• A Comprehensive Approach to Automated Fact-Checking of Podcasts 

      Prabhu, Bhakti (Master thesis, 2024)
      Podcasts have become a prominent medium for disseminating information, yet they remain largely uncharted territory for automated fact-checking systems. This research addresses the critical need for reliable fact-checking ...
    • Agil Utvikling av et Modulært System for Ferie- og Avspaseringshåndtering 

      Alvsåker, Daniel (Bachelor thesis, 2023)
      Denne avhandlingen presenterer design og implementasjon av et system for å strømlinjeforme prosessen med å forespørre ferie og avspasering for ansatte hos Bouvet. Det sentrale målet med prosjektet var å skape et modulært ...
    • Analyse og presentasjon av Mars rover data 

      Fjellheim, Markus (Masteroppgave/UIS-TN-IDE/2020;;, Master thesis, 2020-07-15)
      Space-crafts and their instruments tend to collect way more data on their missions than what can be transmitted back to earth in a timely manner. This leads to the need to prioritize what data is to be downloaded and what ...
    • Deep neural models to represent news events 

      Chechelnytskyy, Denys (Masteroppgave/UIS-TN-IDE/2018;, Master thesis, 2018-05-15)
      The thesis is dedicated to the background linking tasks for news articles, utilizing the deep neural network models. The goal is to retrieve similar articles based on the news story currently viewed. We examined neural and ...
    • Detecting Fake News and Rumors in Twitter Using Deep Neural Networks 

      Mjaaland, Henrik (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-15)
      The scope of this thesis is to detect fake news by classifying them as either real or fake based on article content, metadata, tweets and retweets of news articles from the Politifact dataset using graph neural networks. Fake ...
    • Fact-Checking using Knowledge bases 

      Ramesh, Apoorva; Khurshid, Adil (Master thesis, 2022)
      In today's society, the spread of incorrect information is becoming an increasingly serious issue. Verifying information using unstructured data, such as a text corpus, can be difficult for all claims since they lack ...
    • Generative adversarial networks for bias flipping 

      Le, Nguyen Khoa (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-06-30)
      The disinformation news in media channels such as social media websites or online newspapers has become a big challenge for many organizations, governments, and scientific researchers. In connection to fake news, the ...
    • Graph-based Entity Recognition & Inference and Link Prediction in static Network 

      Alam, Junaid (Master thesis, 2018-06-15)
      The size of data we are producing is exponentially increasing every year. According to former Google CEO Eric Schmidt, we produce as much information in two days now as we did from the dawn of mankind through 2003. The ...
    • Making sense of nonsense : Integrated gradient-based input reduction to improve recall for check-worthy claim detection 

      Sheikhi, Ghazaal; Opdahl, Andreas Lothe; Touileb, Samia; Setty, Vinay (CEUR Workshop Proceedings;, Chapter, 2023)
      Analysing long text documents of political discourse to identify check-worthy claims (claim detection) is known to be an important task in automated fact-checking systems, as it saves the precious time of fact-checkers, ...
    • Report on the 44th European Conference on Information Retrieval (ECIR 2022): The First Major Hybrid IR Conference 

      Balog, Krisztian; Nørvåg, Kjetil; Setty, Vinay (Journal article, 2022)
      The 44th European Conference on Information Retrieval (ECIR’22) was held in Stavanger, Norway. It represents a landmark, not only for being the northernmost ECIR ever, but also for being the first major IR conference in a ...
    • Scaling Network Embeddings 

      Maksyk, Vladyslav (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020)
      A Recommendation System is an intelligent machine learning system that seeks to predict a customer ranked set of personalized products from a dynamic pool of diverse choices. We can define the main objective of such systems ...
    • Semantic Answer Type Prediction using BERT: IAI at the ISWC SMART Task 2020 

      Setty, Vinay; Balog, Krisztian (Chapter, 2020)
      This paper summarizes our participation in the SMART Task of the ISWC 2020 Challenge. A particular question we are interested in answering is how well neural methods, and specifically transformer models, such as BERT, ...
    • Semi-supervised learning for classification of Nordic news articles 

      Fossåen, Nils Magne (Masteroppgave/UIS-TN-IDE/2020;, Master thesis, 2020-07-15)
      Semi-supervised learning defines the techniques that fall in between supervised and unsupervised learning. It is commonly used in classification settings where one has a lesser amount of labeled data compared to unlabeled. ...
    • Smart tekst redigering/utvidelse for fakta sjekk 

      Hersi, Mustafa; Ratdal, Kevin (Bachelor thesis, 2021)
      Chrome utvidelse, falske nyheter, cosinus likhet, fakta sjekking, RESTful API
    • Smart tekst redigering/Utvidelse for faktasjekk 

      Ratdal, Kevin; Hersi, Mustafa (Bachelor thesis, 2021)
      Chrome utvidelse, falske nyheter, cosinus likhet, fakta sjekking, RESTful API
    • Social Media coverage of the fake news 

      Hafezinejad, Ramtin; Mohamed, Awalle; Aabø Lorentzen, Jone (Bachelor thesis, 2021)
      De siste årene har vi sett en betydelig økning i spredningen av feilinformasjon, også kjent som falske nyheter, spesielt på sosiale medier. Enhver bruker kan dele et krav eller en feil fremstilling av noe, og om noen få ...
    • Trustworthy journalism through AI 

      Opdahl, Andreas Lothe; Tessem, Bjørnar; Dang Nguyen, Duc Tien; Motta, Enrico; Setty, Vinay; Throndsen, Eivind; Tverberg, Are; Trattner, Christoph (Peer reviewed; Journal article, 2023-07)
      Quality journalism has become more important than ever due to the need for quality and trustworthy media outlets that can provide accurate information to the public and help to address and counterbalance the wide and rapid ...