Abstract:
Recently, many digital libraries have been
constructed and published. Scientific papers often
conclude with a section that lists referenced works
in the form of a reference list or bibliography. This
form of acknowledgment is crucial in helping
readers and reviewers to relate the current work to
its context within the research community’s
discourse. Such bibliographical references that
appear in journal articles can provide valuable
hints for subsequent information extraction.
Therefore, automatic extraction of metadata and
bibliographies is widely studies in recent years.
Decision tree is now widely used machine learning
approach in many areas. This paper applies the
Decision tree for bibliographic metadata extraction
and the experiment show that decision tree classifier
achieves high accuracy result.
