Ontology construction for information classification

Following the advent of the Internet technology and the rapid growth of its applications, users have spent long periods of time browsing through the ocean of information found in the Internet. This time-consuming hunt, however, makes searching, retrieving, displaying, integrating and maintaining data such arduous tasks. One way to solve this problem is to study the concept behind the Semantic Web in accordance with the principles of ontology. Apart from facilitating the process of information search in the Semantic Web, ontology also provides a method that will enable computers to exchange, search and identify text information. But establishing the ontology necessitates a great deal of expert assistance; manually setting it up would entail a lot of time, not to mention that there are only a handful of experts available. For this reason, using automatic technology to construct the ontology is a subject worth pursuing. This research uses the theory of formal concept analysis to serve as the groundwork in assembling the different levels of ontological concepts in an automated fashion. An ontology diagram will be presented to show the correlation of concepts and their corresponding significance. Moreover, the experiments of this research select a collection of different concepts in an attempt to classify the relationships between documents and concepts. The objective is to develop an automated technology of ontology construction that will support the present information classification system, as well as to upgrade the ontological aspect of the Semantic Web.