Profiler for Smartphone Users Interests Using Modified Hierarchical Agglomerative Clustering Algorithm Based on Browsing History

Nowadays, smartphone has been a life style for many people in the world and it has become an indispensable part of their live. Smartphone provides many applications to support human activity which one of the applications is web browser applications. People spend much time on browsing activity for finding useful information that they are interested on it. It is not easy to find the particular pieces of information that they interested on it. In this paper, user-profiler is presented as way of providing smartphone users with their interest based on their browsing history. In this study, we propose a Modified Hierarchical Agglomerative Clustering algorithm that uses filtering category groups on a server-based application to aid provides smartphone user profile for interests-focused based on browsing history automatically. Based on experimental results, the proposed algorithm can measure degree of smartphone user interest based on browsing history of web browser applications, provides smartphone users interests profile and also outperforms the C4.5 algorithm in execution time on all memory utilization.