Knowledge Discovery — Semantic Web

Abstract

Knowledge discovery is the process of automatically searching large volume of data for patterns that can be considered knowledge about the data. This is described as deriving knowledge from the input data. Knowledge discovery is defined as “the non-trivial extraction of implicit, unknown, and potentially useful information from the data”. Knowledge discovery is one of the key components of knowledge management system. Today's World Wide Web has large volume of data - billions of documents. So it is a time consuming process to discover effective knowledge from the input data. Here define knowledge discovery meta model (KDM) which defines an ontology for the software and their relationships for the purpose of performing knowledge discovery of existing data. Although search engine technology has improved in recent years, there are still many types of searches that return unsatisfactory results. This situation can be greatly improved if web pages uses a semantic markup language to describe their content, this paper describe SHOE a set of simple HTML ontology Extensions. SHOE allows World-Wide Web authors to annotate their pages with ontology-based knowledge about page contents. This paper contains an examples showing how the use of SHOE can support a new generation of knowledge-based search and knowledge discovery tools that operate on the World-Wide Web. Identifying patterns as the process of knowledge discovery in an university ontology is taken as case study.