Mendeley
TY  _  JOUR
ID  -  13980307189772
TI  -  SGF (Semantic Graphs Fusion): A Knowledge-based Representation of Textual Resources for Text Mining Applications
JO  -  Journal of Information Systems and Telecommunication (JIST) 
JA  -  ES
LA  -  en
SN  -  2322-1437
AU  -  Jaderyan Morteza
AU  -  Khotanlou Hassan
AD  -  Bu Ali SIna University
AD  -  Bu Ali Sina Uinversity
Y1  -  2020
PY  -  2020
VL  -  26
IS  -  
SP  -  120
EP  -  133
KW  -  Semantic document representation
KW  -  
KW  -   Ontology
KW  -  
KW  -   Knowledge base (KB)
KW  -  
KW  -   Semantic network
KW  -   
KW  -  Information fusion
KW  -  
DO  -  
N2  -  The proper representation of textual documents has been the greatest challenge in text mining applications. In this paper, a knowledge-based representation model for text documents is introduced. The system works by integrating structured knowledge in the core components of the system. Semantic, lexical, syntactical and structural features are identified by the pre-processing module. The enrichment module is introduced to identify contextually similar concepts and concept maps for improving the representation. The information content of documents and the enriched contents are fused (merged) into the graphical structure of semantic network to form a unified and comprehensive representation of documents. The 20Newsgroup and Reuters-21578 dataset are used for evaluation. The evaluation results suggest that the proposed method exhibits a high level of accuracy, recall and precision. The results also indicate that even when a small portion of information content is available, the proposed method performs well in standard text mining applications. 
UR  - rimag.ir/en/Article/15287
L1  - rimag.ir/en/Article/Download/15287
ER  -  
