Sökning: "Informationsextraktion"

Visar resultat 6 - 10 av 12 uppsatser innehållade ordet Informationsextraktion.

  1. 6. Prerequisites for Extracting Entity Relations from Swedish Texts

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

    Författare :Erik Lenas; [2020]
    Nyckelord :Machine Learning; Natural Language Processing; Relation Extraction; Named Entity Recognition; Coreference resolution; BERT; Maskininlärning; Natural Language Processing; Relationsextrahering; Named Entity Recognition; Coreference resolution; BERT;

    Sammanfattning : Natural language processing (NLP) is a vibrant area of research with many practical applications today like sentiment analyses, text labeling, questioning an- swering, machine translation and automatic text summarizing. At the moment, research is mainly focused on the English language, although many other lan- guages are trying to catch up. LÄS MER

  3. 7. Suitability of OCR Engines in Information Extraction Systems : a Comparative Evaluation

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

    Författare :Zacharias Erlandsson; [2019]
    Nyckelord :;

    Sammanfattning : Previous research has compared the performance of OCR (optical character recognition) engines strictly for character recognition purposes. However, comparisons of OCR engines and their suitability as an intermediate tool for information extraction systems has not previously been examined thoroughly. LÄS MER

  4. 8. Comparison of sequence classification techniques with BERT for named entity recognition

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

    Författare :Erik Rosvall; [2019]
    Nyckelord :;

    Sammanfattning : This thesis takes its starting point from the recent advances in Natural Language Processing being developed upon the Transformer model. One of the significant developments recently was the release of a deep bidirectional encoder called BERT that broke several state of the art results at its release. LÄS MER

  5. 9. Deep Text Mining of Instagram Data Without Strong Supervision

    Master-uppsats, KTH/Programvaruteknik och datorsystem, SCS

    Författare :Kim Hammar; [2018]
    Nyckelord :Natural Language Processing; Information Extraction; Machine Learning; Språkteknologi; Informationsextraktion; Maskinlärning;

    Sammanfattning : With the advent of social media, our online feeds increasingly consist of short, informal, and unstructured text. This data can be analyzed for the purpose of improving user recommendations and detecting trends. LÄS MER

  7. 10. Automatisk extraktion av nyckelord ur ett kundforum

    Kandidat-uppsats, Stockholms universitet/Avdelningen för datorlingvistik

    Författare :Sara Ekman; [2018]
    Nyckelord :Automatic keyword extraction; Information extraction; Noisy text; TF*IDF; User generated text; Användargenererad text; Automatisk nyckelordsextraktion; Brusig text; Informationsextraktion; TF*IDF;

    Sammanfattning : Konversationerna i ett kundforum rör sig över olika ämnen och språket är inkonsekvent. Texterna uppfyller inte de krav som brukar ställas på material inför automatisk nyckelordsextraktion. Uppsatsens undersöker hur nyckelord automatiskt kan extraheras ur ett kundforum trots dessa svårigheter. LÄS MER