Ontology-assisted automatic precise information extractor for visually impaired inhabitants
As the internet grows rapidly, millions of web pages are being added on a daily basis. The extraction of precise information is becoming more and more difficult as the volume of data on the internet increases. Several search engines and information fetching tools are available on the internet, all of which claim to provide the best crawling facilities. For the most part, these search engines are keyword based. This poses a problem for visually impaired people who want to get the full use from online resources available to other users. Visually impaired users require special aid to get along with any given computer system. Interface and content management are no exception, and special tools are required to facilitate the extraction of relevant information from the internet for visually impaired users. The HOIEV (Heavyweight Ontology Based Information Extraction for Visually impaired User) architecture provides a mechanism for highly precise information extraction using heavyweight ontology and built-in vocal command system for visually impaired internet users. Our prototype intelligent system not only integrates and communicates among different tools, such as voice command parsers, domain ontology extractors and short message engines, but also introduces an autonomous mechanism of information extraction (IE) using heavyweight ontology. In this research we designed domain specific heavyweight ontology using OWL 2 (Web Ontology Language 2) and for axiom writing we used PAL (Prot,g, Axiom Language). We introduced a novel autonomous mechanism for IE by developing prototype software. A series of experiments were designed for the testing and analysis of the performance of heavyweight ontology in general, and our information extraction prototype specifically.
heavyweight ontology for ie intelligent information extraction ie for blind user e-store ontology hybrid technique for ontology modeling