On-line communities on the Internet are highly selforganizing, dynamic and ubiquitous. The prime interest of peers in this community is often sharing common interest, even when compromising privacy. This paper presents a peer coordination strategy and a data sharing process for peers on the Internet which allows them to discover their common interest in terms of sets of frequently visited URLs. To this end, sample data was collected by randomly following links on popular websites to simulate the algorithm in operation. Experiments were then performed to compare the number of discovered frequently visited URL sets and association rules with the overhead induced by our network.