Repke, TimTimRepke2024-10-142024-10-142016https://knowledge.hpi.de/handle/123456789/1948In this master’s thesis a system for extracting meta-information, specifically citation data, from webpages is proposed. Machine Learning models like Artificial Neural Networks and Random Forests are trained to classify elements on a given webpage based on visual cues. Visual properties of elements are analysed in detail in order to derive meaningful numerical features for classification. After applying sensible post-processing filters, the system is able to recall up to 80% of the desired data at a precision of up to 90%. Relying purely on visual cues however has it’s limitations for robust extraction of some of the citation data. Possible approaches to facilitate that are discussed at the end.mastersthesis