Abstract. Many applications involve queries that combine spatial, temporal and textual filters. In this paper, we address the problem of effcient evaluation of queries that perform spatial, temporal and keyword-based filtering on historical movement data of objects which are additionally associated with textual information in the form of keywords. Our work combines and builds upon concepts and techniques for spatio-temporal and spatio-textual queries, proposing two hybrid indexes for this purpose. An experimental evaluation of the proposed approaches is presented, using real-world datasets from two different types of sources.