Sökning: "wikipedia artiklar"

Visar resultat 1 - 5 av 16 uppsatser innehållade orden wikipedia artiklar.

  1. 1. Generating Wikipedia Articles with Grammatical Framework : A Case Study

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

    Författare :Keivan Matinzadeh; [2023]
    Nyckelord :Grammatical Framework; Computational Linguistics; Natural Language Generation; Computer Science; Grammatical Framework; Beräkningslingvistik; Textgenerering; Datavetenskap;

    Sammanfattning : Natural language generation is a method used to produce understandable texts in human languages from data [1]. Grammatical Framework is a grammar formalism and a functional programming language using a nonstatistical approach to build natural language applications. LÄS MER

  3. 2. A Method for the Assisted Translation of QA Datasets Using Multilingual Sentence Embeddings

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

    Författare :Thomas Vakili; [2020]
    Nyckelord :Natural Language Processing NLP ; Information Retrieval IR ; Multilingual Sentence Embeddings; QADatasets; Lesser-Resourced Languages; språkteknologi; informationssökning; språkagnostiska meningsvektorer; fråga-svarskorpusar; språk med mindre resurser;

    Sammanfattning : This thesis presents a method which reduces the amount of labour required to translate the English question answering dataset SQuAD into Swedish. The purpose of the study is to contribute to shrinking the gap between natural language processing research in English and research in lesser-resourced languages by providing a method for creating datasets in these languages which are counterparts to those used in English. LÄS MER

  4. 3. A Method for Automatic Question Answering in Swedish based on BERT

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

    Författare :Tove Tengvall; [2020]
    Nyckelord :;

    Sammanfattning : This report presents a method for doing automatic reading comprehension in Swedish. The method is based on BERT, a pre-trained Swedish neuralnetwork language model, which was fine-tuned on a Swedish question-answer corpus. LÄS MER

  5. 4. Evaluating a Novel, Scalable Natural Language Processing Heuristic for Determining Semantic Relatedness

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

    Författare :Mattias Bergström; Per Fahlander; [2019]
    Nyckelord :;

    Sammanfattning :  Distributional semantics is a recent research field aiming to quantify how close one text is to another in terms of contextual meaning. In this study we propose and evaluate a novel distributional semantics model on how much agreement its predictions can yield with a set of 12,227 human opinions. LÄS MER

  7. 5. Content based filtering for application software

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

    Författare :David Lindström; [2018]
    Nyckelord :Recommender system; content based filtering;

    Sammanfattning : In the study, two methods for recommending application software were implemented and evaluated based on their ability to recommend alternative applications with related functionality to the one that a user is currently browsing. One method was based on Term Frequency–Inverse Document Frequency (TF-IDF) and the other was based on Latent Semantic Indexing (LSI). LÄS MER