A Novel Framework for Data Extraction from Multiple Repositories and Generation of Ontologies using Inverted Indexing Technique

Recent years have observed the tremendous growth of information through the large number of domains available in the web. Social media (LinkedIn, Twitter etc.) concentrate on handling massive data obtaining from various sources. It is a fact that information retrieval and data extraction are difficult tasks in handling the large collection of web documents. Semantic web is a new technology used to handle the massive raw data to transform it into knowledgeable representation. Traditional search engines use page ranking algorithms to find data from a large data sources. The proposed work is aimed at designing a user interface for data extraction from multiple repositories using Uniform Resource Identifiers (URIs) and applying inverted indexing techniques for generation of Ontologies. These methods may be used to develop efficient semantic web knowledge based systems for retrieving relevant information from the web.