Published in

CIRWORLD, International Journal Of Computers and Technology, (18), p. 7451-7469, 2019

DOI: 10.24297/ijct.v18i0.8063

Links

Tools

Export citation

Search in Google Scholar

A Review on Ontology Learning Approaches of Creating a Topic Map of Cybercrime Research

Journal article published in 2019 by Kijung Lee
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

Full text: Download

Green circle
Preprint: archiving allowed
Green circle
Postprint: archiving allowed
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Conducting an academic research requires getting a firm grasp of ongoing research issues as well as locating research materials effectively. Often research in different fields on a similar topic can assume diverse approaches due to different objectives and research goals in their own fields. Especially in an interdisciplinary research field like cybercrime, many research topics overlap with those of other research fields. Researchers in such a field, therefore, can benefit from understanding the related domains of one’s own research. Topic maps provide methods for understanding research domain and managing relevant information resources at the same time. In this paper, we review a topic map solution to acquire knowledge structure and to locate information resources effectively. We address current problems of cybercrime research, review previous studies that use automated methods for topic map creation, and examine existing sets of methods for automatically extracting topic map components. Especially, the methods we discuss here are text mining techniques for extracting ontology components, denoted as ontology learning.