This paper is published in Volume-4, Issue-5, 2018
Area
Library and Information Science
Author
Nilesh Shewale, Dr. J. Shivarama
Org/Univ
Tata Institute of Social Sciences, Mumbai, Maharashtra, India
Keywords
Digital library, Ontology, Information retrieval, Semantic web technology, Engineering
Citations
IEEE
Nilesh Shewale, Dr. J. Shivarama. Ontology based digital library search system for enhanced information retrieval in engineering domain, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Nilesh Shewale, Dr. J. Shivarama (2018). Ontology based digital library search system for enhanced information retrieval in engineering domain. International Journal of Advance Research, Ideas and Innovations in Technology, 4(5) www.IJARIIT.com.
MLA
Nilesh Shewale, Dr. J. Shivarama. "Ontology based digital library search system for enhanced information retrieval in engineering domain." International Journal of Advance Research, Ideas and Innovations in Technology 4.5 (2018). www.IJARIIT.com.
Nilesh Shewale, Dr. J. Shivarama. Ontology based digital library search system for enhanced information retrieval in engineering domain, International Journal of Advance Research, Ideas and Innovations in Technology, www.IJARIIT.com.
APA
Nilesh Shewale, Dr. J. Shivarama (2018). Ontology based digital library search system for enhanced information retrieval in engineering domain. International Journal of Advance Research, Ideas and Innovations in Technology, 4(5) www.IJARIIT.com.
MLA
Nilesh Shewale, Dr. J. Shivarama. "Ontology based digital library search system for enhanced information retrieval in engineering domain." International Journal of Advance Research, Ideas and Innovations in Technology 4.5 (2018). www.IJARIIT.com.
Abstract
Recent years have seen an exponential increase in the amount of available information in both print medium and electronic medium. The acceptance of electronic/digital medium has increased dramatically in recent years, which had led to the demand for more organized and accessible information in the digital medium. Hence, Digital libraries (DL’s) emerged as the digital counterpart of the traditional library system. Digital library environments had negated the traditional limits on representation and distribution of information, by facilitating global access, round the clock service, classification, and organization of the available information, by adding more information retrieval elements. Another challenge emerged with the advancement of technology, which had increased applications of new forms of information, such as multimedia files, scientific data, unstructured data, semi-structured data, heterogeneous structured data, which is being generated, stored and utilized by digital libraries worldwide. There a large amount of data generated every day for different domains such as medicine, healthcare, engineering, energy, and more. As a consequence, retrieving relevant information related to any domain from heterogeneous knowledge sources had become a challenging task. Ontologies have emerged as a potential solution in this field, as they have the ability to manage information resources efficiently, manage web complexities, and automate bibliofigureic storage and annotation management and more. Ontologies play a significant role in digital libraries by promoting interoperability by defining a common vocabulary for the ease of sharing information in a particular domain. Ontologies also tackle the challenge presented by the availability of heterogeneous information sources and improve the accuracy of information retrieval. This paper discusses, the need and potential applications of domain-specific ontologies and semantic technologies in DL’s, which can be used to address the issue of increasing volume of information as well as enhancing the information retrieval capacity of Digital Libraries. The paper also discusses the designing and developing of domain-specific ontologies for Digital Library and suggest a model of Ontology-based Digital Library search system which retrieves exact results for queries and eliminates irrelevant results by having refined queries