Ideas

The following features could be integrated into eRaUI (when running in widget form) to enhance the user experience.

• Social Networking Icons – i.e. facebook and twitter (like / tweet)
• Print Page Icon
• Translate
• Contact Us
• Bookmark
• Feedback and bug reporting capabilities

Existing Softwares which place a widget (toolbar) within the browser window:

• · http://skysa.com
• · http://www.meebo.com/
• · http://www.wibiya.com/
• · http://www.apture.com/

Mechanisms of Deployment:

• · The most simple and feasible mechanism to deploy a browser-based widget is probably to add a javascript include (single line of code) to the section of a webpage.
• · Another possibility is to create a Wibiya Application – allowing eRaUI to be deployed inside Wibiya.
• · Could also feasibly be run as a Browser Extension (like the Google Toolbar) so that it could work with any website or web application.

Algorithms and methods for machine learning

Machine learning algorithms could be used to determine which features of eRaUI are being used on a website and which are redundant. Thus the application could switch features on and off according to the extent to which they are made use of. This might be particularly useful when taking into account detected User-Agent or resolving a client’s IP address to their geographic location. Machine learning algorithms could be used to determine what elements of eRaUI are best for presenting to the user.

Types of Machine Learning Algorithms:

• · Supervised Learning – less suitable because of the need for an element of human supervision.
• · Semi-Supervised Learning – same issues as Supervised Learning in terms of requiring an element of human supervision.
• · Reinforcement Learning – possible
• · Genetic Algorithms – it may be possible to allow the underlying algorithms to modify themselves in such a way as to present the most useful information to the user.

http://www.obitko.com/tutorials/genetic-algorithms/

• · K-Nearest Neighbour algorithm – this is a possibility – although it is the most simplistic of all machine learning algorithms
• · Cluster Analysis – although not an algorithm in itself, this could help with the process of separating user actions in such a way as to make them amenable to certain techniques.
• · Bayesian Methods