We present an scalable algorithm for answering multiple conjunctive queries using views. This is an important problem in query optimization, data integration and ontology-based data access. Since rewriting one conjunctive query using views is an NP-hard problem, we develop an approach where answering n queries takes less than n times the cost of answering one query, by compactly representing and indexing common patterns in the input queries and the views. Our initial experimental results show a promising speed up.