GFocus: User Focus-Based Graph Query Autocompletion

Graph query autocompletion (
gQAC
) generates a small list of ranked query suggestions during the graph query formulation process in a visual environment. The current state-of-the-art of
gQAC
provides suggestions that are formed by adding subgraph increments to arbitrary places of an existing (partial) user query. However, according to the research results on human-computer interaction (HCI), humans can only interact with a small number of recent software artifacts in hand. Hence, many of such suggestions could be irrelevant. In this paper, we present the
GFocus
framework that exploits a novel notion of
user focus of graph query formulation
(or simply
focus
). Intuitively, the focus is the subgraph that a user is working on. We formulate
locality principles
inspired by the HCI research to automatically identify and maintain the focus. We propose novel monotone submodular ranking functions for generating
popular
and
comprehensive
query suggestions only at the focus. In particular, the query suggestions of
GFocus
have high result counts (when they are used as queries) and maximally cover the possible suggestions at the focus. We propose efficient algorithms and an index for ranking the suggestions. Our results show that
GFocus
saves 12-32 percent more mouse clicks and is 35× more efficient than the state-of-the-art competitor.