Design of Building Automatic Global Concept Indexer for Ontology Alignment

Abstract

Abstract-Users of current World Wide Web (WWW) themselves have to involve in refining their search queries in order to find the exact answers because current WWW is web of documents representing only text, audio, video, images and metadata information (unstructured data) not conceptual information. Computers are used to present those documents only and not for retrieving the desired results which ultimately overburdens the users task. Therefore, to deal with this issue, Tim Berner Lee inventor of WWW envisioned semantic web which prioritizes data than documents and uses ontologies to manage the data. Ontologies have been realized as the key technology to shaping and exploiting information for the effective management of knowledge by establishing a common vocabulary for community members to interlink, combine, and communicate knowledge. But, due to the availability large number of ontologies of same domain, integrating data using ontology has become a big challenge. Therefore, there is a need to unify desperate ontologies belonging to same domain to bridge the gap between conceptualization of the same domain. To deal with this challenge, a framework is being proposed in this paper which works to unify the desperate ontologies by a merging technique. Ontology merging process collects the ontologies of the same domain, unifies their entities (class, property) and forms a global ontology. The empirical result shows the construction of global concept indexer which collects unique concepts by applying matching operation between concepts taken from desperate ontologies.Keyword-Ontology, Concept, concept matching, concept indexer, ontology alignment. I. INTRODUCTION Despite of the huge development in the techniques and tools for making current web more expressive, it is merely an information-publishing medium directed towards human consumption. In the web, computers are used as the information space; their ability is not exploited yet. Moreover, Current tools are not that much expressive to provide direct solutions against user's requirements. Users have to search for a number of web documents for finding the required solution corresponding to their queries. A lot of research is going on to deal with this problem and one of the solutions is data integration but because of data heterogeneity on the web, this task has become a big challenge. Tim-Berner-Lee envisioned semantic web [1] as an extension of the current web in which information is given well-defined meaning, better enabling computers and people to work in cooperation. Its primary concern is to have data on the Web defined and linked in a way that machines can also understand its meaning. Thus machines can also be used for automation, integration and reuse of data across various applications. In order to make computer understand the meaning of the content, semantic web uses the concept of ontology which is specialized in formalizing information of a domain at the conceptual level. Ontology [2] is considered as the backbone of the semantic web. It is an explicit ...

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