Document Classification in Summarization
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@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}
}
TY - JOUR
T1 - Document Classification in Summarization
AU - G. Mamakis , A. G. Malamos , J. A.Ware and I.Karelli
JO - Journal of Information and Computing Science
VL - 1
SP - 025
EP - 036
PY - 2024
DA - 2024/01
SN - 7
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/jics/22660.html
KW - Document classification, supervised document summarization, statistics
AB - 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.
G. Mamakis , A. G. Malamos , J. A.Ware and I.Karelli. (2024). Document Classification in Summarization.
Journal of Information and Computing Science. 7 (1).
025-036.
doi:
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