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Visar resultat 1 - 5 av 12 uppsatser som matchar ovanstående sökkriterier.

1. 1. Exploring GPT models as biomedical knowledge bases : By evaluating prompt methods for extracting information from language models pre-trained on scientific articles

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

   Författare :Ebba Hellberg; [2023]
   Nyckelord :Language model; GPT; knowledge probing; information extraction; prompt methods; Språkmodell; GPT; kunskapsbas; informationsextraktion; prompt-metoder;

   Sammanfattning : Scientific findings recorded in literature help continuously guide scientific advancements, but manual approaches to accessing that knowledge are insufficient due to the sheer quantity of information and data available. Although pre-trained language models are being explored for their utility as knowledge bases and structured data repositories, there is a lack of research for this application in the biomedical domain. LÄS MER

3. 2. CONNECTING THE DOTS : Exploring gene contexts through knowledge-graph representations of gene-information derived from scientific literature

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

   Författare :Henrietta Hellberg; [2023]
   Nyckelord :Knowledge graph construction; Information extraction; Knowledge Graphs; Next-Generation Sequencing; Gene contextualization; Kunskapsgrafkonstruktion; Informationsextraktion; Kunskapsgrafer; Next-Generation Sequencing; Kontextualisering av gener;

   Sammanfattning : Analyzing the data produced by next-generation sequencing technologies relies on access to information synthesized based on previous research findings. The volume of data available in the literature is growing rapidly, and it is becoming increasingly necessary for researchers to use AI or other statistics-based approaches in the analysis of their datasets. LÄS MER

4. 3. A visual approach to web information extraction : Extracting information from e-commerce web pages using object detection

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

   Författare :Alexander Brokking; [2023]
   Nyckelord :Web information extraction; computer vision; object detection; deep learning; Informationsextraktion från webben; datorseende; objektigenkänning; djupinlärning;

   Sammanfattning : Internets enorma omfattning har resulterat i ett överflöd av information som är oorganiserad och spridd över olika hemsidor. Det har varit motivationen för automatisk informationsextraktion av hemsidor sedan internets begynnelse. LÄS MER

5. 4. Coreference Resolution for Swedish

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

   Författare :Lisa Vällfors; [2022]
   Nyckelord :Natural language processing; Information extraction; Machine learning; Random forests; Coreference resolution; Språkteknologi; informationsextraktion; maskininlärning; beslutsträdsinlärning; koreferenslösning;

   Sammanfattning : This report explores possible avenues for developing coreference resolution methods for Swedish. Coreference resolution is an important topic within natural language processing, as it is used as a preprocessing step in various information extraction tasks. LÄS MER

7. 5. Exploring Construction of a Company Domain-Specific Knowledge Graph from Financial Texts Using Hybrid Information Extraction

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

   Författare :Chun-Heng Jen; [2021]
   Nyckelord :Natural Language Processing; Information Extraction; Named Entity Recognition; Relation Extraction; Knowledge Graph; Naturlig språkbehandling; Informationsextraktion; Namngiven Entitetsigenkänning; Relationsextraktion; Kunskapsgraf;

   Sammanfattning : Companies do not exist in isolation. They are embedded in structural relationships with each other. Mapping a given company’s relationships with other companies in terms of competitors, subsidiaries, suppliers, and customers are key to understanding a company’s major risk factors and opportunities. LÄS MER