Automatic Extraction of Main Thesis Documents Fields Using Decision Trees

Thesis documents are underestimated even though they hold large sets of useful information -- as they include most of the research information -- , but since they are harder to obtain, researchers were lead to depend on research papers even though they have a size limitation and lack elaboration. A lot of time and effort are invested in research, so having a linkage among researchers based on their work would somehow facilitate solving the research problem process. A major step to tackle this goal is to structure thesis documents by extracting some fields such as title, author and abstract. This paper presents a way to structure a semi-structured thesis documents using decision trees in 4 different ways (Simple, Medium, Complex and using KNIME), they scored an overall accuracy of 99.2%.