Please use this identifier to cite or link to this item: https://research.matf.bg.ac.rs/handle/123456789/2918
Title: Ontology-driven conceptual document classification
Authors: Graovac, Jelena 
Pavlović-Lažetić, Gordana
Affiliations: Informatics and Computer Science 
Keywords: Artificial intelligence;clustering and classification methods;knowledge discovery and information retrieval;knowledge-based systems;symbolic systems
Issue Date: 2010
Rank: M33
Publisher: SciTePress
Related Publication(s): Proceedings of the International Conference on Knowledge Discovery and Information Retrieval (KDIR 2010)
Conference: International Conference on Knowledge Discovery and Information Retrieval (KDIR) ([2] ; 2010 ; Valencia)
Abstract: 
Document classification based on the lexical-semantic network, wordnet, is presented. Two types of document classification in Serbian have been experimented with – classification based on chosen concepts from Serbian WordNet (SWN) and proper names-based classification. Conceptual document classification criteria are constructed from hierarchies rooted in a set of chosen concepts (first case) or in hierarchies rooted in some of the proper names' hypernyms (second case). A classificator of the first type is trained and then tested on an indexed and already classified Ebart corpus of Serbian newspapers (476917 articles). Precision, recall and F-measure show that this type of classification is promising although incomplete due mainly to SWN incompleteness. In the context of proper names-based classification, a proper names ontology based on the SWN is presented in the paper. A distance based similarity measure is defined, based on Euclidean and Manhattan distances. Classification of a su (More)
URI: https://research.matf.bg.ac.rs/handle/123456789/2918
DOI: 10.5220/0003063903830386
Appears in Collections:Research outputs

Show full item record

Google ScholarTM

Check

Altmetric

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.