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Visar resultat 21 - 25 av 244 uppsatser som matchar ovanstående sökkriterier.

1. 21. W2R: an ensemble Anomaly detection model inspired by language models for web application firewalls security

   Magister-uppsats, Högskolan i Halmstad/Akademin för informationsteknologi

   Författare :Zelong Wang; Athira AnilKumar; [2023]
   Nyckelord :web application firewall; anomaly detection; word2vec; BERT; dimension reduction; ensemble model;

   Sammanfattning : Nowadays, web application attacks have increased tremendously due to the large number of users and applications. Thus, industries are paying more attention to using Web application Firewalls and improving their security which acts as a shield between the app and the internet by filtering and monitoring the HTTP traffic. LÄS MER

3. 22. Fake Mass-Produced Advertisements Detection on Global Online Adult Service Websites

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

   Författare :Ernest Pokropek; [2023]
   Nyckelord :Machine learning; Spam detection; Mass-produced spam; Global adult online services; Maskininlärning; Detektering av Spam; Massproducerad Spam; Globala Webbplatser som Erbjuder Eskorttjänster;

   Sammanfattning : A significant amount of sex trafficking victims are being advertised on online adult services, which are currently being flooded with spam. Investigators rely on online adult services to track cases of sex trafficking; however, the ever-increasing volume of spam poses a mounting challenge, making their task progressively more difficult. LÄS MER

4. 23. Recommendation of Text Properties for Short Texts with the Use of Machine Learning : A Comparative Study of State-of-the-Art Techniques Including BERT and GPT-2

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

   Författare :Luciano Zapata; [2023]
   Nyckelord :Text classification; Short texts; Deep Learning; BERT; GPT; GPT-2; Transformers; Natural Language Processing; Textklassificering; Korta Texter; Djupinlärning; BERT; GPT; GPT-2; Transformatorer; Naturlig språkbehandling;

   Sammanfattning : Text mining has gained considerable attention due to the extensive usage ofelectronic documents. The significant increase in electronic document usagehas created a necessity to process and analyze them effectively. LÄS MER

5. 24. Automatic Analysis of Peer Feedback using Machine Learning and Explainable Artificial Intelligence

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

   Författare :Kevin Huang; [2023]
   Nyckelord :Text classification; Peer feedback; Explainable Artificial Intelligence; BERT; RoBERTa; DistilBERT; Decision Tree; MLP; CSCL; STEM education; Textklassificering; Feedback till kamrater; Förklarig Artificiell Intelligens; BERT; RoBERTa; DistilBERT; Decision Tree; MLP; CSCL; STEM-utbildning;

   Sammanfattning : Peer assessment is a process where learners evaluate and provide feedback on one another’s performance, which is critical to the student learning process. Earlier research has shown that it can improve student learning outcomes in various settings, including the setting of engineering education, in which collaborative teaching and learning activities are common. LÄS MER

7. 25. Neural Cleaning of Swedish Textual Data : Using BERT-based methods for Token Classification of Running and Non-Running Text

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

   Författare :Andreas Ericsson; [2023]
   Nyckelord :Natural Language Processing; Text Cleaning; Transformers; BERT; Token Classification; Deep Learning; Språkteknologi; Textrensning; Transformers; BERT; Token-klassificering; Djupinlärning;

   Sammanfattning : Modern natural language processing methods requires big textual datasets to function well. A common method is to scrape the internet to acquire the needed data. This does, however, come with the issue that some of the data may be unwanted – for instance, spam websites. LÄS MER