of large pre-training datasets or computational budget for smaller languages. LÄS MER

4. 13. Named Entity Recognition on Transaction Descriptions

   Master-uppsats, Lunds universitet/Institutionen för datavetenskap

   Författare :Nik Johansson; [2022]
   Nyckelord :Technology and Engineering;

   Sammanfattning : With the surge of open banking, there is a large increase in applications based on transaction data. Therefore, there is a need for being able to extract important information from Swedish transaction descriptions in a structured way. LÄS MER

5. 14. Multilingual Transformer Models for Maltese Named Entity Recognition

   Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

   Författare :Kris Farrugia; [2022]
   Nyckelord :low-resource; named-entity; information extraction; Maltese;

   Sammanfattning : The recently developed state-of-the-art models for Named Entity Recognition are heavily dependent upon huge amounts of available annotated data. Consequently, it is extremely challenging for data-scarce languages to obtain significant result. LÄS MER

7. 15. Domain Adaptation with N-gram Language Models for Swedish Automatic Speech Recognition : Using text data augmentation to create domain-specific n-gram models for a Swedish open-source wav2vec 2.0 model

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

   Författare :Viktor Enzell; [2022]
   Nyckelord :Automatic Speech Recognition; Domain Adaptation; Language Models; Ngram Models; Wav2vec2; Taligenkänning; Domänanpassning; Språkmodeller; N-gramModeller; Wav2vec2;

   Sammanfattning : Automatic Speech Recognition (ASR) enables a wide variety of practical applications. However, many applications have their own domain-specific words, creating a gap between training and test data when used in practice. LÄS MER