Luyi Wang

Information intelligence in cloud computing: how can Vijjana, a collaborative, self-organizing, domain centric knowledge network model help

This research reports agent activities in a collaborative, self-organizing, domain centric knowledge network, called Vijjana. Vijjana means classified knowledge in Sanskrit language. This model has been designed and implemented to assist users engaged in web activities, limiting the data retrieval to desired material only. The model Vijjana sits on the top layer of the cloud computing architecture, and with its agent activities develops a body of intelligent reasoning system which can semantically connect different dispersed users with their own knowledge nets. Vijjana model makes the cloud computing intelligibly usable for connecting different people working with the same domain specific interest. This provides a high order of accountability with assurance on confidentiality, integrity and availability.

Vijjana: A collaborative agent model for creating a knowledge advantage machine

In this paper we describe the Discovery Agent of Vijjana, an umbrella project for creating a person-specific knowledge repository based on classification and analysis. Vijjana provides a framework designed for building collaborative knowledge networks that are domain specific and well bounded in search categories. Using the Vijjana model, we can envision creating an intelligent agent that presents context based information that is drawn from a personalized knowledge base. We call such an agent a Knowledge Advantage Machine (KaM) as it enables a user to take advantage of the personalized knowledge base to perform the task at hand more effectively - in much the same way mechanical advantage had been helping industrial workers. In this paper we discuss only the first part, namely the discovery agent. In this part the focus is on a conceptual way to bridge the gap between the presentation layer and the data access layer which is discussed here using the Object Relational Mapping through the Hibernate framework.

Personal Knowledge Advantage Machine: Pervasive Methods for Semantic Information Retrieval

We present a new framework for visualization and retrieval of knowledge organized as a personal semantic web. This framework is an extension of other semantic web technologies and aims to achieve a fast, elegant solution to carrying your knowledge with you. The architecture described has been developed on the Google Android platform and embedded OpenGL. We call this a Personal Knowledge Advantage Machine (pKaM) as it is designed to access a personalized semantic network using a user-specific ontology. This also includes a graphical browser which enables a user visualize the portion of the semantic network that is relevant to the specific user context.