Shiva++: An Enhanced Graph based Ontology Matcher
  With the web getting bigger and assimilating knowledge about different
concepts and domains, it is becoming very difficult for simple database driven
applications to capture the data for a domain. Thus developers have come out
with ontology based systems which can store large amount of information and can
apply reasoning and produce timely information. Thus facilitating effective
knowledge management. Though this approach has made our lives easier, but at
the same time has given rise to another problem. Two different ontologies
assimilating same knowledge tend to use different terms for the same concepts.
This creates confusion among knowledge engineers and workers, as they do not
know which is a better term then the other. Thus we need to merge ontologies
working on same domain so that the engineers can develop a better application
over it. This paper shows the development of one such matcher which merges the
concepts available in two ontologies at two levels; 1) at string level and 2)
at semantic level; thus producing better merged ontologies. We have used a
graph matching technique which works at the core of the system. We have also
evaluated the system and have tested its performance with its predecessor which
works only on string matching. Thus current approach produces better results.
