Information acquisition is a great challenge in the context of a continually growing Web. Nowadays, large Web search engines are primarily designed to assist an information pull by the user. On this platform, only actual information needs are handled without assistance of long-term needs. To overcome these shortcomings we propose a cooperative system for information pull and push on a peer-to-peer architecture. In this paper we present a hybrid network for a collaborative search environment, based on a local personalization strategy on each peer, and a highly-available Web search service (e.g. Google). Each peer participates in the Pull-Push Cycle, and has the function of an information consumer as well as an information provider. Hence, long-term information needs can be identified without any context restrictions, and recommendations are computed based on Virtual Knowledge Communities.