Sökning: "Spam Classification"

Visar resultat 1 - 5 av 11 uppsatser innehållade orden Spam Classification.

1. 1. 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

3. 2. 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

4. 3. Detection of Vulnerability Scanning Attacks using Machine Learning : Application Layer Intrusion Detection and Prevention by Combining Machine Learning and AppSensor Concepts

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

   Författare :Pojan Shahrivar; [2022]
   Nyckelord :Vulnerability Scanning; Random Forest; Web application security; Next-Gen Web application Firewall; Machine learning; Dynamic application security testing; Intrusion detection prevention;

   Sammanfattning : It is well-established that machine learning techniques have been used with great success in other domains and has been leveraged to deal with sources of evolving abuse, such as spam. This study aims to determine whether machine learning techniques can be used to create a model that detects vulnerability scanning attacks using proprietary real-world data collected from tCell, a web application firewall. LÄS MER

5. 4. Classification of sequence tags from tandem mass spectrometry spectra using machine learning models

   Master-uppsats, Lunds universitet/Examensarbeten i bioinformatik

   Författare :Júlia Ortís Sunyer; [2022]
   Nyckelord :Biology and Life Sciences;

   Sammanfattning : Motivation: Proteomics is the large-scale study of all the proteins found in a cell, tissue or organism. In the last few years, and thanks to the development of mass spectrometry and bioinformatics, proteomics has led the research in several fields, ranging from medicine to agriculture. LÄS MER

7. 5. Taskfinder : Comparison of NLP techniques for textclassification within FMCG stores

   Master-uppsats, Uppsala universitet/Institutionen för elektroteknik

   Författare :Julius Jensen; [2022]
   Nyckelord :LSTM; GRU; Text classification; RNN; Naive bayes;

   Sammanfattning : Natural language processing has many important applications in today, such as translations, spam filters, and other useful products. To achieve these applications supervised and unsupervised machine learning models, have shown to be successful. The most important aspect of these models is what the model can achieve with different datasets. LÄS MER