Title

Ontology Based Meta Knowledge Extraction with Semantic Web Tools for Ubiquitous Computing

Document Type

Conference Proceeding

Publication Date

12-7-2016

Abstract

The Semantic Web propels ubiquitous computing by driving the evolution of Web technologies for meaningful user-friendly access. It allows users to apply its potential to find, share and combine information. Ontology based annotations can be used in the Semantic Web to provide better support for organizing knowledge exchange between users. We address this issue to extract meta knowledge from the Web, regardless of devices (e.g., desktops, tablets). Accessing and reusing RDF data from many sources of varying credibility and authority is done through the Semantic Web. This makes the tracking, representation and utilization of various meta knowledge aspects such as reliability, provenance and timestamps extremely important. In this paper, we present an ontology based approach deployed to extract meta knowledge with the following tasks: (1) annotate and extract Wikipedia contents (2) create RDF metadata using the annotations (3) query metadata from the RDF files to obtain the required knowledge. Our general purpose is to link documents to Wikipedia fed to DBpedia / Cyc for extracting the shared lightweight ontology and utilize it for SPARQL querying of documents encompassing meta knowledge. In our approach and experiments we focus on academic scenarios. This knowledge extraction process is useful in developing AI tools and mobile apps where semantics is critical. This work enhances ubiquitous computing by providing efficient and accurate Web access for knowledge extraction on many platforms including desktop computers and mobile devices.

DOI

10.1109/UEMCON.2016.7777817

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