Sökning: "Ämnesmodellering"

Hittade 5 uppsatser innehållade ordet Ämnesmodellering.

  1. 1. Efficient Sentiment Analysis and Topic Modeling in NLP using Knowledge Distillation and Transfer Learning

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

    Författare :George Malki; [2023]
    Nyckelord :Large Language Model; RoBERTa; Knowledge distillation; Transfer learning; Sentiment analysis; Topic modeling; Stor språkmodell; RoBERTa; Kunskapsdestillation; överföringsinlärning; Sentimentanalys; Ämnesmodellering;

    Sammanfattning : This abstract presents a study in which knowledge distillation techniques were applied to a Large Language Model (LLM) to create smaller, more efficient models without sacrificing performance. Three configurations of the RoBERTa model were selected as ”student” models to gain knowledge from a pre-trained ”teacher” model. LÄS MER

  3. 2. Index prediction on the Swedish stock market using natural language processing methods on Swedish news

    Master-uppsats, Lunds universitet/Matematisk statistik

    Författare :Erik Ris; Axel Sjöberg; [2021]
    Nyckelord :Stock market prediction; Index prediction; Sentiment analysis; Topic modelling; LDA; Swedish newspaper data; NLP; Machine Learning; RNN; Mathematics and Statistics;

    Sammanfattning : This master thesis explores if topic modelling and sentiment analysis on Swedish financial newspaper data can be used to predict the direction of the Swedish stock market. A pipeline was set up where full length articles as well as article summaries were fed into a topic model and a sentiment analysis model. LÄS MER

  4. 3. The state of network research

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

    Författare :Haoyu Zhu; [2020]
    Nyckelord :Natural Language Processing; Network Spider; Network; Topic Modelling; State of Research.; Naturlig Språkbearbetning; Nätverksspindel; Nätverk; Ämnesmodellering; Forskningstillstånd.;

    Sammanfattning : In the past decades, networking researchers experienced great changes. Being familiar with the development of networking researches is the first step for most scholars to start their work. The targeted areas, useful documents, and active institutions are helpful to set up the new research. LÄS MER

  5. 4. Trolldetektering : En undersökning i lämpligheten att använda ämnesmodellering och klustring för trolldetektion

    Kandidat-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

    Författare :Erik Söderberg; Lili Du; [2016]
    Nyckelord :;

    Sammanfattning : Denna rapport syftar till att undersöka om ämnesmodellering och klustring kan användas till eller underlätta arbetet med trolldetektering. De två ämnesmodellerna Latent Semantic Indexing (LSI) och Latent Dirichlet Allocation (LDA) används samt klustringsmetoden K-means. LÄS MER

  7. 5. Neural probabilistic topic modeling of short and messy text

    Master-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

    Författare :Mattias Harrysson; [2016]
    Nyckelord :Topic modeling; Twitter; Latent Dirichlet allocation; LDA; Re-organized LDA; RO-LDA; GMM; Gaussian mixture model; Unsupervised; Machine learning;

    Sammanfattning : Exploring massive amount of user generated data with topics posits a new way to find useful information. The topics are assumed to be “hidden” and must be “uncovered” by statistical methods such as topic modeling. However, the user generated data is typically short and messy e.g. LÄS MER