On-line communities on the Internet are highly self-organizing, 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 ...
On-line communities on the Internet are highly self-organizing, 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, an algorithm was developed that allows the user to collect URLs of common interest from peers who are currently visiting the same URLs as the user. Using the algorithm, 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. An extended discussion on the experiments performed is presented, by which the viability of the proposed model is demonstrated.