Ontology Based Approach For Instance Matching
M. Preethi, R. Madhumitha · 2014
One of the important barrier that hinders achieving semantic interoperability is ontology matching. Instance-based ontology matching (IBOM) or concept based ontology matching(CBOM) uses the extension of concepts, the instances directly associated with a concept, to determine whether a pair of concepts is related or not. Practically, instances are often associated with concepts of a single ontology only, rendering IBOM rarely applicable. This is achieved by enriching instances of each dataset with the conceptual annotations of the most similar instances from the other dataset, creating artificially dually annotated instances. We call this technique concept based ontology matching by concept enrichment (CBOMbCE). We are using the instance matching process with web crawlers mediating three world's leading publishers such as Oxford, ScienceDirect and Springer. We are obtaining keywords from the articles of these four journals which acts as the instances. We are collecting all possible journals available in these three websites since the access permission of these three journals can be restricted to some constraints within it. After searching and finding keywords those instances are matched with their ontology creation and further enrichment of instances. Through this technique we will obtain instances that are uncommon among two datasets. Semantic interoperability is a requirement to enable machine computable logic, inferencing, knowledge discovery, and data federation between information systems. This is accomplished by linking each data element to a controlled, shared vocabulary. The Semantic web is nothing but a web with a meaning. It is a group of methods and technologies. It is the total formula of searching, aggregating and combining the web information. It is a logical method of accessing meaningful and accurate information. Data are interlinked. The Semantic Web is an idea of World Wide Web that the Web as a whole can be made more intelligent and perhaps even intuitive about how to serve a user's needs. The goal of Semantic Web Services is to enable dynamic, execution-time discovery, composition, and invocation of Web Services. Ontology matching has taken a critical place for helping heterogeneous resources to interoperate. Ontology alignment tools find classes of data that are semantically equivalent.