TY - GEN
T1 - Answering the why-not questions of graph query autocompletion
AU - Li, Guozhong
AU - Ng, Nathan
AU - Yi, Peipei
AU - ZHANG, Zhiwei
AU - CHOI, Koon Kau
N1 - Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.
PY - 2018
Y1 - 2018
N2 - Graph query autocompletion (gQAC) helps users formulate graph queries in a visual environment (a.k.a GUI). It takes a graph query that the user is formulating as input and generates a ranked list of query suggestions. Since it is impossible to accurately predict the user’s target query, the current state-of-the-art of gQAC sometimes fails to produce useful suggestions. In such scenarios, it is natural for the user to ask why are useful suggestions not returned. In this paper, we address the why-not questions of gQAC. Specifically, given an intermediate query q, a target query qt, and a gQAC system X, the why-not questions of gQAC seek for the minimal refinement of the configuration of X, with respect to a penalty model, such that at least one useful suggestion towards qt appears in the returned suggestions. We propose a generic ranking function for existing gQAC systems. We propose a search algorithm for the why-not questions.
AB - Graph query autocompletion (gQAC) helps users formulate graph queries in a visual environment (a.k.a GUI). It takes a graph query that the user is formulating as input and generates a ranked list of query suggestions. Since it is impossible to accurately predict the user’s target query, the current state-of-the-art of gQAC sometimes fails to produce useful suggestions. In such scenarios, it is natural for the user to ask why are useful suggestions not returned. In this paper, we address the why-not questions of gQAC. Specifically, given an intermediate query q, a target query qt, and a gQAC system X, the why-not questions of gQAC seek for the minimal refinement of the configuration of X, with respect to a penalty model, such that at least one useful suggestion towards qt appears in the returned suggestions. We propose a generic ranking function for existing gQAC systems. We propose a search algorithm for the why-not questions.
KW - Graph query
KW - Query autocompletion
KW - Why-not questions
UR - http://www.scopus.com/inward/record.url?scp=85048032165&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-91452-7_22
DO - 10.1007/978-3-319-91452-7_22
M3 - Conference proceeding
AN - SCOPUS:85048032165
SN - 9783319914510
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 332
EP - 341
BT - Database Systems for Advanced Applications - 23rd International Conference, DASFAA 2018, Proceedings
A2 - Manolopoulos, Yannis
A2 - Li, Jianxin
A2 - Sadiq, Shazia
A2 - Pei, Jian
PB - Springer Verlag
T2 - 23rd International Conference on Database Systems for Advanced Applications, DASFAA 2018
Y2 - 21 May 2018 through 24 May 2018
ER -