Title: Automatic conversion of web content into ontology-based resource description language for tourism domain
Authors: Palanisamy Jayaprabha; Arumugam Saradha
Addresses: Department of Computer Applications, Vidyaa Vikas College of Engineering and Technology, Tiruchengode, Tamilnadu, 673 601, India. ' Department of Computer Science Engineering, Institute of Road and Transport Technology, Erode, Tamilnadu, 673 601, India
Abstract: World Wide Web (WWW) becomes the biggest repository of information and most of the data in the web are in unstructured text format. Search engines returns inappropriate result to the users query and the machines find it difficult to integrate the information available in the World Wide Web due to unstructured information. During information retrieval from the internet, the search engines take care of the locations instead of caring about semantics of the information. The above shortcomings are overcome with the evolution of the next generation web 'Semantic Web'. Semantic Web maintains the web in a structured form and makes web accessible data more amenable to machine processing. It becomes a challenging task to the research community to convert, integrate voluminous legacy text data that are unstructured and semi structured into Semantic Web format. This paper proposes a generic approach to transform the existing web contents related to tourism domain into Semantic Web format using RDF with ontology. Such Semantic Web will be advantageous for semantic search and it provides better interoperability.
Keywords: Semantic Web; collaborative movements; collaboration; World Wide Web Consortium; W3C; internet; common frameworks; data sharing; Web Ontology Language; OWL; knowledge representation languages; ontologies; resource description framework; RDF; semantic interoperability; automatic conversion; web content; tourism; web domains; information repositories; text formats; search engines; inappropriate results; information integration; unstructured information; information retrieval; information semantics; next generation; structured forms; web accessible data; machine processing; legacy data; text data; data conversion; data integration; unstructured data; semi structured data; semantic searching; interoperability; innovation; learning.
International Journal of Innovation and Learning, 2012 Vol.12 No.3, pp.267 - 282
Received: 08 May 2021
Accepted: 12 May 2021
Published online: 03 Aug 2012 *