This paper proposes a cluster-based peer-to-peer system, called PeerCluster, for sharing data over the Internet. In PeerCluster, all participant computers are grouped into various interest clusters, each of which contains computers that have the same interests. The intuition behind the system design is that by logically grouping users interested in similar topics together, we can improve query efficiency. To efficiently route and broadcast messages across/within interest clusters, a hypercube topology is employed. In addition, to ensure that the structure of the interest clusters is not altered by arbitrary node insertions/deletions, we have devised corresponding JOIN and LEAVE protocols. The complexities of these protocols are analyzed. Moreover, we augment PeerCluster with a system recovery mechanism to make it robust against unpredictable computer/network failures. Using an event-driven simulation, we evaluate the performance of our approach by varying several system parameters. The experimental results show that PeerCluster outperforms previous approaches in terms of query efficiency, while still providing the desired functionality of keyword-based search.