Sökning: "Sentence Representation Models"

Visar resultat 1 - 5 av 9 uppsatser innehållade orden Sentence Representation Models.

  1. 1. Information Extraction for Test Identification in Repair Reports in the Automotive Domain

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

    Författare :Huang Jie; [2023]
    Nyckelord :text classification; information retrieval; contrastive learning; prompt-based fine-tuning; large language models;

    Sammanfattning : The knowledge of tests conducted on a problematic vehicle is essential for enhancing the efficiency of mechanics. Therefore, identifying the tests performed in each repair case is of utmost importance. This thesis explores techniques for extracting data from unstructured repair reports to identify component tests. LÄS MER

  3. 2. Text Curation for Clustering of Free-text Survey Responses

    Master-uppsats, Linköpings universitet/Institutionen för datavetenskap

    Författare :Anton Gefvert; [2023]
    Nyckelord :Natural Language Processing; NLP; Sentence Representations; Sentence Representation Models; Survey; Surveys; Clustring;

    Sammanfattning : When issuing surveys, having the option for free-text answer fields is only feasible where the number of respondents is small, as the work to summarize the answers becomes unmanageable with a large number of responses. Using NLP techniques to cluster these answers and summarize them would allow a greater range of survey creators to incorporate free-text answers in their survey, without making their workload too large. LÄS MER

  4. 3. Evaluation of the performance of machine learning techniques for email classification

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

    Författare :Isabella Tapper; [2022]
    Nyckelord :Natural Language Processing; Text Representations; Email Classification; Text Classification; Behandling Av Naturliga Språk; Text Representation; epost-klassificering; Textklassificering;

    Sammanfattning : Manual categorization of a mail inbox can often become time-consuming. Therefore many attempts have been made to use machine learning for this task. One essential Natural Language Processing (NLP) task is text classification, which is a big challenge since an NLP engine is not a native speaker of any human language. LÄS MER

  5. 4. Automatic Classification of Conditions for Grants in Appropriation Directions of Government Agencies

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

    Författare :Emma Wallerö; [2022]
    Nyckelord :Text classification; annotation; SVM; BiLSTM; Transformers; BERT; Textklassificering; annotering; annotation; SVM; BiLSTM; Transformers; BERT;

    Sammanfattning : This study explores the possibilities of classifying language as governing or not. The ground premise is to examine how detecting and quantifying governing conditions from thousands of financial grants in appropriation directions can be performed automatically, as well as creating a data set to perform machine learning for this text classification task. LÄS MER

  7. 5. Automated Trouble Report Labeling : In The Telecom Industry

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Institutionen för informationsteknologi

    Författare :Bergkvist Alexander; [2022]
    Nyckelord :Support Ticket labeling;

    Sammanfattning : Trouble reporting is a substantial component in any technical product's maintenance workflow. In this project, we investigated a set of methods for streamlining this workflow, using both software solutions and machine learning. The aim was to find a way of grouping trouble reports for easier analysis and other potential usecases down the line. LÄS MER