Context-similarity based hotlinks assignment: Model, metrics and algorithm

Enhancing web browsing experience is an open issue frequently dealt using hotlinks assignment between webpages, shortcuts from one node to another. Our aim is to provide a novel, more efficient approach to minimize the expected number of steps needed to reach expected pages when browsing a website. We present a randomized algorithm, which combines the popularity of the webpages, the website structure, and for the first time to the best authors' knowledge, the similarity of context between pages in order to suggest the placement of suitable hotlinks. We verify experimentally that users need less page transitions to reach expected information pages when browsing a website, enhanced using the proposed algorithm.