G. Mamakis , A. G. Malamos , J. A.Ware and I.Karelli
Abstract
Document classification and document summarization have a fairly indirect relation as document
classification fall into classification problems as opposed to document summarization, where it is treated as a
problem of semantics. A major part of the summarization process is the identification of the topic or topics
that are discussed in a random document. With that in mind, we try to discover whether document
classification can assist in supervised document summarization. Our approach considers a set of classes, in
which a document may be classified in, and a novel summarization scheme adapted to extract summaries
according the results of the classification. The system is evaluated against a number of supervises and
unsupervised approaches and yields significant results.
