Research Article
A New Method for Conceptual Classification of Multi-label Texts in Web Mining Based on Ontology
393 downloads
@INPROCEEDINGS{10.1007/978-3-642-32573-1_7, author={Mahnaz Khani and Hamid Naji and Mohammad Malakooti}, title={A New Method for Conceptual Classification of Multi-label Texts in Web Mining Based on Ontology}, proceedings={Signal Processing and Information Technology. First International Joint Conference, SPIT 2011 and IPC 2011, Amsterdam, The Netherlands, December 1-2, 2011, Revised Selected Papers}, proceedings_a={SPIT \& IPC}, year={2012}, month={10}, keywords={Ontology TSR Conceptual Classification Web Mining}, doi={10.1007/978-3-642-32573-1_7} }- Mahnaz Khani
Hamid Naji
Mohammad Malakooti
Year: 2012
A New Method for Conceptual Classification of Multi-label Texts in Web Mining Based on Ontology
SPIT & IPC
Springer
DOI: 10.1007/978-3-642-32573-1_7
Abstract
This paper presents a new inductive learning method for conceptual classification of multi-label texts in web mining based on ontology through Term Space Reduction (TSR) and through using mutual information measure. Laboratory results show the presented method has high precision in compare to existing methods of SVM, Find Similar, Naïve Bayes Nets, and Decision Trees. It should be noted that break–even point is used in micro–averaging for appropriate classification of data complex entitled "Reuters–21578 Apte Split".
Copyright © 2011–2024 ICST
