@Article{JICS-7-025,
author = {G. Mamakis , A. G. Malamos , J. A.Ware and I.Karelli},
title = {Document Classification in Summarization},
journal = {Journal of Information and Computing Science},
year = {2024},
volume = {7},
number = {1},
pages = {025--036},
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. 
},
issn = {1746-7659},
doi = {https://doi.org/},
url = {http://global-sci.org/intro/article_detail/jics/22660.html}
}