Enhancing semantic interoperability in digital library by applying intelligent techniques

In the modern digital libraries an enormous quantity of heterogeneous and distributed information is stored. The growing capacity of digital documents and electronic objects storage has opened up vast new avenues for the distribution of knowledge in virtual space. This data abundance has made the task of locating relevant knowledge more complex. Such complexity drives the need for intelligent techniques for searching and for knowledge retrieval. The Artificial Intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. This paper proposes a new method to gather all these resources and organize so that patrons have everything in one place and able to search and access easily. We propose a comprehensive approach for discovering information objects in large digital collections based on analysis of recorded semantic metadata and the application of artificial intelligence techniques. The work suggests a conceptual architecture for a semantic and intelligent search engine and we also have developed a prototype and tested it for supporting efficient retrieval knowledge from digital libraries.