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Showing result 1 - 5 of 7 essays matching the above criteria.

  1. 1. Advancing Keyword Clustering Techniques: A Comparative Exploration of Supervised and Unsupervised Methods : Investigating the Effectiveness and Performance of Supervised and Unsupervised Methods with Sentence Embeddings

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Filippo Caliò; [2023]
    Keywords : Keyword Clustering; Supervised Learning; Unsupervised Learning; Cluster Labels; Natural Language Processing; Sentence Embeddings; Nyckelord Klustring; övervakad inlärning; oövervakad inlärning; klustermärkning; naturlig språkbehandling; Inbäddning av meningar;

    Abstract : Clustering keywords is an important Natural Language Processing task that can be adopted by several businesses since it helps to organize and group related keywords together. By clustering keywords, businesses can better understand the topics their customers are interested in. READ MORE

  3. 2. Fine-Tuning Pre-Trained Language Models for CEFR-Level and Keyword Conditioned Text Generation : A comparison between Google’s T5 and OpenAI’s GPT-2

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Quintus Roos; [2022]
    Keywords : Transformed-based Pre-trained Language Models; Natural Language Processing; Natural Language Generation; Conditional Text Generation; Text Classification; Fine-tuning; English Language Learning.; Transformbaserade förtränade språkmodeller; naturlig språkbehandling; naturlig språkgenerering; betingad textgenerering; finjustering; instruktionsjustering; engelska inlärning.;

    Abstract : This thesis investigates the possibilities of conditionally generating English sentences based on keywords-framing content and different difficulty levels of vocabulary. It aims to contribute to the field of Conditional Text Generation (CTG), a type of Natural Language Generation (NLG), where the process of creating text is based on a set of conditions. READ MORE

  4. 3. Bootstrapping Annotated Job Ads using Named Entity Recognition and Swedish Language Models

    University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Author : Anna Nyqvist; [2021]
    Keywords : labour market; named entity recognition; natural language processing; BERT; data annotation; inter-annotator agreement; arbetsmarknad; namngiven entitetsigenkänning; naturlig språkbehandling; BERT; dataannotering; interannoterar-överenskommelse;

    Abstract : Named entity recognition (NER) is a task that concerns detecting and categorising certain information in text. A promising approach for NER that recently has emerged is fine-tuning Transformer-based language models for this specific task. However, these models may require a relatively large quantity of labelled data to perform well. READ MORE

  5. 4. Hur matematikundervisning som har vardagliga samband påverkar elevernas lärande

    University essay from Malmö universitet/Fakulteten för lärande och samhälle (LS)

    Author : Kondwelan James Tembo; [2020]
    Keywords : everyday connection; interest; mathematics teaching; motivation; understanding; intresse; matematikundervisning; motivation; lärande; vardagsanknytning;

    Abstract : Denna studie fokuserar på problemet där flesta elever tappar intresse, motivation och lust att lära sig matematik eftersom de upplever att det är ett svårt ämne. Syftet med detta arbete å andra sidan är att undersöka om hur matematikundervisning som har vardagliga samband påverkar elevernas lärande. READ MORE

  6. 5. Comparison of supervised machine learning models forpredicting TV-ratings

    University essay from KTH/Hälsoinformatik och logistik

    Author : Sebastian Elf; Christopher Öqvist; [2020]
    Keywords : ;

    Abstract : Abstract Manual prediction of TV-ratings to use for program and advertisement placement can be costly if they are wrong, as well as time-consuming. This thesis evaluates different supervised machine learning models to see if the process of predicting TV-ratings can be automated with better accuracy than the manual process. READ MORE