While location-based social networks (LBSNs) have become widely used for sharing and consuming location information, a large number of users turn to general web search engines for recreational activity ideas. In these cases, users typically express a query combining desired activity type, constraints and suitability, around an explicit location and time -- for example, "parks for kids in NYC in winter", or "cheap bars for bachelor party in san francisco". In this work we characterize such queries as recreational queries, and propose a relevance framework for ranking points of interest (POIs) to present in the web search recreational vertical using signals from query logs and LBSNs. The first part of this framework is a taxonomy of recreational intents, which we derive from those previously seen in query logs and other behavioral data. Based on the most popular recreational intents, we proceed to outline a new relevance model combining social, geographical and temporal information. We implement a prototype and conduct a preliminary user-study evaluation. Results show the proposed relevance model and bundles greatly improve user satisfaction for recreational queries.