Ontology Driven Query Expansion in Data Integration

There is huge explosion in the number of new databases, applications and documents in the recent past. This results into lot of redundancy and duplication, which leads to high inefficiency in query processing. Most of the users, who need the information, are naive, because they do not have knowledge of internal structures of databases, contents of data sources and query languages. So it is very difficult for them to query and analyze the desired data from autonomous, geographically distributed and heterogeneous data sources. Query expansion is used to answer the users¿ queries to improve performance and effectiveness of queries. We propose a solution for expanding the users¿ queries with the support of ontology so that recall is improved and information loss is minimized while answering users¿ queries. We have developed rules for expanding the semantically meaningful and illustrate with appropriate example. The results show that our rules are better in terms of recall.