Abstract
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In recent years, the information retrieval of multi domain data access has become a critical process. Information retrieval is the process of retrieving relevant information based on user query. The conventional information retrieval methods were employed in multiple domains such as medical, instrumentation, mechanical, electrical, and software. Nevertheless, it had limitations such as index based matching methods, reduced accuracy on matching information, and time consumption for voluminous information. In order to solve these issues, this research work aims at developing an ontology based spatial inverted index list mechanism for multi-domain information retrieval. In the initial stage of the proposed work, user loads the query as input and it is preprocessed to eliminate redundant words for keyword extraction. Words are analyzed for similarity and then it¡¯s evaluated. Finally, the ontology based ranking methodology is applied to rank the similar information based on user query. Here, the rank is evaluated by integration of both semantic searching and ontology based searching. The performance of proposed work is analyzed with existing works.
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