Abstract
Archiving graph data over history is demanded in many applications, such as social network and bibliographies. Typically, people are interested in querying temporal graphs. Existing keyword search approaches for graph-structured data are insufficient for querying temporal graphs. This paper initiates the study of supporting keyword-based queries on temporal graphs. We propose a search syntax that is an extension of keyword search, which allows casual users to easily search temporal graphs with temporal predicates and ranking functions. To generate results efficiently, we propose a best path iterator, which finds the "best" paths between two data nodes in each snapshot regarding to three ranking factors. We develop algorithms that efficiently generate top-k query results. Extensive experiments verified the efficiency and effectiveness of our approach.