RDF and RDFS have recently become very popular as frameworks for representing data and meta-data in form of a domain description, respectively. RDF data can also be thought of as graph data. In this paper, we focus on keyword-based querying of RDF data. In the existing approaches for answering such keyword queries, keywords are mapped to nodes in the graph and their neighborhoods are explored to extract subgraph(s) of the data graph that contain(s) information relevant to the query. In order to restrict the computational effort, a fixed distance bound is used to define the neighborhoods of nodes. In this paper we present an elegant algorithm for keyword query processing on RDF data that does not assume such a fixed bound. The approach adopts a pruned exploration mechanism where closely related nodes are identified, subgraphs are pruned and joined using suitable hook nodes. The system dynamically manages the distance depending on the closeness between the keywords. The working of the algorithm is illustrated using a fragment of AIFB institute data represented as an RDF graph. © 2011 ACM.