The Application of Closed Frequent Subtrees to Authorship Attribution
Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
In this experimental study we compare the authorship attribution performance of two different types of distinguishing features; overlapping syntax subtrees of height one (or small trees) and closed frequent syntax subtrees. Authors and documents used in the experiments are randomly drawn from a large corpus of blog posts and news articles. Results show that small trees outperform closed frequent trees on this data set, both in terms of classifier performance and computational eciency.
Place, publisher, year, edition, pages
, UMNAD, 981
Engineering and Technology
IdentifiersURN: urn:nbn:se:umu:diva-86458OAI: oai:DiVA.org:umu-86458DiVA: diva2:699270
Bachelor of Science Programme in Computing Science