International Journal of Computer Science Issues

More than a traditional journal...

This is the era of Infopreneurs and web researchers for finding the best fit decisions. For general advice or recommendation, the information need arises. The advice should be such, that best fits the situational need, context and is feasible to afford. Research talks variedly about recommendation systems and expert finding systems for expert advice. These Expert Finding Systems and Recommendation architectures have many other angles which distort the real picture. Many issues like novelty, user friendliness, over-specialization, sparsity, scalability and information overhead due to time and resource, maturation effect of Context, Data and Peoples Knowledge fail to provide the best fit decisions. This makes the research for best fit recommendations or expert finding an infinite, inconsistent and highly circular in nature. This paper introduces a “knowledge prototype” which tries to solve most of the aforesaid issues, and is flexible and easily integrated into any other architecture. The Knowledge Grid or Knowledge prototype traps the dynamic contextual information and can serve any decision seeker at any time even without real time interactions. It harnesses its potential and performance and takes care of Environmental maturation effect.