Global versus modular link prediction approach for discapnet: Website focused to visually impaired people

Abstract

Web personalization becomes essential in industries and specially for the case of users with special needs such as visually impaired people. Adaptation may very much speed up the navigation of visually impaired people and contribute to diminish the existing technological gap. This work is the first stage of a web mining process carried out in discapnet: a website created to promote the social and work integration of people with disabilities where slow navigation has been detected. Based on observation in-use where behaviours emerge applying a web mining process to server log data, we designed a system to generate user navigation profiles and adapt to the web site through link prediction. Two approaches for user profiling were implemented: a global system built based on the complete database and a modular approach carried out discovering the navigation profiles within different zones. Although both approaches are effective, the modular approach outperforms. When 25% of the navigation of the new user has happened the designed system is able to propose a set of links where nearly 60% of them (2 out of 3) is among the ones the new user will be using in the future. This will definitely make the navigation easier saving a lot of time.